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in the Introduction to R workshop, and will introduce more advanced tools, including creating your own custom functions, iterating with purrr map functions, advanced data manipulations with dplyr, and reshaping and joining datasets in R.\n\n**Who**: The course is aimed at graduate students, postdocs, staff, faculty, and other researchers across campus who are interested in taking their R skills to the next level to learn how to conduct more sophisticated data manipulations and analysis. \n\nParticipants in this workshop should already be comfortable working in Quarto (or R Markdown) documents in RStudio, and have basic knowledge of the the R programming language and the tidyverse, including the dplyr select, filter, mutate, and summarize functions, as well as creating basic visualizations using ggplot2.\n\n**Requirements**: Participants must bring a laptop onto which they can [download R and Rstudio](https://posit.co/download/rstudio-desktop/) (and you should do so before the workshop).\n\n**Contact**: Please email andrew.george@hsc.utah.edu or rebecca.barter@hsc.utah.edu for more information.\n\n## Schedule\n\nNote that the schedule below serves as a guideline. The start, end, and break times are fixed, but timing for each topics covered may vary as we may go faster or slower through the content.\n\n\n\n| Time | Topic | Incomplete .qmd | Complete .qmd |\n| ----:|:----|:---------------|:-----------------|\n| 9:00 | Introduction and Setup | | |\n| 9:30 | Writing Functions | | |\n| 10:30 | [Break] | | |\n| 10:45 | Iteration with Purrr | | |\n| 12:00 | [Lunch] | | |\n| 1:00 | Advanced Data Manipulations with Dplyr | | |\n| 2:30 | [Break] | | |\n| 2:45 | Reshaping and Joining Data | | |\n| 4:00 | [End] | | |\n\n","srcMarkdownNoYaml":"\n\n[![](DELPHI-long.png)](https://uofuhealth.utah.edu/delphi-data-science-initiative)\n\n\n::: {.callout-note appearance=\"simple\" icon=false}\n**Date**: October 29 2024\n\n**Time**: 9:00 am -- 4:00 pm MDT\n\n**Location**: HELIX Rm - GS150 - Chokecherry\n\n**Instructors**: Rebecca Barter\n:::\n\n**Registration**: Use the [following link](????) to sign up for this workshop.\n\n[**Sign up for the DELPHI mailing list**](https://www.lists.utah.edu/wws/subscribe/delphi?previous_action=info) to stay in the loop about future workshops and funding opportunities.\n\n## General Information\n\n**What**: This workshop will build upon the foundations covered in the Introduction to R workshop, and will introduce more advanced tools, including creating your own custom functions, iterating with purrr map functions, advanced data manipulations with dplyr, and reshaping and joining datasets in R.\n\n**Who**: The course is aimed at graduate students, postdocs, staff, faculty, and other researchers across campus who are interested in taking their R skills to the next level to learn how to conduct more sophisticated data manipulations and analysis. \n\nParticipants in this workshop should already be comfortable working in Quarto (or R Markdown) documents in RStudio, and have basic knowledge of the the R programming language and the tidyverse, including the dplyr select, filter, mutate, and summarize functions, as well as creating basic visualizations using ggplot2.\n\n**Requirements**: Participants must bring a laptop onto which they can [download R and Rstudio](https://posit.co/download/rstudio-desktop/) (and you should do so before the workshop).\n\n**Contact**: Please email andrew.george@hsc.utah.edu or rebecca.barter@hsc.utah.edu for more information.\n\n## Schedule\n\nNote that the schedule below serves as a guideline. 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Information","containsRefs":false,"markdown":"\n\n[![](DELPHI-long.png)](https://uofuhealth.utah.edu/delphi-data-science-initiative)\n\n\n::: {.callout-note appearance=\"simple\" icon=false}\n**Date**: October 29 2024\n\n**Time**: 9:00 am -- 4:00 pm MDT\n\n**Location**: HELIX Rm - GS150 - Chokecherry\n\n**Instructors**: Rebecca Barter\n:::\n\n**Registration**: Use the [following link](????) to sign up for this workshop.\n\n[**Sign up for the DELPHI mailing list**](https://www.lists.utah.edu/wws/subscribe/delphi?previous_action=info) to stay in the loop about future workshops and funding opportunities.\n\n\n**What**: This workshop will build upon the foundations covered in the Introduction to R workshop, and will introduce more advanced tools, including creating your own custom functions, iterating with purrr map functions, advanced data manipulations with dplyr, and reshaping and joining datasets in R.\n\n**Who**: The course is aimed at graduate students, postdocs, staff, faculty, and other researchers across campus who are interested in taking their R skills to the next level to learn how to conduct more sophisticated data manipulations and analysis. \n\nParticipants in this workshop should already be comfortable working in Quarto (or R Markdown) documents in RStudio, and have basic knowledge of the the R programming language and the tidyverse, including the dplyr select, filter, mutate, and summarize functions, as well as creating basic visualizations using ggplot2.\n\n**Requirements**: Participants must bring a laptop onto which they can [download R and Rstudio](https://posit.co/download/rstudio-desktop/) (and you should do so before the workshop).\n\n**Contact**: Please email andrew.george@hsc.utah.edu or rebecca.barter@hsc.utah.edu for more information.\n\n## Schedule\n\nNote that the schedule below serves as a guideline. The start, end, and break times are fixed, but timing for each topics covered may vary as we may go faster or slower through the content.\n\n\n\n| Time | Topic | \n| ----:|:----|\n| 9:00 | Introduction and Setup | \n| 9:30 | [Writing Functions](content/complete/01_custom_functions_complete.html) | [Writing Functions] | \n| 10:30 | [Break] | \n| 10:45 | [Iteration with Purrr](content/complete/02_iteration_purrr_complete.html) | \n| 12:00 | [Lunch] | \n| 1:00 | [Across()](content/complete/03_across_complete.html) |\n| 1:45 | [Recoding variables](content/complete/04_recoding_variables_complete.html)| \n| 2:30 | [Break] |\n| 2:45 | [Reshaping Data](content/complete/05_pivoting_complete.html) | \n| 3:15 | [Joining Data](content/complete/06_joining_complete.html) | \n| 4:00 | [End] | \n\n","srcMarkdownNoYaml":"\n\n[![](DELPHI-long.png)](https://uofuhealth.utah.edu/delphi-data-science-initiative)\n\n\n::: {.callout-note appearance=\"simple\" icon=false}\n**Date**: October 29 2024\n\n**Time**: 9:00 am -- 4:00 pm MDT\n\n**Location**: HELIX Rm - GS150 - Chokecherry\n\n**Instructors**: Rebecca Barter\n:::\n\n**Registration**: Use the [following link](????) to sign up for this workshop.\n\n[**Sign up for the DELPHI mailing list**](https://www.lists.utah.edu/wws/subscribe/delphi?previous_action=info) to stay in the loop about future workshops and funding opportunities.\n\n## General Information\n\n**What**: This workshop will build upon the foundations covered in the Introduction to R workshop, and will introduce more advanced tools, including creating your own custom functions, iterating with purrr map functions, advanced data manipulations with dplyr, and reshaping and joining datasets in R.\n\n**Who**: The course is aimed at graduate students, postdocs, staff, faculty, and other researchers across campus who are interested in taking their R skills to the next level to learn how to conduct more sophisticated data manipulations and analysis. \n\nParticipants in this workshop should already be comfortable working in Quarto (or R Markdown) documents in RStudio, and have basic knowledge of the the R programming language and the tidyverse, including the dplyr select, filter, mutate, and summarize functions, as well as creating basic visualizations using ggplot2.\n\n**Requirements**: Participants must bring a laptop onto which they can [download R and Rstudio](https://posit.co/download/rstudio-desktop/) (and you should do so before the workshop).\n\n**Contact**: Please email andrew.george@hsc.utah.edu or rebecca.barter@hsc.utah.edu for more information.\n\n## Schedule\n\nNote that the schedule below serves as a guideline. The start, end, and break times are fixed, but timing for each topics covered may vary as we may go faster or slower through the content.\n\n\n\n| Time | Topic | \n| ----:|:----|\n| 9:00 | Introduction and Setup | \n| 9:30 | [Writing Functions](content/complete/01_custom_functions_complete.html) | [Writing Functions] | \n| 10:30 | [Break] | \n| 10:45 | [Iteration with Purrr](content/complete/02_iteration_purrr_complete.html) | \n| 12:00 | [Lunch] | \n| 1:00 | [Across()](content/complete/03_across_complete.html) |\n| 1:45 | [Recoding variables](content/complete/04_recoding_variables_complete.html)| \n| 2:30 | [Break] |\n| 2:45 | [Reshaping Data](content/complete/05_pivoting_complete.html) | \n| 3:15 | [Joining Data](content/complete/06_joining_complete.html) | \n| 4:00 | [End] | 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navigation","crossref-fig-title":"Figure","crossref-tbl-title":"Table","crossref-lst-title":"Listing","crossref-thm-title":"Theorem","crossref-lem-title":"Lemma","crossref-cor-title":"Corollary","crossref-prp-title":"Proposition","crossref-cnj-title":"Conjecture","crossref-def-title":"Definition","crossref-exm-title":"Example","crossref-exr-title":"Exercise","crossref-ch-prefix":"Chapter","crossref-apx-prefix":"Appendix","crossref-sec-prefix":"Section","crossref-eq-prefix":"Equation","crossref-lof-title":"List of Figures","crossref-lot-title":"List of Tables","crossref-lol-title":"List of Listings","environment-proof-title":"Proof","environment-remark-title":"Remark","environment-solution-title":"Solution","listing-page-order-by":"Order By","listing-page-order-by-default":"Default","listing-page-order-by-date-asc":"Oldest","listing-page-order-by-date-desc":"Newest","listing-page-order-by-number-desc":"High to Low","listing-page-order-by-number-asc":"Low to 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} } \ No newline at end of file diff --git a/content/complete/.Rhistory b/content/complete/.Rhistory new file mode 100644 index 0000000..d0a4c8f --- /dev/null +++ b/content/complete/.Rhistory @@ -0,0 +1,512 @@ +# Chunk 4 +cor(cost_report$cost_charge_ratio, cost_report$patient_revenue_per_bed) +# Chunk 5 +cost_charge_ratio_model1 <- lm(cost_charge_ratio ~ patient_revenue_per_bed, +cost_report) +summary(cost_charge_ratio_model1) +# Chunk 6 +tibble(pred = cost_charge_ratio_model1$fitted.values, +obs = cost_report$cost_charge_ratio) |> +ggplot(aes(x = pred, y = obs)) + +geom_point() +# Chunk 7 +tibble(pred = cost_charge_ratio_model1$fitted.values, +obs = cost_report$cost_charge_ratio) |> +cor() +# Chunk 8 +tibble(residual = cost_charge_ratio_model1$residuals, +patient_revenue_per_bed = cost_report$patient_revenue_per_bed) |> +ggplot(aes(x = patient_revenue_per_bed, y = residual)) + +geom_point() +# Chunk 9 +cost_charge_ratio_model2 <- +lm(cost_charge_ratio ~ patient_revenue_per_bed + discharges_per_bed + +employees_per_bed + salary_per_bed + +patient_income_per_bed + patient_charges_per_bed + +hospital_state, +cost_report) +summary(cost_charge_ratio_model2) +# Chunk 10 +tibble(pred = cost_charge_ratio_model2$fitted.values, +obs = cost_report$cost_charge_ratio) |> +ggplot(aes(x = pred, y = obs)) + +geom_point() +# Chunk 11 +tibble(pred = cost_charge_ratio_model2$fitted.values, +obs = cost_report$cost_charge_ratio) |> +cor() +# Chunk 12 +tibble(residual = cost_charge_ratio_model2$residuals, +patient_revenue_per_bed = cost_report$patient_revenue_per_bed) |> +ggplot(aes(x = patient_revenue_per_bed, y = residual)) + +geom_point() +summary(cost_charge_ratio_model2) +round(coef(cost_charge_ratio_model2)["patient_revenue_per_bed"], 3) +cost_charge_ratio_model2$coefficients["patient_revenue_per_bed"] +cost_charge_ratio_model2 <- +lm(cost_charge_ratio ~ patient_revenue_per_bed + discharges_per_bed + +employees_per_bed + salary_per_bed + +patient_income_per_bed + patient_charges_per_bed, +cost_report) +summary(cost_charge_ratio_model2) +cost_report +cost_report |> count(facility_type) +library(tidyverse) +hospital_data <- read_csv("hospital_data/CostReport_2021_Final.csv") +setwd("~/Library/CloudStorage/Box-Box/teaching/headlamp/statistics/assessments/project_prep") +library(tidyverse) +hospital_data <- read_csv("hospital_data/CostReport_2021_Final.csv") +colnames(hospital_data) +hospital_data_clean <- hospital_data |> +select(hospital_name = `Hospital Name`, +hospital_address = `Street Address`, +hospital_city = `City`, +hospital_state = `State Code`, +hospital_zip = `Zip Code`, +hospital_county = `County`, +rural_urban = `Rural Versus Urban`, +facility_type = `CCN Facility Type`, +full_time_employees = `FTE - Employees on Payroll`, +total_salary = `Total Salaries From Worksheet A`, +beds = `Number of Beds`, +discharges = `Total Discharges (V + XVIII + XIX + Unknown)`, +patient_charges = `Combined Outpatient + Inpatient Total Charges`, +patient_revenue = `Total Patient Revenue`, +income_patient_service = `Net Income from Service to Patients`, +cost_charge_ratio = `Cost To Charge Ratio`) |> +filter(!(hospital_state %in% c("AS", "PR", "GU", "VI", "DC")), +cost_charge_ratio < 10, +facility_type == "STH") |> +select(-facility_type) +set.seed(8328) +hospital_data_sample <- hospital_data_clean |> +drop_na(discharges, full_time_employees, beds, total_salary, patient_revenue, patient_charges) |> +sample_n(500) +write_csv(hospital_data_sample, "hospital_cost_report.csv") +summary(lm(cost_charge_ratio ~ rural_urban + +discharges + +full_time_employees + discharges, +hospital_data_sample)) +urban <- hospital_data_sample |> +filter(rural_urban == "R") |> +mutate(discharges_per_bed = discharges / beds) |> +pull(discharges_per_bed) +rural <- hospital_data_sample |> +filter(rural_urban == "U") |> +mutate(discharges_per_bed = discharges / beds) |> +pull(discharges_per_bed) +mean(urban) +mean(rural) +t.test(urban, rural) +urban <- hospital_data_sample |> +filter(rural_urban == "R") |> +mutate(discharges_per_bed = full_time_employees / beds) |> +pull(discharges_per_bed) +rural <- hospital_data_sample |> +filter(rural_urban == "U") |> +mutate(discharges_per_bed = full_time_employees / beds) |> +pull(discharges_per_bed) +mean(urban) +mean(rural, na.rm = T) +t.test(urban, rural) +urban <- hospital_data_sample |> +filter(rural_urban == "R") |> +mutate(discharges_per_bed = patient_charges / patient_revenue) |> +pull(discharges_per_bed) +rural <- hospital_data_sample |> +filter(rural_urban == "U") |> +mutate(discharges_per_bed = patient_charges / patient_revenue) |> +pull(discharges_per_bed) +mean(urban, na.rm = T) +mean(rural, na.rm = T) +t.test(urban, rural) +cost_report <- read_csv("hospital_cost_report.csv") +mean(cost_report$cost_charge_ratio) +cost_report |> +ggplot() + +geom_histogram(aes(x = cost_charge_ratio)) +cost_report |> +ggplot() + +geom_histogram(aes(x = cost_charge_ratio), +col = "white") + +geom_vline(xintercept = 1) +cost_report |> +filter(cost_charge_ratio < 0.1) +cost_report |> +filter(cost_charge_ratio < 0.01) +cost_report |> +filter(cost_charge_ratio < 0.05) +cost_report |> +filter(cost_charge_ratio < 0.05) |> +select(hospital_name, hospital_city, hospital_state) +cost_report |> +filter(cost_charge_ratio == max(cost_charge_ratio)) |> +select(hospital_name, hospital_city, hospital_state) +cost_report |> +filter(cost_charge_ratio == min(cost_charge_ratio)) |> +select(hospital_name, hospital_city, hospital_state) +hospital_Data +hospital_data +sd(hospital_data$`Cost To Charge Ratio`) +sd(hospital_data$`Cost To Charge Ratio`, na.rm = T) +mean(hospital_data$`Cost To Charge Ratio`, na.rm = T) +median(hospital_data$`Cost To Charge Ratio`, na.rm = T) +mean(cost_report$cost_charge_ratio) +sd(hospital_data$`Cost To Charge Ratio`, na.rm = T) +hospital_data_clean <- hospital_data |> +select(hospital_name = `Hospital Name`, +hospital_address = `Street Address`, +hospital_city = `City`, +hospital_state = `State Code`, +hospital_zip = `Zip Code`, +hospital_county = `County`, +rural_urban = `Rural Versus Urban`, +facility_type = `CCN Facility Type`, +full_time_employees = `FTE - Employees on Payroll`, +total_salary = `Total Salaries From Worksheet A`, +beds = `Number of Beds`, +discharges = `Total Discharges (V + XVIII + XIX + Unknown)`, +patient_charges = `Combined Outpatient + Inpatient Total Charges`, +patient_revenue = `Total Patient Revenue`, +income_patient_service = `Net Income from Service to Patients`, +cost_charge_ratio = `Cost To Charge Ratio`) |> +filter(!(hospital_state %in% c("AS", "PR", "GU", "VI", "DC")), +cost_charge_ratio < 10, +facility_type == "STH") |> +select(-facility_type) +mean(hospital_data_clean$cost_charge_ratio) +sd(hospital_data_clean$cost_charge_ratio) +mean(cost_report$cost_charge_ratio) +sd(cost_report$cost_charge_ratio) +simulated_means <- rnorm(1000, 0.26, 0.15 / sqrt(500)) +n <- nrow(cost_report) +pop_mean <- 0.26 +pop_sd <- 0.15 +n <- nrow(cost_report) +simulated_means <- rnorm(1000, pop_mean, pop_sd / sqrt(n)) +ggplot() + +geom_histogram(aes(x = simulated_means)) +simulated_means <- rnorm(1000, mean = pop_mean, sd = pop_sd / sqrt(n)) +ggplot() + +geom_histogram(aes(x = simulated_means)) +# Chunk 1 +# define a function called `add_one()` that adds 1 to its argument, x +add_one <- function(x) { +x + 1 +} +# Chunk 2 +# apply function add_one() to 5 +add_one(5) +# Chunk 3 +# apply function add_one() to 5 using a *named argument* +add_one(x = 5) +# Chunk 4 +# re-define add_one() with two lines of code: x - 1 and x + 1 +add_one <- function(x) { +x - 1 +x + 1 +} +# Chunk 5 +# apply add_one to 5 again +add_one(5) +# Chunk 6 +# redefine add_one() but apply the return statement to x - 1 only +add_one <- function(x) { +return(x - 1) +x + 1 +} +# Chunk 7 +# apply add_one to 5 again +add_one(5) +# Chunk 9 +# define function cube() +cube <- function(value) { +cubed_value = value^3 +return(cubed_value) +} +# apply cube() to 3 +cube(value = 3) +add_xy() +add_xy +add_x2y +# Chunk 1 +# define a function called `add_one()` that adds 1 to its argument, x +add_one <- function(x) { +x + 1 +} +# Chunk 2 +# apply function add_one() to 5 +add_one(5) +# Chunk 3 +# apply function add_one() to 5 using a *named argument* +add_one(x = 5) +# Chunk 4 +# re-define add_one() with two lines of code: x - 1 and x + 1 +add_one <- function(x) { +x - 1 +x + 1 +} +# Chunk 5 +# apply add_one to 5 again +add_one(5) +# Chunk 6 +# redefine add_one() but apply the return statement to x - 1 only +add_one <- function(x) { +return(x - 1) +x + 1 +} +# Chunk 7 +# apply add_one to 5 again +add_one(5) +# Chunk 9 +# define function cube() +cube <- function(value) { +cubed_value = value^3 +return(cubed_value) +} +# Chunk 10 +# apply cube() to 3 +cube(value = 3) +# Chunk 11 +# define a function called add_x2y that computes x + 2y +add_x2y <- function(x, y) { +x + 2*y +} +# Chunk 12 +# apply add_x2y() to x = 2 and y = 5 +add_xy(2, 5) +add_x2y +# Chunk 1 +# define a function called `add_one()` that adds 1 to its argument, x +add_one <- function(x) { +x + 1 +} +# Chunk 2 +# apply function add_one() to 5 +add_one(5) +# Chunk 3 +# apply function add_one() to 5 using a *named argument* +add_one(x = 5) +# Chunk 4 +# re-define add_one() with two lines of code: x - 1 and x + 1 +add_one <- function(x) { +x - 1 +x + 1 +} +# Chunk 5 +# apply add_one to 5 again +add_one(5) +# Chunk 6 +# redefine add_one() but apply the return statement to x - 1 only +add_one <- function(x) { +return(x - 1) +x + 1 +} +# Chunk 7 +# apply add_one to 5 again +add_one(5) +# Chunk 9 +# define function cube() +cube <- function(value) { +cubed_value = value^3 +return(cubed_value) +} +# Chunk 10 +# apply cube() to 3 +cube(value = 3) +# Chunk 11 +# define a function called add_x2y that computes x + 2y +add_x2y <- function(x, y) { +x + 2*y +} +# Chunk 12 +# apply add_x2y() to x = 2 and y = 5 +add_x2y(2, 5) +# Chunk 13 +add_x2y(y = 2, 5) +# Chunk 14 +# run add_x2y() with named arguments x = 2 and y = 5 +add_x2y(x = 2, y = 5) +# Chunk 15 +# run add_x2y() with named arguments y = 5 and x = 2 +add_x2y(y = 5, x = 2) +# Chunk 16 +#| error: true +y +add_x2y <- function(x = 1, y = 1, output_type = c("numeric", "character")) { +# this line will set the default value of output_type to be "numeric" +# and will only allow options provided in the default vector +output_type <- match.arg(output_type) +# stop condition if x or y are not numeric +if (!is.numeric(x) | !is.numeric(y)) { +stop("'x' and 'y' must be numeric") +} +# computing my result +result <- x + 2 * y +# returning result in the format specified by output_type +if (output_type == "numeric") { +return(result) +} else if (output_type == "character") { +return(as.character(result)) +} +} +# apply add_x2y() to x = 2 and y = 3 and output_type = "character" +add_x2y(x = 2, y = 3, output_type = "character") +# apply add_x2y() to x = 2 and y = 3 with no output_type specified +add_x2y(2, 3) +#| error: true +add_x2y(2, 3, output_type = "charcter") +#| error: true +add_x2y(2, 3, output_type = "blah") +# apply add_x2y() to x = 2 and y = 3 and output_type = "logical" +#| error: true +add_x2y(2, 3, output_type = "logical") +?geom_point +# load in the tidyverse and demographics NHANES data +library(tidyverse) +demographics <- read_csv("data/demographics.csv") +setwd("~/Library/CloudStorage/Box-Box/teaching/live_workshops_utah/2024-10-29-adv_r/website/content/complete") +# load in the tidyverse and demographics NHANES data +library(tidyverse) +demographics <- read_csv("data/demographics.csv") +setwd("~/Library/CloudStorage/Box-Box/teaching/live_workshops_utah/2024-10-29-adv_r/website/content/complete") +demographics <- read_csv("data/demographics.csv") +# take a look at the demographics data +head(demographics) +# compute boxplots for the age_years distribution across different levels of the served_active_duty_us variable +demographics |> ggplot() + +geom_boxplot(aes(x = served_active_duty_us, +y = age_years)) +# compute boxplots for the age_years distribution across different levels of the served_active_duty_us variable +demographics |> ggplot() + +geom_boxplot(aes(x = served_active_duty_us, +y = age_years), na.rm = TRUE) +# turn the above boxplot code into a function called createBoxplots() +createBoxplots <- function(variable_name) { +demographics |> ggplot() + +geom_boxplot(aes(x = variable_name, +y = age_years)) +} +# try to apply createBoxplots to the language_english column of demographics +createBoxplots(language_english) +createBoxplots("language_english") +# update our createBoxplots() function so that it uses tidy_evaluation +createBoxplots <- function(variable_name) { +demographics |> ggplot() + +geom_boxplot(aes(x = {{ variable_name }}, +y = age_years)) +} +createBoxplots(language_english) +# apply createBoxplots() to the marital_status column +createBoxplots(marital_status) +View(demographics) +createBoxplots(pregnant) +createBoxplots(marital_status) + +theme(axis.text.x = element_text(angle = 90, +hjust = 1, +vjust = 0.5)) +library(patchwork) +createBoxplots(language_english) + createBoxplots(marital_status) +(createBoxplots(language_english) + createBoxplots(marital_status)) / createBoxplots(pregnant) +(createBoxplots(language_english) + createBoxplots(pregnant)) / createBoxplots(marital_status) +createOrderedBars <- function(variable_name) { +demographics |> +# group by the column provided +group_by({{ variable_name }}) |> +# compute the mean age +summarize(mean_age = mean(age_years)) |> +# create the bar plot +ggplot() + +geom_col(aes(x = {{ variable_name }}, +y = mean_age)) +} +createOrderedBars(marital_status) +demographics |> +# group by the column provided +group_by(marital_status) |> +# compute the mean age +summarize(mean_age = mean(age_years)) +demographics |> +group_by(marital_status) |> +summarize(mean_age = mean(age_years)) |> +ggplot() + +geom_col() +demographics |> +group_by(marital_status) |> +summarize(mean_age = mean(age_years)) |> +ggplot() + +geom_col(aes(x = marital_status, +y = mean_age)) +createOrderedBars <- function(variable_name, ascending = TRUE) { +mean_age <- demographics |> +# group by the column provided +group_by({{ variable_name }}) |> +# compute the mean age +summarize(mean_age = mean(age_years)) +if (ascending) { +mean_age <- mean_age |> +# arrange in increasing order of mean_age +arrange(mean_age) |> +# modify selected_variable so that it is a factor whose levels are in +# increasing order of mean_age +mutate(selected_variable = fct_inorder({{ variable_name }})) +} +# create the bar plot +mean_age |> +ggplot() + +geom_col(aes(x = selected_variable, +y = mean_age)) +} +createOrderedBars(marital_status) +createOrderedBars(marital_status, ascending = TRUE) +createOrderedBars(marital_status, ascending = FALSE) +createOrderedBars <- function(variable_name, ascending = TRUE) { +mean_age <- demographics |> +# group by the column provided +group_by({{ variable_name }}) |> +# compute the mean age +summarize(mean_age = mean(age_years)) +if (ascending) { +mean_age <- mean_age |> +# arrange in increasing order of mean_age +arrange(mean_age) |> +# modify selected_variable so that it is a factor whose levels are in +# increasing order of mean_age +mutate(selected_variable = fct_inorder({{ variable_name }})) +} else { +mean_age <- mean_age |> +mutate(selected_variable = variable_name) +} +# create the bar plot +mean_age |> +ggplot() + +geom_col(aes(x = selected_variable, +y = mean_age)) +} +createOrderedBars(marital_status, ascending = FALSE) +createOrderedBars <- function(variable_name, ascending = TRUE) { +mean_age <- demographics |> +# group by the column provided +group_by({{ variable_name }}) |> +# compute the mean age +summarize(mean_age = mean(age_years)) +if (ascending) { +mean_age <- mean_age |> +# arrange in increasing order of mean_age +arrange(mean_age) |> +# modify selected_variable so that it is a factor whose levels are in +# increasing order of mean_age +mutate(selected_variable = fct_inorder({{ variable_name }})) +} else { +mean_age <- mean_age |> +mutate(selected_variable = {{ variable_name }}) +} +# create the bar plot +mean_age |> +ggplot() + +geom_col(aes(x = selected_variable, +y = mean_age)) +} +createOrderedBars(marital_status, ascending = TRUE) +createOrderedBars(marital_status, ascending = FALSE) +createOrderedBars(marital_status) diff --git a/content/complete/01_custom_functions_complete.qmd b/content/complete/01_custom_functions_complete.qmd new file mode 100644 index 0000000..4fa6f56 --- /dev/null +++ b/content/complete/01_custom_functions_complete.qmd @@ -0,0 +1,767 @@ +--- +title: "Custom functions" +format: html +editor_options: + chunk_output_type: console +--- + +## A simple custom function + +In this notebook, you will learn how to define your own functions. + + +```{r} +# define a function called `add_one()` that adds 1 to its argument, x +add_one <- function(x) { + x + 1 +} +``` + +The code that is run when you "call" your function is inside the curly parentheses. + +```{r} +# apply function add_one() to 5 +add_one(5) +``` + +```{r} +# apply function add_one() to 5 using a *named argument* +add_one(x = 5) +``` + + +What happens when the body of your function contains two pieces of code? + + +```{r} +# re-define add_one() with two lines of code: x - 1 and x + 1 +add_one <- function(x) { + x - 1 + x + 1 +} +``` + +```{r} +# apply add_one to 5 again +add_one(5) +``` + + +By default, any custom R function you create will automatically return the final result that is computed. + + + +For this reason, it is common to explicitly provide a "return statement". + +```{r} +# redefine add_one() but apply the return statement to x - 1 only +add_one <- function(x) { + return(x - 1) + x + 1 +} +``` + +```{r} +# apply add_one to 5 again +add_one(5) +``` + + + + + + + + + +## The general syntax of a custom function + +The general syntax of a custom function is shown below: + +```{r} +#| eval: false + +fn_name <- function(arg) { + # code involving arg + + return(object) +} +``` + + + + +## Exercise + +Write a function called "cube" that returns the cubic (`^3`) of the argument + +```{r} +# define function cube() +cube <- function(value) { + cubed_value = value^3 + return(cubed_value) +} +``` + + +```{r} +# apply cube() to 3 +cube(value = 3) +``` + + + + + + +## Multiple arguments + +To create a function with multiple arguments, you need to provide two arguments inside the function definition, separated by a comma. The function below has two arguments: `x` and `y`: + +```{r} +# define a function called add_x2y that computes x + 2y +add_x2y <- function(x, y) { + x + 2*y +} +``` + +When you call this `add_x2y()`, you can then specify a value for each argument, separated by a comma: + +```{r} +# apply add_x2y() to x = 2 and y = 5 +add_x2y(2, 5) +``` + +When you have multiple arguments, funny things can start to happen when you don't name your arguments. + + + + + +What do you think will happen if you *first* provide a named argument for the *second* argument `y` by specifying `y = 2`, and then provide an unnamed argument afterwards? + +```{r} +add_x2y(y = 2, 5) +``` + + + + + + +R will be clever and it will first apply the named arguments by assigning `y` to the value 2, and then fill in the remaining argument, so `x` will be assigned to the value `5`. + +It is good practice to name your arguments if there is any chance for ambiguity. + +```{r} +# run add_x2y() with named arguments x = 2 and y = 5 +add_x2y(x = 2, y = 5) +``` + + + +Note that when you provide named arguments, it technically doesn't matter which order you provide them in (but this is *not* true when you don't provide named arguments!) + +```{r} +# run add_x2y() with named arguments y = 5 and x = 2 +add_x2y(y = 5, x = 2) +``` + + + + + + + + +Again, note that even when you provide named arguments in a function call (e.g., in `add_x2y(x = 2, y = 5)`), you are *not* defining a global version of the arguments, i.e., there is no `y` defined: + +```{r} +#| error: true + +y +``` + + + + + + + +What do you think will happen when you call `add_x2y` without any parentheses? + +```{r} +# run add_x2y +add_x2y +``` + +It will print out the definition of the function! + + +What do you think will happen when you call `add_x2y` with parentheses but no arguments? + +```{r} +#| error: true +add_x2y() +``` + +You get an error! We can fix this by providing "default" values for the arguments. + + + + + + + + + + + +### Default values + +To provide *default* values for your arguments, you can assign the argument inside the function definition. In the example below, both `x` and `y` are given the default values of 1. + +```{r} +# redefine add_x2y() with default values for x and y (both 1) +add_x2y <- function(x = 1, y = 1) { + x + 2*y +} +``` + + +```{r} +# call add_x2y() without any arguments +add_x2y() +``` + + +What happens if we only provide some of the arguments? + +```{r} +# run add_x2y() with a single unnamed argument, 4 +add_x2y(4) +``` + +```{r} +# run add_x2y() with a single argument: y = 3 +add_x2y(y = 3) +``` + + + + + +### Exercise + + +Without using the `mean()` function, write a function called `my_mean()` that takes four values as its arguments and computes their mean. Ensure that each argument has a default of 0. Use your function to compute the mean of the values 4, 5, 2, 1. + +How would you modify your function to take a single vector of length 4 as its argument instead of four separate arguments? + + +#### Solution + +```{r} +my_mean <- function(a = 0, b = 0, c = 0, d = 0) { + return((a + b + c + d) / 4) +} +``` + +Note that when we run this function it is taking four separate arguments (rather than a vector, as the original mean function does): + +```{r} +my_mean(4, 5, 2, 1) +``` + +You can define a function that instead takes a single vector as its argument: + +```{r} +my_mean_vec <- function(vec) { + return(sum(vec) / length(vec)) +} +``` + +and then to run this function, you provide a vector by wrapping the four values inside `c()`: + +```{r} +my_mean_vec(c(4, 5, 2, 1)) +``` + +What happens if you apply your original `my_mean()` function to this vector? + +```{r} +my_mean(c(4, 5, 2, 1)) +``` + +This is equivalent to assigning the argument `a = c(4, 5, 2, 1)`, and then not providing any values for the `b`, `c`, and `d` arguments (so their default values are used). So the above code is equivalent to: + +```{r} +# (a + b + c + d) / 4 + +(c(4, 5, 2, 1) + 0 + 0 + 0) / 4 +``` + +The fact that we haven't told any of our functions what type of object the arguments should be means that the function will simply take whatever object it is given and try and run the code. + + + + + + + + + + + + + +## If/else statements + +### If statements + + +The following code defines a variable `a`, and then runs some *conditional* code that is only run if the condition `a == 1` is `TRUE`. + +```{r} +# define a variable a containing 5 +a <- 5 +# if a is equal to 1, print out some text +if (a == 1) { + "a is 1" +} + +# Then: +# 1. try the code again, with a equal to 1 +# 2. replace the code that is run in the if statement with a mathematical computation +# 3. replace the code that is run in the if statement with a variable definition (e.g., define y <- 3) + +a <- 1 +# if a is equal to 1, print out some text +if (a == 1) { + y <- 3 +} +``` + + + +Unlike for a function, if you define a variable inside an if statement, then this variable will have been defined in our "global" environment too. + +```{r} +#| eval: false +# Does y exist globally? +y +``` + + + + + +### Else statemenets + +The "else" part of the "if/else" statement provides some code that will be run if the "if" condition is *not* `TRUE`. + +```{r} +# define a variable "a" containing 3 +a <- 3 +# if "a" equals 1, define y <- 3, else define y <- 9 +if (a == 1) { + y <- 3 +} else { + y <- 9 +} +``` + +```{r} +# check what y was assigned to +y +``` + + + + + + +### Using "if" statements to provide custom errors for a function + +The following uses an "if" statement to add a "stop condition" that throws an error when innapropriate arguments are provided + +```{r} +# add an "if" condition to throw an error if `a` is either non-numeric OR the length of `a` is greater than 1 +my_mean <- function(a = 0, b = 0, c = 0, d = 0) { + # write your if statement here containing a stop() function + if (!is.numeric(a) | (length(a) != 1)) { + stop("'a' must be a numeric value of length 1") + } + return((a + b + c + d) / 4) +} +``` + + + + + +### Exercise + +1. Write a standalone if/else statement that checks whether the value in a variable called `age` is at least 18. If the age variable is 18 or older, your statement should return the character value of "You are eligible to vote" and if not, your statement should return "You are not eligible to vote" + +```{r} +age <- 21 +if (age >= 18) { + "You are eligible to vote" +} else { + "You are not eligible to vote" +} +``` + +2. Write a function that computes the area of a circle (`area = pi * radius^2`) with the radius as its argument, and throws an error if a non-numeric or a negative radius value is given. + +```{r} +circle_area <- function(radius) { + if (!is.numeric(radius) | radius < 0) { + stop("'radius' must be a non-negative numeric value") + } + area <- pi * radius^2 + return(area) +} +``` + + +Test your function on the following code + +```{r} +#| error: true + +# the following should throw an error: +circle_area("4") +circle_area(-4) +# the following should NOT throw an error: +circle_area(4) +``` + + + + + + + + + + +## Default argument options with `match.arg()` + +Below, we give an example of providing multiple options to an argument. + +```{r} +# define a function add_x2y with three arguments: +# x: a numeric value with default value 1 +# y: a numeric value with default value 1 +# output_type: a character value with default value "numeric" and alternative option "character" + +# in the body of the function: +# use match.arg() to ensure that output_type is one of the options provided +# use an if statement to modify the output based on the value of output_type + + +add_x2y <- function(x = 1, y = 1, output_type = c("numeric", "character")) { + # this line will set the default value of output_type to be "numeric" + # and will only allow options provided in the default vector + output_type <- match.arg(output_type) + + # stop condition if x or y are not numeric + if (!is.numeric(x) | !is.numeric(y)) { + stop("'x' and 'y' must be numeric") + } + + # computing my result + result <- x + 2 * y + + # returning result in the format specified by output_type + if (output_type == "numeric") { + return(result) + } else if (output_type == "character") { + return(as.character(result)) + } + +} +``` + + +```{r} +# apply add_x2y() to x = 2 and y = 3 and output_type = "character" +add_x2y(x = 2, y = 3, output_type = "character") +``` + +```{r} +# apply add_x2y() to x = 2 and y = 3 with no output_type specified +add_x2y(2, 3) +``` + +```{r} +#| error: true +# apply add_x2y() to x = 2 and y = 3 and output_type = "logical" +add_x2y(2, 3, output_type = "logical") +``` + + + + + + + +### Exercise + +Write a function called `calculate_area()` that will calculate the area of the shape specified in the argument `shape`, which has options "circle", "square", and "triangle". Your function will need to have the following additional arguments: + +- `radius` for computing the area of a circle (`pi * radius^2`), + +- `side` for computing the area of a square (`side^2`), + +- `base` and `height` for computing the area of a triangle (`height * base / 2`). + +Arguments that are not *always* required should have a default value of `NULL`. Your function should throw an error when you fail any value other than "circle", "square" or "triangle" for the `shape` argument (you can use `match.arg()` to do this!). + +Your function should throw an error when: + +1. the 'radius' argument is not provided when `shape == "circle"` + +1. the 'side' argument is not provided when `shape == "square"` + +1. the 'base' and 'height' arguments are not provided when `shape == "triangle"` + + +```{r} +calculate_area <- function(shape = c("circle", "square", "triangle"), + radius = NULL, + side = NULL, + base = NULL, + height = NULL) { + + shape = match.arg(shape) + # error statements + if (shape == "circle" & is.na(radius)) { + stop("'radius' required for 'circle' shape") + } + if (shape == "square" & is.na(side)) { + stop("'side' required for 'square' shape") + } + if (shape == "triangle" & (is.na(base) | is.na(height))) { + stop("'base' and 'height' required for 'triangle' shape") + } + + # compute the area + if (shape == "circle") { + area <- pi * radius^2 + } else if (shape == "square") { + area <- side^2 + } else if (shape == "triangle") { + area <- base * height / 2 + } + + return(area) + +} +``` + + + + + + + + + + + + + +## Tidy evaluation for writing tidyverse-style functions + +Sometimes you want to write a function whose argument is a column of a data frame without quotes (i.e., in the tidyverse style) so that you can use it in a tidyverse function. + + + +```{r} +# load in the tidyverse and demographics NHANES data +library(tidyverse) +demographics <- read_csv("data/demographics.csv") +``` + +```{r} +# take a look at the demographics data +head(demographics) +``` + +Notice that when we refer to the variables from our data frame in the context of the tidyverse (including ggplot2), we do *not* use quotes around the column names: + +```{r} +# compute boxplots for the age_years distribution across different levels of the language_english variable +demographics |> ggplot() + + geom_boxplot(aes(x = language_english, + y = age_years)) +``` + + +Let's try and turn this into a function so we can create boxplots comparing the age distribution across all of the levels of other categorical variables without having to copy-and-paste the code over and over again. + +In this first attempt, we use `variable_name` as the argument: + +```{r} +# turn the above boxplot code into a function called createBoxplots() +createBoxplots <- function(variable_name) { + + demographics |> ggplot() + + geom_boxplot(aes(x = variable_name, + y = age_years)) + +} +``` + + +```{r} +#| error: true + +# try to apply createBoxplots() to the language_english column +createBoxplots(language_english) +createBoxplots("language_english") +``` + + +The issue is that ggplot wants us to refer to the column names without strings, but our custom function doesn't know how to find our column name variable that we provide. + +We can use tidy evaluation (`{{ var_name }}`) to solve this problem. + +```{r} +# update our createBoxplots() function so that it uses tidy_evaluation +createBoxplots <- function(variable_name) { + demographics |> ggplot() + + geom_boxplot(aes(x = {{ variable_name }}, + y = age_years)) +} +``` + +And now it works: + +```{r} +# apply createBoxplots() to the language_english column +createBoxplots(language_english) +``` + + +Let's use our function on a few different columns to make sure: + +```{r} +# apply createBoxplots() to the marital_status column +createBoxplots(marital_status) +# apply createBoxplots() to the pregnant column +createBoxplots(pregnant) +``` + + + + + + +#### Tip: Using patchwork to patch together plots + +The patchwork library can be used to create custom grids of ggplot objects (be sure to expand your plot window if the plots aren't showing up properly): + +```{r} +# load the patchwork library +library(patchwork) +# create a grid of the language_english and marital_status boxplots +createBoxplots(language_english) + createBoxplots(marital_status) +``` + +```{r} +# create a grid of the language_english and pregnant boxplots +# on top with the marital_status boxplots underneath +(createBoxplots(language_english) + createBoxplots(pregnant)) / createBoxplots(marital_status) +``` + + + + +### Exercise + +Create a function called createOrderedBars() that takes a categorical column from `demographics` as its argument and creates a bar chart for the average age for each level of the variable. + +*Hint*: Some example code for computing the average age for each level of the `marital_status` variable and creating a bar chart is shown below: + +```{r} +demographics |> + group_by(marital_status) |> + summarize(mean_age = mean(age_years)) |> + ggplot() + + geom_col(aes(x = marital_status, + y = mean_age)) +``` + + +Challenge activity: Arrange the bars in ascending order, and provide an argument called `ascending` that allows the user to specify whether or not the bars will be arranged in ascending order. + + + +#### Solution + +Note that you'll want to use `geom_col()` instead of `geom_bar()` to create bar charts where the bars have the specific height provided in the y-variable. + +```{r} +createOrderedBars <- function(variable_name) { + demographics |> + # group by the column provided + group_by({{ variable_name }}) |> + # compute the mean age + summarize(mean_age = mean(age_years)) |> + # create the bar plot + ggplot() + + geom_col(aes(x = {{ variable_name }}, + y = mean_age)) +} +``` + +```{r} +createOrderedBars(marital_status) +``` + + + +#### Challenge solution + +To arrange the bars in ascending order of `mean_age`, you first need to convert the categorical variable itself to a factor whose levels are in the order that you want the bars to appear. You can do this by arranging the rows of your data frame in order of `mean_age` and then using `fct_inorder()` to convert your variable to a factor with levels match the increasing order of `mean_age`. + +```{r} +createOrderedBars <- function(variable_name, ascending = TRUE) { + mean_age <- demographics |> + # group by the column provided + group_by({{ variable_name }}) |> + # compute the mean age + summarize(mean_age = mean(age_years)) + + if (ascending) { + mean_age <- mean_age |> + # arrange in increasing order of mean_age + arrange(mean_age) |> + # modify selected_variable so that it is a factor whose levels are in + # increasing order of mean_age + mutate(selected_variable = fct_inorder({{ variable_name }})) + } else { + mean_age <- mean_age |> + mutate(selected_variable = {{ variable_name }}) + } + + # create the bar plot + mean_age |> + ggplot() + + geom_col(aes(x = selected_variable, + y = mean_age)) +} +``` + + + +```{r} +createOrderedBars(marital_status, ascending = TRUE) +createOrderedBars(marital_status, ascending = FALSE) +createOrderedBars(marital_status) +``` + diff --git a/content/complete/02_iteration_purrr_complete.qmd b/content/complete/02_iteration_purrr_complete.qmd new file mode 100644 index 0000000..cde00bb --- /dev/null +++ b/content/complete/02_iteration_purrr_complete.qmd @@ -0,0 +1,347 @@ +--- +title: "Iteration with purrr" +format: html +editor_options: + chunk_output_type: console +--- + +The purpose of this lesson is to learn how to iteratively apply functions to all elements contained within an object, such as all columns in a data frame, or all entries in a vector. + +The "purrr" R package that we will be using in this lesson is *included* in the tidyverse package. + +```{r} +# load the tidyverse and demographics dataset +library(tidyverse) +demographics <- read_csv("data/demographics.csv") +``` + + + + +The function that we want to iterate first is the `n_distinct()` function from the tidyverse. + +Recall that to pull up the help page for a function, you can use the following syntax: + +```{r} +# pull up the help page for n_distinct +?n_distinct +``` + + +`n_distinct()` counts the number of unique values in a vector. + +```{r} +# apply n_distinct to the "gender" column of demographics +n_distinct(demographics$gender) +``` + + +The code below uses the `map()` function to apply `n_distinct()` to every column of the `demographics` data frame simultaneously: + +```{r} +# use map() to apply n_distinct to every column of demographics +map(demographics, n_distinct) +``` + + +The output of the `map()` function is a list (more on that in a moment). + +The following code shows a simpler example, this time applying the `exp()` function to all entries/elements in a simple numeric vector: + +```{r} +# use map() to apply exp() to the vector c(4, 5, 6) +map(c(4, 5, 6), exp) +``` + + + + + +### Lists + +Lists, like vectors, correspond to a collection of values contained in a single object. + +You can use the `list()` function to define a list, for example: + +```{r} +# define a list called my_list with three elements: 1, 4, and 7 +my_list <- list(1, 4, 7) +``` + +You can extract elements from a list just as you would from a vector, using the square bracket notation. The code below extracts the third element from `my_list`: + +```{r} +# extract the third entry from my_list using [] +my_list[3] +# ask the class of the object above +class(my_list[3]) +``` + +However, the output above is a list itself. + + +If you want to extract the actual object/value contained within the third element of the list, then you need to use double square parentheses: + +```{r} +# extract the third entry from my_list using [[]] +my_list[[3]] +``` + + + +Unlike vectors, lists are not vectorized. + +```{r} +#| error: true + +# try to add 1 to my_list +my_list + 1 +``` + +Why would we ever prefer lists to vectors? The reason is that lists are infinitely more flexible than vectors. While all entries in a vector must be a *single value* of the *same type*, entries of a list can be anything. + + +```{r} +# create a list my_complex_list containing +# (1) the head of demographics, +# (2) the value 2, and +# (3) a vector containing "a" and "b" +my_complex_list <- list(head(demographics), 2, c("a", "b")) +my_complex_list +``` + +You can also create a *named* list when defining it as if you are defining argument names: + +```{r} +# create a named version of my_complex_list +my_complex_list <- list(data = head(demographics), + value = 2, + vector = c("a", "b")) +my_complex_list +``` + + + +You can then extract entries from the named list using `$` or `[[]]` + +```{r} +# extract one of the elements from my_complex_list using $ +my_complex_list$data +# extract one of the elements from my_complex_list using [[]] +my_complex_list[["data"]] +``` + + + + + + + +### Exercise + +Use `map()` to apply `class()` to every column in the demographics dataset, and extract the class of the `household_income` column. + +#### Solution + +```{r} +demographics_class <- map(demographics, class) +``` + +```{r} +demographics_class$household_income +demographics_class[[ncol(demographics)]] +demographics_class[["household_income"]] + +``` + + + + + + +## Using custom functions in purrr + + +To iterate using your own custom functions in a purrr `map()` function, you can define your function and provide it in the second argument of `map()`. + +```{r} +# define a function called exp_plus_one() that returns exp(x) + 1 +exp_plus_one <- function(x) { + return(exp(x) + 1) +} + +# apply it to every entry in the vector c(1, 4, 5) +map(c(1, 4, 5), exp_plus_one) +``` + +For simple functions like this, we can define the function inside the `map()` function itself: + +```{r} +# apply the function exp(x) + 1 to every entry in the vector c(1, 4, 5) +# using an "anonymous" function +map(c(1, 4, 5), function(x) exp(x) + 1) +``` + +However, we can go one step further and forego the `function(x)` part entirely using what I call the "tilde-dot" shorthand syntax. + +Here, we use the tilde `~` symbol to "start" an anonymous function and we use a `.` to represent the argument of our anonymous function. + +```{r} +# apply the function exp(x) + 1 to every entry in the vector c(1, 4, 5) +# using the "tilde-dot" syntax +map(c(1, 4, 5), ~{exp(.) + 1}) +``` + + +To decide what should go inside the `~{}`, I typically use a representative value to test out my code first. + +Let's count the number of missing values in each column of demographics. + +For example, below, I take a single column `demographics$pregnant`, and I write out the code that I want to apply to it: + +```{r} +# compute the number of missing values in the "pregnant" column of demographics +sum(is.na(demographics$pregnant)) +``` + +Generalize this code for the map function: + +```{r} +# use a map function to compute the number of missing values in every column +map(demographics, ~{sum(is.na(.))}) +``` + + + + + + + +### Exercise + +Use the tilde-dot short-hand syntax to compute the number of values in each column that is equal to 1. Recall that if a vector has missing values, and you want to use `sum()`, you will want to provide an argument `na.rm = TRUE` to ignore missing values. + +#### Solution + +First, the code below does the long-form version which defines a function and then provides that function in the second argument of the `map()` function: + +```{r} +add_ones <- function(x) { + sum(x == 1, na.rm = TRUE) +} + +map(demographics, add_ones) +``` + +Then I make this more concise by taking the body of my `add_ones()` function above, and placing it inside `~{}`, and replace the `x` argument with a `.`: + +```{r} +map(demographics, ~{sum(. == 1, na.rm = TRUE)}) +``` + + + + + + + + + + +## Alternative map functions for outputting doubles, characters and data frames + +Recall our `map()` function previously that we used to count the number of missing values in each column of the demographics data. + +```{r} +map(demographics, ~sum(is.na(.))) +``` + +A list may not be the most useful format for this information... + + + + + +### Outputting numeric vectors + +The `map_dbl()` function will output a "double" (numeric) vector. + +```{r} +# use map_dbl to count the number of missing values in each column and +# output a numeric vector +map_dbl(demographics, ~sum(is.na(.))) +``` + + + +### Outputting character vectors + +The `map_chr()` function can output a *character* vector. + +```{r} +# use map_chr to apply class to every column and output a character vector +map_chr(demographics, class) +``` + + + + +### Outputting data frames + +One of the most versatile functions is the `map_df()` function, which outputs a data frame. + + +```{r} +# apply map_df to demographics to determine the class of each column, outputting a "wide" data frame +map_df(demographics, class) +``` + +If you want your output to be in a "long" format, the function you are applying must output a single-column tibble/data frame. + +```{r} +# use tibble() to create a single-column tibble containing the class of demographics$pregnant +tibble(col_class = class(demographics$pregnant)) +# modify this code to be the function call in map_df to create a +# long-form data frame +map_df(demographics, ~tibble(col_class = class(.))) +# provide an .id argument to include the original column names as a variable +map_df(demographics, ~tibble(col_class = class(.)), .id = "variable_name") +``` + + + + + + + +### Example + +This long-format is very useful if you want to create a plot, such as a bar chart for the number of missing values. + +```{r} +# create a bar chart of the number of missing values in each column +# use factors to order the columns by the number of missing values +map_df(demographics, + ~tibble(n_missing = sum(is.na(.))), + .id = "variable_name") |> + arrange(n_missing) |> + mutate(variable_name = fct_inorder(variable_name)) |> + ggplot() + + geom_col(aes(x = variable_name, y = n_missing)) + + scale_y_continuous(expand = c(0, 0)) + + theme_classic() + + theme(axis.text.x = element_text(angle = 90, + hjust = 1, + vjust = 0.5)) +``` + +An alternative approach is to use `map_dbl()` and `enframe()` + +```{r} +# use map_dbl() and enframe() to create a long data frame of the +# number of missing values in each column +map_dbl(demographics, ~sum(is.na(.))) |> + enframe() +``` + + diff --git a/content/complete/03_across_complete.qmd b/content/complete/03_across_complete.qmd new file mode 100644 index 0000000..05e6823 --- /dev/null +++ b/content/complete/03_across_complete.qmd @@ -0,0 +1,243 @@ +--- +title: "Across" +format: html +editor_options: + chunk_output_type: console +--- + +In this lesson, we will introduce the `across()` function, which can be used to apply dplyr functions like mutate, summarize, select, etc to subsets of columns that satisfy certain criteria, such as to all numeric columns, or all columns that start with `age_`. + + + +```{r} +# load the tidyverse and demographics dataset +library(tidyverse) +demographics <- read_csv("data/demographics.csv") +head(demographics) +``` + + +Let's suppose that our task is to **convert all character columns of the demographics data to upper-case**. + +```{r} +# apply toupper() to the string value "abc" +toupper("abc") +``` + + +Before introducing across, let's first see one way that we could do this using the `map()` functions that we have just learned: + +```{r} +# create a copy of demographics +demographics_tmp <- demographics +# create a logical vector for identifying character columns using map_chr() +character_cols <- map_chr(demographics_tmp, class) == "character" +# re-assign the character columns to an upper-case version of themselves +# using map_df() applied to demographics_tmp[character_cols] with toupper() +demographics_tmp[character_cols] <- map_df(demographics_tmp[character_cols], toupper) + +# look at demographics_tmp +demographics_tmp +# look at demographics (it should still have lowercase) +demographics +``` + +While this works, it is fairly convoluted, is hard to read, and involves defining an intermediate variable (`character_cols`) -- in the tidyverse style, it is generally recommended to *avoid* defining intermediate variables whenever possible. + + + + + +## Introducing across() + +We could instead do this kind of operation using a `mutate()` operation in conjunction with `across()`. + +Let's figure out the code for just one column first +```{r} +# apply toupper to interview_examination with mutate +demographics |> mutate(interview_examination = toupper(interview_examination)) +``` + +To do this for *all character* columns, you need to provide `across()` to the argument of your mutate function. The `across()` function has two arguments: + +- The first argument is a "select statement" that specifies which columns you want to apply your function to. + +- The second argument is the function name, `toupper`, that we want to apply to all columns that are selected as a result of the first argument. + +The result is that `toupper()` is applied to all columns "where" `is.character()` would result in `TRUE`: + + +```{r} +# use across inside mutate to apply toupper() to all columns +# where(is.character) is TRUE... +demographics |> mutate(across(where(is.character), toupper)) +``` + + + + + + +## More across examples + +### Add 100 to all `age_` columns + +If we were to do this to just the `age_years` column, our code would look like: + +```{r} +# use mutate to add 100 to age_years +demographics |> mutate(age_years = age_years + 100) +``` + +To generalize this to all columns that start with `age_` using `across()`, we can use the `starts_with()` select helper, and apply the anonymous function `~{. + 100}`: + +```{r} +# use across inside mutate to apply ~{. + 100} to all columns +# that starts_with("age_")... +demographics |> mutate(across(starts_with("age_"), ~{. + 100})) +``` + + + + + + + +### Convert `born_usa` and `citizen_usa` to numeric (binary) columns using `ends_with()` + + +```{r} +# take a look at born_usa and citizen_use using select() +demographics |> select(born_usa, citizen_usa) +``` + + +```{r} +# use across inside mutate to apply as.numeric to all columns +# that ends_with("_usa")... +demographics |> mutate(across(ends_with("_usa"), as.numeric)) |> + print(width = Inf) +``` + + + + + + +### Convert `born_usa` and `citizen_usa` to numeric (binary) columns using a vector of column names + +Suppose we had a vector of column names that we wanted to modify using `mutate()`: + +```{r} +# define a vector selected_columns with "born_usa" and "citizen_usa" +selected_cols <- c("born_usa", "citizen_usa") +``` + +Then we could use `all_of(selected_cols)` in `across()` to apply the function to all columns listed in the `selected_cols` vector as follows: + +```{r} +# use across inside mutate to apply as.numeric to all_of(selected_columns) +demographics |> mutate(across(all_of(selected_cols), as.numeric)) |> + print(width = Inf) +``` + + + + + + + +## Select helpers summary + +So far we have seen the following "select helpers" that can be used to specify the columns inside `across()`: + +- `where()` -- across to all columns that satisfy a logical condition (`across(where(is.character), fun)`) + +- `starts_with()` and `ends_with()` -- across all columns that start or ends with a specified string (`across(starts_with("abc"), fun)`) + +- `contains()` -- across all columns that contain a specified string (`across(contains("abc"), fun)`) + +- `all_of()` and `any_of()` -- across all columns whose names are contained in a character vector, where `all_of()` requires all columns in the vector be present. (`across(all_of(vec_names), fun)`) + +- `everything()` -- across all columns + +These can also be used within `select()` + + +```{r} +# select all columns that contain "age" +demographics |> select(contains("age")) +# select all columns that start with "age" +demographics |> select(starts_with("age")) +# select all columns that have a logical type +demographics |> select(where(is.logical)) +``` + + + + + + + + +### Exercise + +a. For all columns that contain the word "education" (`education_youth` and `education`), add the number 5 to each value + +b. For all numeric columns, standardize the values by subtracting the mean and dividing by the standard deviation + +c. Compute the average age across all columns that start with `age_` (Hint: use `across()` within `summarize()`) + +d. Compute the total number of `TRUE` values in the `born_usa`, `citizen_usa`, and `language_english` columns (Hint: use `across()` within `summarize()`) + + +#### Solution + +a. + +```{r} +demographics |> mutate( + across( + contains("education"), + ~{. + 5} + ) +) |> + print(width = Inf) +``` + +b. + +```{r} +# standardize all numeric columns +demographics |> mutate( + across( + where(is.numeric), + ~{(. - mean(., na.rm = TRUE)) / sd(., na.rm = TRUE)} + ) +) +``` + +c. + +```{r} +# compute average age across all age columns +demographics |> summarize( + across( + starts_with("age"), + ~mean(., na.rm = TRUE) + ) +) +``` + +d. + +```{r} +# compute the total in the `born_usa`, `citizen_usa`, and `language_english` +demographics |> summarise( + across( + any_of(c("born_usa", "citizen_usa", "language_english")), + ~sum(., na.rm = TRUE) + ) +) +``` + diff --git a/content/complete/04_recoding_variables_complete.qmd b/content/complete/04_recoding_variables_complete.qmd new file mode 100644 index 0000000..36158fe --- /dev/null +++ b/content/complete/04_recoding_variables_complete.qmd @@ -0,0 +1,154 @@ +--- +title: "Recoding variables using if_else and case_when" +format: html +editor_options: + chunk_output_type: console +--- + +```{r} +# load the tidyverse and demographics dataset +library(tidyverse) +demographics <- read_csv("data/demographics.csv") +head(demographics) +``` + + +In this document, you will learn how to "recode" variables by replacing values in a variable with other values of your choice, e.g., converting numerically-encoded variables to categorical/character versions, and vice versa. + +We will introduce two functions for doing this: + +- `if_else()` which can be used to create binary variables (variables with just two distinct values) based on a logical "condition" + +- `case_when()` which can be used to create variables with many different values. + + + + + + +## if_else + + + +```{r} +# apply count() to interview_examination +demographics |> count(interview_examination) +``` + +Let's convert it to a numeric format using `if_else()`. + +```{r} +# use mutate() to create a new column called interview_examination_numeric +# which is 2 if interview_examination is "both interview and exam" +# and 1 otherwise +# then select just interview_examination and interview_examination_numeric +demographics |> + mutate(interview_examination_numeric = if_else( + interview_examination == "both interview and exam", + true = 2, + false = 1) + ) |> + select(interview_examination, interview_examination_numeric) +``` + + + + + + +### Exercise + +Use `if_else()` to create a variable called `completed_high_school`, which has the values `"yes"` if `education` is equal to at least 3, and `"no"` otherwise. + +A link to the documentation for the demographics data can be found [here](https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/P_DEMO.htm#DMDEDUC2). + + +#### Solution + +Our condition is `education >= 3` and we want to replace all values for which this condition is true with `"yes"`, and all other values with `"no"`: + +```{r} +demographics |> + mutate(completed_high_school = if_else( + education >= 3, + true = "yes", + false = "no")) |> + select(education, completed_high_school) |> + sample_n(10) +``` + + + + + + + + +## case_when + +The `case_when()` function is similar to `if_else()`, but it allows you to have an unlimited number of conditions and corresponding recoded values. + +In this section we will work with the `marital_status` column of the demographics data: + +```{r} +# apply count() to the marital_status column +demographics |> count(marital_status) +``` + +Let's create a new variable based on `marital_status` that replaces + +- `"married"` with `3` + +- `"living_with_partner"` with `2` + +- `"divorced"`, `"widowed"`, `"never_married"`, and `"separated"` with `1` + +```{r} +# use mutate and case_when() to create marital_status_numeric +# with the values above +demographics |> mutate(marital_status_numeric = case_when( + marital_status == "married" ~ 3, + marital_status == "living_with_partner" ~ 2, + marital_status %in% c("divorced", "widowed", "never_married", "separated") ~ 1)) |> + select(marital_status, marital_status_numeric) +``` + + + + + + + + +## Execise + +Use `case_when()` to convert `born_usa` and `citizen_usa` to "yes" and "no". Bonus points: use `across()`. + + +### Solution + +To do this without `across()`, you can write: + +```{r} +demographics |> mutate(born_usa_chr = case_when(born_usa ~ "yes", + !born_usa ~ "no"), + citizen_usa_chr = case_when(citizen_usa ~ "yes", + !citizen_usa ~ "no")) |> + select(born_usa, born_usa_chr, citizen_usa, citizen_usa_chr) |> + sample_n(10) +``` + +Note that `born_usa ~ "yes"` is equivalent to `born_usa == TRUE ~ "yes"`, but the `== TRUE` is redundant because `born_usa` is itself a logical variable. Similarly, `!citizen_usa ~ "no"` is equivalent to `citizen_usa == FALSE ~ "no"`. + +To use `across()`, the relevant select helper is something like `ends_with("_usa")` or `contains("usa")`, and you provide a `~` before `case_when()` to start an anonymous function, and you need to replace the column name with `.` (again, you don't need the `== TRUE` for this particular example in the condition, but that's just because the columns we're applying the `case_when()` function to are logical). + +```{r} +demographics |> mutate(across(ends_with("_usa"), + ~case_when(. == TRUE ~ "yes", + . == FALSE ~ "no"), + .names = "{.col}_chr")) |> + select(contains("_usa")) |> + sample_n(10) +``` + + diff --git a/content/complete/05_pivoting_complete.qmd b/content/complete/05_pivoting_complete.qmd new file mode 100644 index 0000000..e700ec3 --- /dev/null +++ b/content/complete/05_pivoting_complete.qmd @@ -0,0 +1,95 @@ +--- +title: "Reshaping (Pivoting) Data" +format: html +editor_options: + chunk_output_type: console +--- + +In this lesson, we will be working with a new NHANES table that contains urine albumin and creatinine *lab* data. + +```{r} +# load the tidyverse and the urine_albumin_creatinine NHANES data +library(tidyverse) +labs_data <- read.csv("data/urine_albumin_creatinine.csv") +``` + +```{r} +# take a look at the first 10 rows +head(labs_data, 10) +``` + +This data is in a **long format**--there are multiple rows for each observational unit, each corresponding to a different variable being measured (in this case, the different labs). + + +A **wide format**, on the other hand, will only have *one* row for each observational unit (respondent), and each of the individual variables being measured (the labs) will have their own column, each containing the *values* for the corresponding lab. + +You can convert from a long format to a wide format using the `pivor_wider()` function. + +The code below creates a wide-form version of the labs data, and saves it as a new data frame called `labs_data_wide`: + +```{r} +# use pivot_wider() to convert the labs data from a +# long format to a wide format. +# arguments are `names_from` and `values_from` +# save the wide data as `labs_data_wide`. +labs_data_wide <- labs_data |> + pivot_wider(names_from = "lab", values_from = "measurement") +labs_data_wide +``` + +If you want to convert from a wide format dataset into a longer-format dataset, you can instead use the `pivot_longer()` function. + + +```{r} +# use pivot_longer() to convert labs_data_wide back to along format +# arguments are `cols` (use a select helper!), `names_to` and `values_to` +labs_data_wide |> + pivot_longer(cols = starts_with("ur_"), + names_to = "lab", + values_to = "measurement") +``` + + +Use-case for long-format: creating a visualization that compares the different variables using ggplot2. + +```{r} +# create boxplots using the long format for the measurements from each lab +# maybe add a log-scale to the y-axis +labs_data |> ggplot() + + geom_boxplot(aes(x = lab, y = measurement)) + + scale_y_log10() +``` + + +### Exercise + +Load the demographics data and use `select()` to select just the `respondent_id`, `gender`, `marital_status` and `race` columns and then use `pivot_longer()` to create the following long-format table (below are just the first 10 rows). + + respondent_id name value + + 1 73557 gender male + 2 73557 marital_status separated + 3 73557 race black + 4 73558 gender male + 5 73558 marital_status married + 6 73558 race white + 7 73559 gender male + 8 73559 marital_status married + 9 73559 race white +10 73560 gender male + +#### Solution + +```{r} +demographics <- read_csv("data/demographics.csv") +demographics +``` + +```{r} +demographics |> + select(respondent_id, gender, marital_status, race) |> + pivot_longer(cols = all_of(c("gender", "marital_status", "race"))) +``` + + + diff --git a/content/complete/06_joining_complete.qmd b/content/complete/06_joining_complete.qmd new file mode 100644 index 0000000..89452ad --- /dev/null +++ b/content/complete/06_joining_complete.qmd @@ -0,0 +1,185 @@ +--- +title: "Joining Data Together" +format: html +editor_options: + chunk_output_type: console +--- + +This lesson introduces techniques for "joining" multiple data tables together using a "key" variable + +A really helpful resource for learning about joins is the [R for Data Science](https://r4ds.had.co.nz/index.html) book (specifically the chapter about ["Relational Data"](https://r4ds.had.co.nz/relational-data.html)). + +At the end of this lesson we will have created a *single* data frame that contains the information from both the `demographics` data and the urine albumin and creatinine `labs` data. + +```{r} +# load the tidyverse, the demographics, and the urine_albumin_creatinine data +library(tidyverse) +demographics <- read_csv("data/demographics.csv") +labs <- read_csv("data/urine_albumin_creatinine.csv") +``` + +## Determining what kind of join to do + +There are four kinds of joins that you might want to use for combining two tables into a single table: + +![Diagram of joins](figures/joins.png) + +- An **inner join**, which will keep only the data for the observational units that appear in both tables + +- A **left join**, which will keep all of the data for the observational units in the first (left) table, and will add missing values when there is no available data in the second table. + +- A **right join**, which will keep all of the data for the observational units in the second (right) table, and will add missing values when there is no available data in the first table. + +- A **full join**, which will keep all of the data for the observational units in both the first (left) table, and will add missing values when there is no available data in the other table. + +The kind of join that you will implement will depend on what you want to use your joined data for. + + + +### Checking the uniqueness of the key ID variables + +Below, we see that the `respondent_id` column is indeed unique for `demographics`: + +```{r} +# check whether the respondent ID values in demographics are unique? +identical(unique(demographics$respondent_id), demographics$respondent_id) +``` + +But not for `labs`: + +```{r} +# check whether the respondent ID values in labs are unique? +identical(unique(labs$respondent_id), labs$respondent_id) +``` + + + + + + + +### Checking overlap between tables + + +*Are there any observations in the demographics table that do not appear in the labs table?* + +```{r} +# Compute the proportion of people in demographics who are also in labs +sum(unique(demographics$respondent_id) %in% unique(labs$respondent_id)) / n_distinct(demographics$respondent_id) +``` + +The calculation above shows that around 81% of observations in the demographics table have available labs data. + + + + + +*Are there any observations in the labs table that do not appear in the demographics table?* + +```{r} +# proportion of people in labs who are also in demographics +sum(unique(labs$respondent_id) %in% unique(demographics$respondent_id)) / n_distinct(labs$respondent_id) +``` + +The calculation above shows that 100% of observations in the labs table have available demographics data. + + + + + + + + + + +## Joining demographics and labs + +Our two options for to join demographics (left) and labs (right) are: + +- An inner or right join will only keep the 81% of people in demographics who have available labs data + +- A left or full join will keep all people in demographics data, and join missing values for those who don't have labs data available + +Since we don't want to discard any data, we will choose the left/full join. + + +```{r} +# perform a left/full join of demographics and labs +print(left_join(demographics, labs, by = "respondent_id"), width = Inf) +print(full_join(demographics, labs, by = "respondent_id"), width = Inf) +``` + +Look at the results above, does something look wrong to you? + + + + + + + + + + + + + +**If your key ID variable has repeated values, your joined data will too**. + +A good check after completing a join is to make sure that the number of rows in the resulting joined data matches what you expect + + +```{r} +# check the number of rows in the joined data +nrow(left_join(demographics, labs, by = "respondent_id")) +# check the number of rows in demographics +nrow(demographics) +``` + + + + + + + +Therefore, to ensure that we have just one row per observational unit (i.e., per `respondent_id` value), we need to join the wide-format `labs_wide` data instead of the long-format `labs` data. + +```{r} +# compute the wide format of the labs data +labs_wide <- labs |> + pivot_wider(names_from = "lab", + values_from = "measurement") +labs_wide +``` + + +```{r} +# join demographics and labs_wide +print(left_join(demographics, labs_wide, by = "respondent_id"), width = Inf) +``` + + + + + + +## Exercise + +How many rows would you expect an *inner join* of `demographics` and `labs_wide` to have? Check your answer by conducting the join using `inner_join()` + +### Solution + +The number of rows should match the *intersection* of the two datasets. Since all people in `labs_wide` are also in `demographics` (but not the other way around), the join will have the same number of rows in `labs_wide`. + +```{r} +nrow(labs_wide) +``` + +The join can be conducted using `inner_join()` and notice that the number of rows matches `labs_wide`. + +```{r} +inner_join(demographics, labs_wide, by = "respondent_id") +``` + +Note that if there were observations in `labs_wide` that were not in `demographics`, then the resulting inner join will have fewer rows than both tables. + + diff --git a/content/complete/data/demographics.csv b/content/complete/data/demographics.csv new file mode 100644 index 0000000..bef67f3 --- /dev/null +++ b/content/complete/data/demographics.csv @@ -0,0 +1,10176 @@ 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interview and exam,female,8,NA,white,1,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +73697,both interview and exam,female,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +73698,both interview and exam,male,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,60000 +73699,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,NA +73700,both interview and exam,male,0,10,mexican american,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +73701,both interview and exam,male,47,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +73702,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,60000 +73703,both interview and exam,female,38,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,2,married,no,FALSE,NA +73704,both interview and exam,female,8,NA,white,2,104,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +73705,both interview and 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exam,male,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +73725,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +73726,both interview and exam,female,67,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,50000 +73727,both interview and exam,female,3,NA,black,1,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +73728,both interview and exam,male,16,NA,white,2,196,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +73729,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +73730,both interview and exam,male,48,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +73731,both interview and exam,male,12,NA,other,1,154,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +73732,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,3,married,NA,TRUE,50000 +73733,both interview and exam,female,23,NA,mexican 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exam,female,8,NA,white,2,107,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +73753,both interview and exam,female,11,NA,white,1,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +73754,both interview and exam,male,15,NA,mexican american,2,190,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,17500 +73755,both interview and exam,male,75,NA,mexican american,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,40000 +73756,both interview and exam,male,56,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +73757,both interview and exam,female,29,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,87500 +73758,both interview and exam,female,15,NA,white,2,188,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +73759,both interview and exam,female,9,NA,mexican american,2,117,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +73760,both interview and exam,male,64,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +73761,both interview and exam,male,17,NA,mexican 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exam,male,78,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +73781,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +73782,both interview and exam,male,68,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +73783,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +73784,interview only,female,7,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +73785,both interview and exam,male,46,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +73786,both interview and exam,female,18,NA,white,2,217,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +73787,both interview and exam,male,71,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,60000 +73788,both interview and exam,female,9,NA,other hispanic,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +73789,both interview and exam,female,2,NA,black,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +73790,both interview and exam,male,59,NA,white,2,NA,TRUE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +73791,interview only,male,8,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +73792,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +73793,both interview and exam,male,10,NA,mexican american,2,131,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +73794,both interview and exam,female,6,NA,other hispanic,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +73795,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +73796,both interview and exam,female,5,NA,mexican american,1,72,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +73797,both interview and exam,female,57,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +73798,both interview and exam,male,11,NA,other 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and exam,female,14,NA,mexican american,1,179,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,17500 +73827,both interview and exam,female,11,NA,mexican american,2,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +73828,both interview and exam,female,4,NA,black,2,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +73829,both interview and exam,female,7,NA,asian,2,91,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +73830,interview only,male,64,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,100000 +73831,both interview and exam,female,48,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +73832,interview only,male,77,NA,black,NA,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +73833,both interview and exam,female,34,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,unable to ascertain,TRUE,100000 +73834,both interview and exam,male,64,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,never_married,NA,TRUE,NA +73835,both interview and exam,male,13,NA,mexican american,1,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +73836,both interview and exam,female,9,NA,white,2,112,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +73837,both interview and exam,male,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +73838,both interview and exam,female,2,NA,black,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +73839,both interview and exam,male,68,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +73840,both interview and exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,22500 +73841,both interview and exam,male,13,NA,mexican american,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,22500 +73842,both interview and exam,male,53,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,12500 +73843,both interview and exam,male,42,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,40000 +73844,both interview and exam,female,12,NA,white,1,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +73845,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +73846,both interview and exam,female,24,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +73847,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,40000 +73848,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,12500 +73849,both interview and exam,female,16,NA,white,2,200,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +73850,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +73851,both interview and exam,female,48,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +73852,both interview and exam,female,40,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,no,FALSE,50000 +73853,both interview and exam,male,13,NA,white,2,165,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +73854,both interview and exam,female,1,23,mexican american,1,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +73855,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,7500 +73856,both interview and exam,male,0,10,other hispanic,1,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +73857,interview only,male,23,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,FALSE,40000 +73858,both interview and exam,male,52,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +73859,both interview and exam,male,38,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +73860,both interview and exam,male,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,30000 +73861,both interview and exam,male,77,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +73862,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +73863,both interview and exam,male,26,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,never_married,NA,TRUE,50000 +73864,both interview and exam,female,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +73865,both interview and exam,male,48,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +73866,both interview and exam,female,47,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +73867,interview only,female,80,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +73868,both interview and exam,male,32,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +73869,both interview and exam,male,7,NA,black,1,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +73870,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +73871,interview only,female,28,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,unable to ascertain,TRUE,60000 +73872,both interview and exam,female,63,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,married,NA,TRUE,NA +73873,both interview and exam,male,80,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +73874,both interview and exam,female,2,NA,white,1,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +73875,both interview and exam,male,43,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,TRUE,50000 +73876,both interview and exam,female,0,5,white,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +73877,both interview and exam,female,0,6,black,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +73878,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,40000 +73879,both interview and exam,female,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +73880,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,70000 +73881,both interview and exam,male,38,NA,other hispanic,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +73882,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,12500 +73883,both interview and exam,male,67,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,1,married,NA,FALSE,7500 +73884,both interview and exam,male,43,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +73885,both interview and exam,male,6,NA,white,2,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +73886,both interview and exam,female,64,NA,other hispanic,1,NA,FALSE,NA,NA,NA,NA,NA,5,NA,NA,TRUE,100000 +73887,both interview and exam,male,16,NA,white,1,194,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +73888,both interview and exam,male,56,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +73889,both interview and exam,male,15,NA,other hispanic,1,184,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,17500 +73890,both interview and exam,male,16,NA,black,2,196,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,7500 +73891,both interview and exam,male,12,NA,black,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,60000 +73892,both interview and exam,male,15,NA,asian,2,183,NA,NA,FALSE,TRUE,12.5,8,NA,NA,NA,TRUE,100000 +73893,both interview and exam,male,17,NA,black,2,210,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,NA +73894,both interview and exam,male,6,NA,black,1,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +73895,both interview and exam,male,5,NA,mexican american,1,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +73896,both interview and exam,female,19,NA,mexican american,1,232,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +73897,both interview and exam,female,11,NA,black,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +73898,both interview and exam,male,9,NA,white,2,111,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +73899,both interview and exam,male,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +73900,both interview and exam,male,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 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exam,male,51,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +73911,both interview and exam,male,3,NA,white,2,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +73912,both interview and exam,male,0,2,other hispanic,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +73913,both interview and exam,male,26,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +73914,both interview and exam,female,52,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +73915,both interview and exam,female,14,NA,white,2,178,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +73916,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +73917,both interview and exam,male,8,NA,white,2,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +73918,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +73919,both interview and exam,male,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,2500 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exam,female,3,NA,mexican american,1,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +73930,both interview and exam,female,70,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +73931,both interview and exam,female,37,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,no,FALSE,22500 +73932,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +73933,both interview and exam,female,10,NA,other,2,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,17500 +73934,both interview and exam,male,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +73935,both interview and exam,male,63,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +73936,both interview and exam,female,3,NA,white,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +73937,both interview and exam,female,41,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,no,FALSE,22500 +73938,both interview and exam,female,53,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +73939,both interview and exam,female,6,NA,other,1,80,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,2500 +73940,both interview and exam,male,7,NA,mexican american,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,NA +73941,both interview and exam,male,28,NA,black,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,living_with_partner,NA,TRUE,50000 +73942,both interview and exam,male,5,NA,black,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +73943,both interview and exam,male,19,NA,other hispanic,1,232,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,60000 +73944,both interview and exam,male,0,9,black,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +73945,both interview and exam,male,66,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +73946,both interview and exam,male,2,NA,mexican american,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +73947,both interview and exam,male,1,22,mexican american,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 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exam,female,26,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,no,TRUE,100000 +73958,both interview and exam,female,16,NA,black,2,198,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,60000 +73959,both interview and exam,male,5,NA,black,1,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +73960,both interview and exam,female,11,NA,white,2,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +73961,both interview and exam,male,7,NA,black,1,95,NA,NA,FALSE,FALSE,3,0,NA,NA,NA,TRUE,30000 +73962,both interview and exam,male,49,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +73963,both interview and exam,male,16,NA,asian,1,204,NA,NA,FALSE,TRUE,12.5,10,NA,NA,NA,TRUE,87500 +73964,both interview and exam,male,45,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +73965,both interview and exam,male,0,1,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +73966,both interview and exam,male,7,NA,mexican american,1,85,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,22500 +73967,both interview and exam,male,9,NA,asian,1,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +73968,both interview and exam,male,15,NA,black,1,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +73969,both interview and exam,male,0,9,white,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +73970,both interview and exam,male,10,NA,other hispanic,2,125,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +73971,both interview and exam,female,15,NA,black,2,190,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +73972,both interview and exam,female,2,NA,mexican american,2,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +73973,both interview and exam,female,75,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,widowed,NA,TRUE,50000 +73974,both interview and exam,male,34,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +73975,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +73976,both interview and exam,female,11,NA,other,1,137,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +73977,both interview and exam,male,30,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +73978,both interview and exam,female,10,NA,asian,2,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +73979,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +73980,both interview and exam,male,43,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,NA +73981,both interview and exam,female,36,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,3,never_married,no,TRUE,40000 +73982,both interview and exam,male,13,NA,black,2,162,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,7500 +73983,both interview and exam,female,18,NA,black,1,221,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 +73984,both interview and exam,male,5,NA,white,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +73985,both interview and exam,female,43,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,no,TRUE,60000 +73986,both interview and exam,female,7,NA,black,1,87,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +73987,both interview and exam,male,56,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +73988,both interview and exam,male,4,NA,white,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +73989,both interview and exam,male,0,7,white,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +73990,both interview and exam,female,50,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +73991,both interview and exam,female,8,NA,mexican american,2,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,17500 +73992,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +73993,both interview and exam,male,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +73994,both interview and exam,male,36,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +73995,both interview and exam,female,40,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,widowed,no,TRUE,60000 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exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +74006,both interview and exam,female,34,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,no,TRUE,30000 +74007,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +74008,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +74009,both interview and exam,female,6,NA,white,2,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74010,both interview and exam,male,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +74011,both interview and exam,male,55,NA,black,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +74012,both interview and exam,female,68,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,widowed,NA,FALSE,40000 +74013,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +74014,both interview and exam,male,60,NA,mexican 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exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,70000 +74034,both interview and exam,female,0,6,mexican american,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74035,both interview and exam,female,3,NA,black,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74036,both interview and exam,male,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +74037,both interview and exam,male,20,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,never_married,NA,TRUE,22500 +74038,both interview and exam,female,54,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,2500 +74039,both interview and exam,female,10,NA,black,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +74040,both interview and exam,male,4,NA,other hispanic,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +74041,both interview and exam,male,60,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,NA +74042,both interview and exam,female,41,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,unable to ascertain,TRUE,22500 +74043,both interview and exam,female,14,NA,mexican american,2,177,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,7500 +74044,both interview and exam,male,73,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +74045,both interview and exam,male,38,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,never_married,NA,FALSE,50000 +74046,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,unable to ascertain,TRUE,100000 +74047,both interview and exam,female,40,NA,mexican american,1,NA,FALSE,NA,FALSE,NA,NA,NA,2,living_with_partner,no,FALSE,22500 +74048,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +74049,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,NA,TRUE,40000 +74050,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +74051,both interview and exam,female,20,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +74052,both interview and exam,female,19,NA,black,2,239,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 +74053,both interview and exam,female,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +74054,both interview and exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,70000 +74055,both interview and exam,male,57,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,50000 +74056,both interview and exam,male,38,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,22500 +74057,both interview and exam,female,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +74058,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,30000 +74059,both interview and exam,male,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74060,both interview and exam,female,8,NA,white,2,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +74061,both interview and exam,female,12,NA,black,1,148,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +74062,both interview and exam,female,67,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,45,NA,2,never_married,NA,TRUE,17500 +74063,interview only,male,49,NA,asian,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,100000 +74064,both interview and exam,male,17,NA,asian,2,207,FALSE,NA,FALSE,FALSE,3,9,NA,NA,NA,TRUE,17500 +74065,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,50000 +74066,both interview and exam,male,56,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,FALSE,17500 +74067,both interview and exam,female,2,NA,white,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74068,both interview and exam,female,5,NA,white,2,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74069,both interview and exam,female,0,11,white,1,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74070,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74071,both interview and exam,female,3,NA,white,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74072,both interview and exam,male,63,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,17500 +74073,both interview and exam,male,0,8,black,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74074,both interview and exam,female,4,NA,mexican american,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74075,both interview and exam,male,59,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +74076,both interview and exam,female,4,NA,mexican american,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74077,both interview and exam,male,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,60000 +74078,both interview and exam,male,63,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +74079,both interview and exam,female,2,NA,mexican american,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +74080,both interview and exam,female,5,NA,white,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74081,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +74082,both interview and exam,male,4,NA,other,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74083,both interview and exam,female,67,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +74084,both interview and exam,male,1,15,other,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74085,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +74086,both interview and exam,male,6,NA,black,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74087,both interview and exam,female,59,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,100000 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exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +74098,both interview and exam,male,0,4,mexican american,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74099,both interview and exam,male,44,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,FALSE,22500 +74100,both interview and exam,male,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,17500 +74101,both interview and exam,female,34,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +74102,both interview and exam,female,18,NA,black,2,217,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,40000 +74103,both interview and exam,female,17,NA,other hispanic,1,211,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,22500 +74104,both interview and exam,female,8,NA,other,1,102,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +74105,both interview and exam,female,0,1,black,2,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74106,both interview and exam,female,10,NA,black,2,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +74107,both interview and exam,male,4,NA,white,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74108,both interview and exam,female,1,19,black,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74109,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,FALSE,FALSE,35,NA,3,divorced,NA,TRUE,40000 +74110,both interview and exam,male,60,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,30000 +74111,both interview and exam,female,61,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,widowed,NA,TRUE,100000 +74112,both interview and exam,female,28,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,17500 +74113,both interview and exam,male,17,NA,white,1,212,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +74114,both interview and exam,female,9,NA,black,1,112,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +74115,both interview and exam,male,27,NA,mexican 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exam,female,28,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,separated,no,TRUE,22500 +74125,both interview and exam,female,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,NA +74126,both interview and exam,female,53,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +74127,both interview and exam,female,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +74128,both interview and exam,female,71,NA,black,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,married,NA,TRUE,40000 +74129,both interview and exam,male,56,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,NA,TRUE,50000 +74130,both interview and exam,male,12,NA,black,1,149,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +74131,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,70000 +74132,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,70000 +74133,both interview and exam,female,14,NA,mexican american,2,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,30000 +74134,both interview and exam,female,51,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,NA,TRUE,60000 +74135,both interview and exam,female,6,NA,white,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74136,both interview and exam,male,9,NA,asian,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +74137,both interview and exam,male,17,NA,mexican american,1,212,FALSE,NA,FALSE,FALSE,12.5,12,NA,NA,NA,FALSE,50000 +74138,both interview and exam,male,69,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,FALSE,30000 +74139,both interview and exam,female,63,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,2500 +74140,both interview and exam,female,8,NA,mexican american,1,100,NA,NA,FALSE,FALSE,7.5,2,NA,NA,NA,FALSE,12500 +74141,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,60000 +74142,both interview and exam,male,61,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +74143,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74144,both interview and exam,male,51,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,87500 +74145,both interview and exam,male,6,NA,black,2,79,NA,NA,FALSE,FALSE,7.5,0,NA,NA,NA,TRUE,40000 +74146,both interview and exam,male,50,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,TRUE,7500 +74147,both interview and exam,female,79,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +74148,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,22500 +74149,both interview and exam,female,54,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +74150,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,87500 +74151,interview 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exam,male,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +74347,both interview and exam,male,13,NA,other,2,166,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +74348,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +74349,both interview and exam,female,57,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,100000 +74350,both interview and exam,male,52,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +74351,both interview and exam,female,7,NA,black,1,87,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,50000 +74352,both interview and exam,male,65,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,100000 +74353,interview only,female,20,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,unable to ascertain,TRUE,17500 +74354,both interview and exam,female,0,2,mexican american,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74355,both interview and 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exam,male,26,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,never_married,NA,TRUE,30000 +74394,both interview and exam,female,51,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +74395,both interview and exam,male,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +74396,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +74397,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +74398,both interview and exam,male,27,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +74399,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +74400,both interview and exam,male,23,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +74401,both interview and exam,female,19,NA,white,2,234,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,22500 +74402,both interview and exam,female,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +74403,both interview and exam,female,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +74404,both interview and exam,female,0,11,white,1,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74405,both interview and exam,female,5,NA,black,1,73,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74406,both interview and exam,female,0,5,other hispanic,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74407,both interview and exam,female,8,NA,white,1,102,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +74408,both interview and exam,male,29,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +74409,interview only,female,6,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +74410,both interview and exam,male,9,NA,white,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +74411,both interview and exam,male,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,70000 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exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +74422,both interview and exam,male,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,7500 +74423,both interview and exam,male,16,NA,asian,2,193,NA,NA,FALSE,FALSE,3,9,NA,NA,NA,TRUE,NA +74424,both interview and exam,female,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,87500 +74425,both interview and exam,female,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +74426,both interview and exam,male,2,NA,white,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74427,both interview and exam,male,14,NA,black,1,172,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,22500 +74428,both interview and exam,male,0,9,white,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74429,both interview and exam,male,1,13,white,2,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +74430,both interview and exam,male,11,NA,white,2,133,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +74431,both interview and 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interview and exam,female,5,NA,asian,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74469,both interview and exam,male,1,15,black,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74470,both interview and exam,male,4,NA,white,2,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74471,both interview and exam,female,16,NA,mexican american,1,204,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +74472,both interview and exam,female,2,NA,white,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74473,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +74474,both interview and exam,male,3,NA,mexican american,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74475,both interview and exam,male,0,8,mexican american,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +74476,both interview and exam,female,68,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,50000 +74477,both interview and exam,male,1,23,mexican 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exam,male,4,NA,white,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74497,both interview and exam,male,2,NA,other hispanic,1,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +74498,both interview and exam,male,29,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,TRUE,50000 +74499,both interview and exam,male,59,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +74500,both interview and exam,male,6,NA,mexican american,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,12500 +74501,both interview and exam,female,10,NA,white,1,131,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +74502,both interview and exam,male,27,NA,black,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,NA,TRUE,7500 +74503,both interview and exam,female,47,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,30000 +74504,both interview and exam,female,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,22500 +74505,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,100000 +74506,both interview and exam,female,4,NA,mexican american,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +74507,both interview and exam,male,14,NA,mexican american,2,176,NA,NA,FALSE,FALSE,3,8,NA,NA,NA,FALSE,22500 +74508,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74509,both interview and exam,female,48,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +74510,both interview and exam,male,64,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +74511,both interview and exam,male,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74512,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,1,married,NA,TRUE,40000 +74513,both interview and exam,male,15,NA,white,2,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,NA +74514,both interview and exam,female,0,5,other 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interview and exam,male,47,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,FALSE,17500 +74525,both interview and exam,male,11,NA,other,2,137,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +74526,both interview and exam,female,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +74527,both interview and exam,male,0,5,black,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74528,both interview and exam,female,1,15,mexican american,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +74529,both interview and exam,male,51,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,30000 +74530,both interview and exam,female,45,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,3,married,NA,FALSE,22500 +74531,both interview and exam,male,72,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,17500 +74532,both interview and exam,male,25,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,17500 +74533,both interview and exam,female,0,8,white,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74534,both interview and exam,male,65,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +74535,both interview and exam,male,1,22,other hispanic,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +74536,both interview and exam,male,65,NA,other hispanic,1,NA,TRUE,TRUE,FALSE,TRUE,55,NA,4,married,NA,TRUE,30000 +74537,both interview and exam,female,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,12500 +74538,both interview and exam,female,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +74539,both interview and exam,male,55,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +74540,both interview and exam,female,11,NA,other hispanic,2,134,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +74541,both interview and exam,female,5,NA,black,1,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74542,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,2500 +74543,both interview and exam,male,40,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +74544,both interview and exam,male,10,NA,black,1,126,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +74545,both interview and exam,female,8,NA,white,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +74546,both interview and exam,female,27,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,2,never_married,no,FALSE,30000 +74547,both interview and exam,male,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +74548,both interview and exam,female,63,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,4,divorced,NA,FALSE,17500 +74549,both interview and exam,female,55,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,NA,TRUE,70000 +74550,both interview and exam,female,4,NA,black,1,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74551,both interview and exam,female,32,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +74552,both interview and exam,female,44,NA,black,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,never_married,no,TRUE,22500 +74553,both interview and exam,male,6,NA,white,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +74554,both interview and exam,female,35,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +74555,interview only,female,2,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74556,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +74557,both interview and exam,female,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,30000 +74558,both interview and exam,female,1,12,black,2,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74559,both interview and exam,female,19,NA,other hispanic,1,234,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,70000 +74560,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +74561,both interview and exam,male,1,18,mexican american,2,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74562,both interview and exam,male,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +74563,both interview and exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +74564,both interview and exam,female,26,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,unable to ascertain,TRUE,30000 +74565,both interview and exam,male,66,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,NA,FALSE,NA +74566,both interview and exam,female,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,12500 +74567,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +74568,both interview and exam,male,8,NA,other hispanic,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +74569,both interview and exam,male,19,NA,white,1,233,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,40000 +74570,both interview and exam,female,63,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +74571,both interview and exam,male,53,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74572,both interview and exam,female,2,NA,black,1,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74573,both interview and exam,female,4,NA,black,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74574,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +74575,both interview and exam,female,16,NA,other hispanic,2,198,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +74576,both interview and exam,female,73,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +74577,interview only,female,3,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74578,both interview and exam,male,4,NA,other hispanic,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74579,both interview and exam,male,51,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,living_with_partner,NA,TRUE,12500 +74580,both interview and exam,female,13,NA,other hispanic,2,160,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,22500 +74581,both interview and exam,male,75,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +74582,both interview and exam,female,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +74583,both interview and exam,female,60,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +74584,both interview and exam,male,10,NA,black,2,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +74585,interview only,female,0,1,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74586,both interview and exam,male,24,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,30000 +74587,both interview and exam,male,66,NA,mexican american,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +74588,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +74589,both interview and exam,male,67,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,22500 +74590,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +74591,both interview and exam,male,73,NA,black,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,22500 +74592,both interview and exam,male,1,15,black,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74593,both interview and exam,male,0,1,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74594,both interview and exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,50000 +74595,both interview and exam,male,5,NA,mexican american,1,62,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +74596,both interview and exam,female,45,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +74597,both interview and exam,male,0,6,mexican american,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 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and exam,male,17,NA,black,1,211,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +74618,both interview and exam,female,0,9,mexican american,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74619,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +74620,both interview and exam,female,14,NA,black,1,175,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +74621,both interview and exam,female,1,16,asian,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74622,both interview and exam,female,0,8,white,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74623,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +74624,both interview and exam,female,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,12500 +74625,interview only,male,21,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +74626,both interview and exam,male,15,NA,mexican american,1,190,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,NA 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exam,female,60,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,divorced,NA,TRUE,100000 +74637,both interview and exam,male,11,NA,white,1,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +74638,both interview and exam,male,34,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,living_with_partner,NA,TRUE,87500 +74639,both interview and exam,male,51,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +74640,both interview and exam,male,14,NA,white,1,181,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +74641,both interview and exam,male,33,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +74642,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +74643,both interview and exam,male,2,NA,black,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74644,both interview and exam,female,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,NA +74645,both interview and exam,female,68,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +74646,both interview and exam,male,49,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +74647,both interview and exam,female,15,NA,white,2,191,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +74648,both interview and exam,female,18,NA,black,2,221,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,17500 +74649,both interview and exam,female,4,NA,black,2,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74650,both interview and exam,male,56,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,4,married,NA,FALSE,30000 +74651,both interview and exam,male,8,NA,white,2,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,7500 +74652,both interview and exam,female,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,no,FALSE,30000 +74653,both interview and exam,female,29,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,17500 +74654,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +74655,both interview and exam,female,36,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,never_married,no,TRUE,100000 +74656,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74657,both interview and exam,male,3,NA,white,2,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74658,both interview and exam,female,12,NA,mexican american,1,155,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,NA +74659,both interview and exam,male,12,NA,white,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +74660,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +74661,both interview and exam,male,65,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +74662,both interview and exam,female,5,NA,other hispanic,2,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74663,both interview and exam,male,52,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,30000 +74664,interview only,female,8,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +74665,both interview and exam,male,16,NA,mexican american,1,198,NA,NA,FALSE,FALSE,12.5,11,NA,NA,NA,TRUE,30000 +74666,both interview and exam,male,13,NA,asian,1,161,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +74667,both interview and exam,male,6,NA,black,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +74668,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,22500 +74669,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,100000 +74670,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,17500 +74671,both interview and exam,female,12,NA,other hispanic,2,155,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,50000 +74672,both interview and exam,male,17,NA,mexican american,2,213,FALSE,NA,FALSE,FALSE,17.5,10,NA,NA,NA,TRUE,30000 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exam,male,17,NA,black,1,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +74683,both interview and exam,female,56,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,never_married,NA,TRUE,100000 +74684,both interview and exam,female,0,2,mexican american,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74685,both interview and exam,male,75,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,TRUE,12500 +74686,both interview and exam,female,32,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,70000 +74687,both interview and exam,male,16,NA,black,1,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +74688,both interview and exam,male,5,NA,white,1,72,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74689,both interview and exam,female,25,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +74690,both interview and exam,male,11,NA,white,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +74691,both interview and exam,female,12,NA,white,1,155,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +74692,both interview and exam,male,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,60000 +74693,both interview and exam,female,37,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,separated,no,FALSE,50000 +74694,both interview and exam,male,71,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +74695,both interview and exam,male,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +74696,both interview and exam,male,62,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +74697,both interview and exam,male,44,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,FALSE,22500 +74698,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +74699,both interview and exam,male,13,NA,white,2,166,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,60000 +74700,both interview and exam,female,11,NA,other,1,135,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +74701,both interview and exam,male,15,NA,white,2,185,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +74702,both interview and exam,male,68,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +74703,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +74704,both interview and exam,female,54,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +74705,both interview and exam,male,74,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +74706,both interview and exam,male,8,NA,black,2,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +74707,both interview and exam,male,51,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,4,married,NA,FALSE,40000 +74708,both interview and exam,male,76,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,1,married,NA,TRUE,100000 +74709,both interview and exam,male,18,NA,asian,1,220,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 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exam,female,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +74720,both interview and exam,female,11,NA,mexican american,2,134,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +74721,both interview and exam,female,53,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,separated,NA,TRUE,70000 +74722,both interview and exam,male,12,NA,black,1,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +74723,both interview and exam,male,66,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +74724,both interview and exam,female,7,NA,mexican american,1,91,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,17500 +74725,both interview and exam,female,37,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +74726,both interview and exam,female,8,NA,mexican american,2,102,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,50000 +74727,both interview and exam,female,3,NA,white,2,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74728,both interview and exam,male,46,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,50000 +74729,both interview and exam,male,5,NA,mexican american,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74730,both interview and exam,male,13,NA,other,2,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +74731,both interview and exam,female,27,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,4,living_with_partner,no,TRUE,7500 +74732,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +74733,both interview and exam,male,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74734,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +74735,both interview and exam,female,9,NA,black,1,116,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,50000 +74736,both interview and exam,male,3,NA,white,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74737,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 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exam,female,64,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,TRUE,30000 +74748,both interview and exam,male,36,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +74749,both interview and exam,female,16,NA,black,1,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +74750,interview only,female,6,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74751,both interview and exam,female,53,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +74752,both interview and exam,female,10,NA,mexican american,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,17500 +74753,both interview and exam,male,12,NA,black,1,147,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,12500 +74754,both interview and exam,male,14,NA,black,1,177,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,87500 +74755,both interview and exam,male,8,NA,other,1,97,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +74756,both interview and exam,female,50,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,separated,NA,TRUE,22500 +74757,both interview and exam,male,7,NA,black,1,95,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +74758,both interview and exam,male,2,NA,other,1,31,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,TRUE,30000 +74759,both interview and exam,male,11,NA,black,1,138,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +74760,both interview and exam,male,53,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,12500 +74761,both interview and exam,male,5,NA,black,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +74762,both interview and exam,male,11,NA,mexican american,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +74763,both interview and exam,male,33,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +74764,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +74765,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +74766,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,12500 +74767,both interview and exam,female,8,NA,black,2,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +74768,both interview and exam,female,0,5,white,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74769,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74770,both interview and exam,male,7,NA,black,1,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +74771,both interview and exam,female,10,NA,white,1,121,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +74772,both interview and exam,female,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,30000 +74773,both interview and exam,male,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,22500 +74774,both interview and exam,female,19,NA,black,1,232,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,12500 +74775,both interview and exam,male,0,1,white,2,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +74776,both interview and exam,male,18,NA,other hispanic,2,218,FALSE,NA,FALSE,FALSE,12.5,12,NA,NA,NA,TRUE,50000 +74777,both interview and exam,male,0,7,white,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74778,both interview and exam,female,18,NA,white,1,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,60000 +74779,both interview and exam,female,78,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,45,NA,5,never_married,NA,TRUE,NA +74780,both interview and exam,female,6,NA,mexican american,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,40000 +74781,both interview and exam,female,51,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,70000 +74782,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +74783,both interview and exam,female,13,NA,black,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +74784,both interview and exam,female,39,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,unable to ascertain,FALSE,70000 +74785,both interview and exam,female,12,NA,mexican american,1,155,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +74786,both interview and exam,female,17,NA,black,2,212,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,7500 +74787,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +74788,both interview and exam,male,13,NA,black,2,168,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +74789,both interview and exam,female,12,NA,mexican american,1,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,40000 +74790,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,100000 +74791,both interview and exam,female,69,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,TRUE,NA +74792,both interview and exam,female,2,NA,other hispanic,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74793,both interview and exam,female,5,NA,black,1,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74794,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74795,both interview and exam,female,12,NA,mexican american,2,150,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,50000 +74796,both interview and exam,male,14,NA,black,1,172,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,17500 +74797,both interview and exam,female,59,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,100000 +74798,both interview and exam,male,5,NA,mexican american,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74799,both interview and exam,female,1,22,white,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74800,both interview and exam,male,28,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +74801,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +74802,both interview and exam,male,18,NA,asian,1,227,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +74803,both interview and exam,female,24,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,3,NA,4,separated,no,TRUE,7500 +74804,both interview and exam,female,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +74805,both interview and exam,male,12,NA,other hispanic,2,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +74806,both interview and exam,male,11,NA,asian,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +74807,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,12500 +74808,both interview and exam,female,0,4,other hispanic,1,4,NA,NA,FALSE,TRUE,0.5,NA,NA,NA,NA,TRUE,7500 +74809,both interview and exam,male,9,NA,black,1,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +74810,interview only,female,3,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +74811,both interview and exam,male,2,NA,asian,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74812,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,7500 +74813,both interview and exam,female,13,NA,other,1,159,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +74814,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,12500 +74815,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +74816,both interview and exam,male,13,NA,mexican american,1,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,7500 +74817,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +74818,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74819,both interview and exam,male,1,17,mexican american,2,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74820,both interview and exam,male,1,18,black,1,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74821,both interview and exam,female,4,NA,black,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74822,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,100000 +74823,both interview and exam,male,67,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +74824,both interview and exam,female,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +74825,both interview and exam,male,16,NA,mexican american,2,203,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +74826,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74827,both interview and exam,female,0,11,white,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74828,both interview and exam,male,8,NA,other,1,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +74829,both interview and exam,female,27,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,yes,TRUE,7500 +74830,both interview and exam,male,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +74831,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74832,both interview and exam,male,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,87500 +74833,both interview and exam,male,16,NA,white,2,196,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +74834,both interview and exam,male,48,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,living_with_partner,NA,FALSE,NA +74835,both interview and exam,male,7,NA,white,1,95,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,70000 +74836,both interview and exam,female,4,NA,black,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74837,both interview and exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +74838,both interview and exam,female,8,NA,other hispanic,1,97,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +74839,both interview and exam,male,47,NA,white,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +74840,both interview and exam,male,10,NA,mexican american,1,121,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +74841,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,widowed,NA,TRUE,NA +74842,both interview and exam,female,2,NA,white,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +74843,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,no,FALSE,7500 +74844,both interview and exam,male,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +74845,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +74846,both interview and exam,female,2,NA,mexican american,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74847,both interview and exam,female,1,20,asian,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74848,both interview and exam,female,5,NA,white,2,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74849,both interview and exam,male,9,NA,other hispanic,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +74850,both interview and exam,female,2,NA,white,2,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 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exam,male,40,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,70000 +74861,both interview and exam,male,60,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,7500 +74862,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +74863,both interview and exam,male,1,20,white,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74864,both interview and exam,female,11,NA,mexican american,2,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,30000 +74865,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +74866,both interview and exam,male,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +74867,both interview and exam,female,53,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +74868,both interview and exam,female,9,NA,mexican american,1,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,22500 +74869,both interview and exam,female,66,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,30000 +74870,both interview and exam,female,11,NA,black,1,137,NA,NA,FALSE,FALSE,7.5,5,NA,NA,NA,TRUE,22500 +74871,both interview and exam,male,8,NA,black,1,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,2500 +74872,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +74873,both interview and exam,female,1,17,black,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74874,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74875,both interview and exam,female,5,NA,black,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74876,both interview and exam,male,2,NA,other hispanic,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74877,both interview and exam,female,14,NA,mexican american,1,179,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,NA +74878,both interview and exam,female,69,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,87500 +74879,both interview and exam,female,43,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,no,TRUE,100000 +74880,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +74881,both interview and exam,female,14,NA,white,1,180,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +74882,both interview and exam,male,25,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,married,NA,FALSE,50000 +74883,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +74884,both interview and exam,male,0,7,white,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74885,both interview and exam,female,57,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +74886,both interview and exam,female,18,NA,black,1,223,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,30000 +74887,both interview and exam,male,13,NA,black,1,164,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +74888,interview only,male,21,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +74889,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +74890,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +74891,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,70000 +74892,both interview and exam,female,0,0,other,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74893,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74894,both interview and exam,female,6,NA,asian,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74895,both interview and exam,female,15,NA,white,2,191,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,70000 +74896,both interview and exam,male,6,NA,black,1,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +74897,both interview and exam,female,46,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,FALSE,22500 +74898,both interview and exam,female,2,NA,mexican american,1,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +74899,both interview and exam,female,0,7,other hispanic,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74900,both interview and exam,female,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +74901,both interview and exam,male,55,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +74902,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +74903,both interview and exam,male,11,NA,black,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,NA +74904,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +74905,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74906,both interview and exam,male,0,6,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74907,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +74908,both interview and exam,male,0,4,black,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74909,both interview and exam,male,64,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,FALSE,50000 +74910,both interview and exam,female,19,NA,black,1,231,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,7500 +74911,both interview and exam,female,13,NA,mexican american,2,166,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,NA +74912,both interview and exam,male,12,NA,asian,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,NA +74913,both interview and exam,female,14,NA,black,2,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +74914,both interview and exam,male,9,NA,mexican american,2,118,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +74915,both interview and exam,female,4,NA,asian,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74916,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +74917,both interview and exam,female,11,NA,white,2,137,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +74918,both interview and exam,female,49,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,NA,FALSE,40000 +74919,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +74920,both interview and exam,female,6,NA,black,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +74921,both interview and exam,male,0,10,mexican american,1,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74922,both interview and exam,male,3,NA,black,2,46,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74923,both interview and exam,male,24,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +74924,both interview and exam,male,1,17,white,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74925,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,30000 +74926,both interview and exam,female,6,NA,black,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +74927,both interview and exam,male,17,NA,black,1,209,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +74928,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,60000 +74929,both interview and exam,female,66,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +74930,both interview and exam,female,11,NA,white,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +74931,both interview and exam,male,53,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +74932,both interview and exam,male,32,NA,other,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +74933,both interview and exam,female,57,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +74934,both interview and exam,male,14,NA,black,1,169,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +74935,both interview and exam,male,20,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,never_married,NA,TRUE,NA +74936,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +74937,both interview and exam,male,74,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +74938,both interview and exam,female,52,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +74939,both interview and exam,male,13,NA,asian,1,156,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +74940,both interview and exam,male,80,NA,black,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,TRUE,40000 +74941,both interview and exam,female,59,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +74942,both interview and exam,female,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +74943,both interview and exam,male,19,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,40000 +74944,both interview and exam,female,2,NA,black,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74945,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +74946,both interview and exam,male,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,2500 +74947,both interview and exam,female,3,NA,other,1,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74948,both interview and exam,female,33,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +74949,both interview and exam,male,8,NA,white,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +74950,both interview and exam,female,20,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,never_married,no,TRUE,40000 +74951,both interview and exam,male,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +74952,both interview and exam,female,0,8,white,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74953,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 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exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +74964,both interview and exam,female,2,NA,mexican american,2,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74965,both interview and exam,male,26,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +74966,both interview and exam,male,3,NA,other,1,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74967,both interview and exam,female,0,6,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74968,both interview and exam,female,10,NA,black,1,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +74969,both interview and exam,male,22,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,never_married,NA,TRUE,22500 +74970,both interview and exam,male,1,16,other,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74971,both interview and exam,female,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +74972,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 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exam,male,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +74983,both interview and exam,female,63,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,2,married,NA,TRUE,30000 +74984,both interview and exam,male,64,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,never_married,NA,FALSE,NA +74985,both interview and exam,female,66,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,widowed,NA,FALSE,12500 +74986,both interview and exam,female,17,NA,mexican american,2,214,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,FALSE,22500 +74987,both interview and exam,female,10,NA,black,2,132,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +74988,both interview and exam,female,8,NA,white,1,103,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +74989,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,NA +74990,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +74991,both interview and 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interview and exam,female,69,NA,white,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,60000 +75012,both interview and exam,male,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +75013,both interview and exam,male,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +75014,interview only,male,47,NA,asian,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,TRUE,87500 +75015,both interview and exam,female,2,NA,mexican american,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75016,both interview and exam,male,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +75017,both interview and exam,male,54,NA,black,2,NA,FALSE,NA,FALSE,FALSE,35,NA,2,never_married,NA,TRUE,40000 +75018,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +75019,both interview and exam,female,11,NA,white,2,143,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +75020,both interview and exam,female,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +75021,both interview and exam,female,0,8,asian,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75022,interview only,male,10,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +75023,both interview and exam,male,27,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +75024,both interview and exam,female,3,NA,white,1,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +75025,both interview and exam,female,12,NA,black,2,155,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,70000 +75026,interview only,male,6,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +75027,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,100000 +75028,both interview and exam,female,10,NA,white,1,128,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +75029,both interview and exam,male,23,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,NA +75030,both interview and 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interview and exam,female,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,87500 +75098,both interview and exam,male,25,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +75099,both interview and exam,male,46,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +75100,both interview and exam,male,15,NA,other,2,181,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +75101,both interview and exam,female,15,NA,other hispanic,1,186,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +75102,both interview and exam,male,16,NA,asian,1,198,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +75103,both interview and exam,female,55,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +75104,both interview and exam,female,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +75105,both interview and exam,male,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75106,both interview and exam,female,2,NA,other,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +75107,both interview and exam,female,8,NA,white,2,106,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +75108,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +75109,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +75110,both interview and exam,male,5,NA,black,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75111,both interview and exam,male,32,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,NA,TRUE,40000 +75112,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +75113,interview only,male,36,NA,asian,NA,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,TRUE,22500 +75114,both interview and exam,female,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +75115,both interview and exam,female,2,NA,other,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +75116,both interview and exam,female,0,5,black,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +75117,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +75118,both interview and exam,female,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,87500 +75119,both interview and exam,male,15,NA,mexican american,2,188,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,70000 +75120,both interview and exam,male,2,NA,black,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +75121,both interview and exam,male,44,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,5,married,NA,TRUE,NA +75122,both interview and exam,male,4,NA,other hispanic,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +75123,both interview and exam,male,35,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +75124,both interview and exam,male,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +75125,both interview and exam,female,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,12500 +75126,both interview and exam,male,6,NA,other,1,76,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +75127,both interview and exam,male,59,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +75128,both interview and exam,male,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +75129,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,30000 +75130,both interview and exam,male,6,NA,mexican american,1,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,50000 +75131,both interview and exam,female,34,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +75132,both interview and exam,male,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +75133,both interview and exam,male,12,NA,black,2,147,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +75134,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,12500 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exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,70000 +75165,both interview and exam,male,10,NA,other hispanic,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,12500 +75166,both interview and exam,male,14,NA,other hispanic,2,174,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +75167,both interview and exam,female,11,NA,black,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +75168,both interview and exam,female,0,3,white,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75169,both interview and exam,female,11,NA,other hispanic,2,136,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +75170,both interview and exam,male,45,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,30000 +75171,both interview and exam,female,17,NA,black,1,205,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,12500 +75172,both interview and exam,female,0,10,white,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75173,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,87500 +75174,both interview and exam,male,76,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,17500 +75175,both interview and exam,male,34,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,40000 +75176,both interview and exam,male,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +75177,both interview and exam,male,9,NA,other hispanic,1,115,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +75178,both interview and exam,female,19,NA,asian,2,233,FALSE,NA,FALSE,TRUE,17.5,14,NA,NA,NA,TRUE,100000 +75179,both interview and exam,female,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,12500 +75180,both interview and exam,male,4,NA,other,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +75181,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +75182,both interview and exam,male,8,NA,mexican 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exam,female,2,NA,asian,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75193,both interview and exam,female,57,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,divorced,NA,TRUE,12500 +75194,both interview and exam,male,11,NA,other hispanic,2,142,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,7500 +75195,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +75196,both interview and exam,female,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,100000 +75197,interview only,male,10,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +75198,interview only,female,11,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,7500 +75199,both interview and exam,female,0,2,other hispanic,2,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +75200,both interview and exam,female,4,NA,white,2,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75201,both interview and exam,male,11,NA,white,1,133,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +75202,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,60000 +75203,both interview and exam,male,69,NA,mexican american,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +75204,both interview and exam,female,7,NA,black,1,91,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,7500 +75205,both interview and exam,female,32,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,no,TRUE,100000 +75206,both interview and exam,male,9,NA,white,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +75207,both interview and exam,male,65,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +75208,both interview and exam,male,9,NA,black,2,117,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +75209,both interview and exam,female,18,NA,asian,1,222,FALSE,NA,FALSE,TRUE,17.5,13,NA,NA,NA,TRUE,7500 +75210,both interview and exam,female,7,NA,mexican american,2,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,22500 +75211,both interview and exam,male,37,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 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exam,male,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +75222,both interview and exam,female,65,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,NA,TRUE,100000 +75223,both interview and exam,female,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +75224,both interview and exam,female,27,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,50000 +75225,both interview and exam,male,14,NA,mexican american,1,179,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,40000 +75226,both interview and exam,female,8,NA,white,2,98,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,17500 +75227,both interview and exam,female,18,NA,asian,1,219,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,12500 +75228,interview only,female,7,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,NA +75229,both interview and exam,male,0,1,black,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75230,both interview and exam,female,2,NA,other hispanic,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 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exam,male,9,NA,asian,2,118,NA,NA,FALSE,FALSE,0.5,4,NA,NA,NA,TRUE,87500 +75251,both interview and exam,male,22,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,22500 +75252,both interview and exam,male,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,70000 +75253,both interview and exam,male,15,NA,mexican american,1,184,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,87500 +75254,both interview and exam,male,26,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +75255,both interview and exam,female,8,NA,asian,1,109,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +75256,both interview and exam,male,44,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,NA,FALSE,50000 +75257,both interview and exam,male,21,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,2500 +75258,both interview and exam,male,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +75259,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +75260,both interview and exam,female,20,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +75261,both interview and exam,male,7,NA,other,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +75262,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75263,both interview and exam,female,61,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,2,married,NA,TRUE,NA +75264,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +75265,both interview and exam,female,16,NA,white,2,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +75266,both interview and exam,female,1,17,black,1,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +75267,both interview and exam,female,4,NA,mexican american,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +75268,both interview and exam,male,28,NA,mexican 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exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +75344,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +75345,both interview and exam,female,54,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +75346,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75347,both interview and exam,female,62,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75348,both interview and exam,female,9,NA,black,2,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +75349,both interview and exam,male,54,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,separated,NA,FALSE,30000 +75350,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,22500 +75351,both interview and exam,female,29,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +75352,both interview and exam,male,30,NA,other 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exam,male,8,NA,other hispanic,2,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,30000 +75576,both interview and exam,male,47,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +75577,both interview and exam,female,1,12,white,1,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +75578,both interview and exam,male,16,NA,other hispanic,1,197,NA,NA,FALSE,FALSE,0.5,8,NA,NA,NA,FALSE,12500 +75579,both interview and exam,male,60,NA,mexican american,1,NA,TRUE,TRUE,FALSE,TRUE,55,NA,4,married,NA,TRUE,40000 +75580,both interview and exam,female,12,NA,other,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +75581,both interview and exam,female,74,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +75582,both interview and exam,male,3,NA,white,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75583,both interview and exam,male,12,NA,mexican american,1,148,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,17500 +75584,both interview and exam,female,52,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,divorced,NA,TRUE,70000 +75585,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,NA +75586,both interview and exam,female,14,NA,mexican american,1,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,NA +75587,both interview and exam,male,16,NA,white,2,202,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,NA +75588,both interview and exam,male,32,NA,other hispanic,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +75589,both interview and exam,female,13,NA,asian,1,159,NA,NA,FALSE,FALSE,7.5,7,NA,NA,NA,TRUE,7500 +75590,both interview and exam,male,45,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +75591,both interview and exam,male,38,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +75592,both interview and exam,female,69,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,3,NA,1,divorced,NA,TRUE,30000 +75593,both interview and exam,female,34,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,12500 +75594,both interview and exam,female,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,7500 +75595,both interview and exam,male,21,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,3,never_married,NA,TRUE,40000 +75596,both interview and exam,male,35,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,17500 +75597,both interview and exam,female,3,NA,black,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +75598,both interview and exam,female,62,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +75599,both interview and exam,female,0,11,other hispanic,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +75600,interview only,male,10,NA,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +75601,both interview and exam,male,61,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,4,married,NA,TRUE,60000 +75602,both interview and exam,male,14,NA,mexican american,1,179,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +75603,both interview and exam,female,3,NA,white,2,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75604,both interview and exam,male,3,NA,white,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +75605,both interview and exam,male,11,NA,white,2,145,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +75606,both interview and exam,female,0,5,asian,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +75607,both interview and exam,male,64,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,NA +75608,both interview and exam,female,17,NA,other hispanic,1,216,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +75609,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +75610,both interview and exam,male,56,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +75611,both interview and exam,female,38,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,1,married,no,TRUE,NA +75612,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +75613,both interview and exam,female,55,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +75614,both interview and exam,female,7,NA,black,2,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +75615,both interview and exam,female,1,23,white,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +75616,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +75617,both interview and exam,male,2,NA,white,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75618,both interview and exam,male,13,NA,mexican american,2,159,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,40000 +75619,both interview and exam,male,36,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,100000 +75620,both interview and exam,female,52,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +75621,both interview and exam,female,59,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +75622,both interview and exam,female,8,NA,white,1,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +75623,both interview and exam,male,9,NA,white,2,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +75624,both interview and exam,female,21,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,never_married,no,TRUE,50000 +75625,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +75626,both interview and exam,female,5,NA,other hispanic,2,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +75627,both interview and exam,male,1,15,black,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75628,both interview and exam,female,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +75629,both interview and exam,female,9,NA,other hispanic,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +75630,both interview and exam,female,59,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +75631,both interview and exam,female,72,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +75632,both interview and exam,female,3,NA,asian,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +75633,both interview and exam,male,10,NA,mexican american,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,NA +75634,both interview and exam,male,13,NA,black,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +75635,both interview and exam,female,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +75636,both interview and exam,female,35,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +75637,both interview and exam,female,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,100000 +75638,both interview and exam,female,16,NA,black,2,197,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +75639,both interview and exam,male,15,NA,black,1,184,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +75640,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +75641,both interview and exam,female,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75642,both interview and exam,male,1,22,mexican american,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +75643,both interview and exam,female,43,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,FALSE,7500 +75644,both interview and exam,male,69,NA,asian,1,NA,TRUE,TRUE,FALSE,TRUE,45,NA,2,married,NA,TRUE,NA +75645,both interview and exam,male,6,NA,black,1,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +75646,both interview and exam,male,20,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +75647,both interview and exam,male,28,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +75648,both interview and exam,female,18,NA,other hispanic,1,219,FALSE,NA,FALSE,FALSE,0.5,9,NA,NA,NA,FALSE,22500 +75649,both interview and exam,male,11,NA,white,1,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +75650,both interview and exam,female,13,NA,mexican american,2,159,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +75651,both interview and exam,male,1,21,asian,2,21,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,100000 +75652,both interview and exam,male,4,NA,mexican american,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +75653,both interview and exam,male,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +75654,both interview and exam,female,49,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +75655,both interview and exam,male,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +75656,both interview and exam,female,1,12,white,2,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +75657,both interview and exam,female,12,NA,white,2,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +75658,both interview and exam,male,8,NA,black,2,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +75659,both interview and exam,male,15,NA,black,2,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +75660,both interview and exam,female,59,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +75661,both interview and exam,male,4,NA,asian,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +75662,both interview and exam,female,44,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +75663,both interview and exam,female,54,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +75664,both interview and exam,female,31,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,7500 +75665,both interview and exam,female,12,NA,other hispanic,2,152,NA,NA,FALSE,FALSE,3,7,NA,NA,NA,FALSE,22500 +75666,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75667,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +75668,both interview and exam,male,10,NA,mexican american,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +75669,both interview and exam,male,64,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,divorced,NA,TRUE,100000 +75670,both interview and exam,female,27,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,50000 +75671,both interview and exam,male,11,NA,asian,1,144,NA,NA,FALSE,FALSE,3,6,NA,NA,NA,TRUE,60000 +75672,interview only,male,1,13,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +75673,interview only,female,6,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +75674,both interview and exam,male,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,17500 +75675,both interview and exam,female,17,NA,black,1,208,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,NA +75676,both interview and exam,female,6,NA,asian,1,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +75677,both interview and exam,female,10,NA,black,2,125,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +75678,both interview and exam,male,10,NA,other hispanic,2,126,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +75679,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +75680,both interview and exam,female,15,NA,white,2,181,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +75681,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,40000 +75682,both interview and exam,male,29,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +75683,both interview and exam,male,23,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,NA +75684,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +75685,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,2500 +75686,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +75687,interview only,female,20,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,100000 +75688,both interview and exam,female,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,2,divorced,NA,FALSE,7500 +75689,both interview and exam,male,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +75690,both interview and exam,male,34,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,40000 +75691,both interview and exam,female,70,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +75692,both interview and exam,male,18,NA,white,2,218,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +75693,both interview and exam,male,0,2,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +75694,both interview and exam,male,9,NA,other hispanic,2,112,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +75695,both interview and exam,female,74,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,widowed,NA,FALSE,30000 +75696,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,widowed,NA,TRUE,12500 +75697,both interview and exam,female,10,NA,white,1,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +75698,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +75699,both interview and exam,female,62,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,1,never_married,NA,FALSE,17500 +75700,both interview and exam,male,68,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,divorced,NA,FALSE,17500 +75701,both interview and exam,female,2,NA,white,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75702,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,divorced,NA,TRUE,50000 +75703,both interview and exam,male,3,NA,black,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75704,both interview and exam,male,24,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +75705,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +75706,both interview and exam,female,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +75707,both interview and exam,female,14,NA,other hispanic,2,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,17500 +75708,both interview and exam,female,5,NA,black,1,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +75709,both interview and exam,female,30,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,no,TRUE,60000 +75710,both interview and exam,male,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75711,both interview and exam,male,12,NA,mexican american,1,150,NA,NA,FALSE,FALSE,3,5,NA,NA,NA,TRUE,87500 +75712,both interview and exam,male,11,NA,white,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +75713,both interview and exam,female,12,NA,asian,1,145,NA,NA,FALSE,FALSE,7.5,6,NA,NA,NA,TRUE,7500 +75714,both interview and exam,male,54,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +75715,both interview and exam,male,12,NA,other hispanic,2,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,NA +75716,both interview and exam,male,2,NA,mexican american,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +75717,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +75718,both interview and exam,male,0,11,other,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75719,both interview and exam,male,2,NA,other,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +75720,both interview and exam,male,6,NA,mexican american,2,72,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,60000 +75721,both interview and exam,male,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +75722,both interview and exam,male,15,NA,black,1,188,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +75723,both interview and exam,female,55,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,never_married,NA,TRUE,17500 +75724,both interview and exam,male,66,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,50000 +75725,both interview and exam,male,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +75726,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +75727,both interview and exam,male,0,0,white,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +75728,both interview and exam,male,10,NA,white,2,131,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +75729,both interview and exam,female,11,NA,mexican american,1,137,NA,NA,FALSE,FALSE,12.5,4,NA,NA,NA,FALSE,50000 +75730,both interview and exam,male,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +75731,both interview and exam,male,8,NA,other hispanic,1,106,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,2500 +75732,both interview and exam,male,15,NA,mexican american,2,190,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +75733,both interview and exam,male,56,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +75734,both interview and exam,male,18,NA,black,1,223,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,87500 +75735,both interview and exam,male,19,NA,asian,2,237,TRUE,FALSE,FALSE,TRUE,17.5,13,NA,NA,NA,TRUE,100000 +75736,both interview and exam,male,0,5,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75737,both interview and exam,female,20,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +75738,both interview and exam,male,47,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,87500 +75739,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +75740,both interview and exam,female,5,NA,black,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +75741,both interview and exam,female,11,NA,white,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +75742,both interview and exam,male,37,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,70000 +75743,both interview and exam,female,36,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,no,TRUE,7500 +75744,both interview and exam,female,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +75745,both interview and exam,female,44,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,no,TRUE,40000 +75746,both interview and exam,female,2,NA,other,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75747,both interview and exam,male,18,NA,asian,2,221,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,87500 +75748,both interview and exam,female,80,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,60000 +75749,both interview and exam,male,69,NA,other hispanic,2,NA,TRUE,FALSE,FALSE,TRUE,45,NA,3,divorced,NA,TRUE,7500 +75750,both interview and exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75751,both interview and exam,male,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75752,both interview and exam,female,11,NA,white,2,141,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +75753,both interview and exam,male,19,NA,mexican american,1,238,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +75754,both interview and exam,male,55,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +75755,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +75756,both interview and exam,female,5,NA,white,2,70,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,NA +75757,both interview and exam,female,7,NA,mexican american,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +75758,both interview and exam,male,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +75759,both interview and exam,male,11,NA,other hispanic,2,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +75760,both interview and exam,female,12,NA,asian,1,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +75761,both interview and exam,female,6,NA,black,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +75762,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,70000 +75763,both interview and exam,male,32,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,30000 +75764,both interview and exam,female,2,NA,other hispanic,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +75765,both interview and exam,female,7,NA,black,1,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +75766,both interview and exam,female,16,NA,white,2,195,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +75767,both interview and exam,female,9,NA,mexican american,2,113,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,40000 +75768,both interview and exam,male,46,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,35,NA,3,married,NA,TRUE,70000 +75769,both interview and exam,male,72,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +75770,both interview and exam,female,10,NA,white,2,127,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +75771,both interview and exam,male,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +75772,both interview and exam,female,15,NA,white,1,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +75773,both interview and exam,female,19,NA,white,1,229,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +75774,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +75775,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,NA,TRUE,NA +75776,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,22500 +75777,both interview and exam,male,9,NA,asian,2,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +75778,interview only,male,62,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,TRUE,30000 +75779,both interview and exam,male,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +75780,both interview and exam,male,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,22500 +75781,both interview and exam,male,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75782,both interview and exam,male,6,NA,mexican american,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +75783,interview only,male,55,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,40000 +75784,both interview and exam,male,57,NA,other hispanic,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +75785,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,70000 +75786,both interview and exam,female,54,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +75787,both interview and exam,male,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +75788,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75789,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +75790,both interview and exam,female,28,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +75791,both interview and exam,female,12,NA,black,1,150,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +75792,both interview and exam,male,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +75793,both interview and exam,female,2,NA,white,1,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +75794,both interview and exam,female,8,NA,black,1,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +75795,both interview and exam,male,79,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,55,NA,1,married,NA,FALSE,22500 +75796,both interview and exam,female,14,NA,black,1,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +75797,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,87500 +75798,both interview and exam,male,9,NA,mexican american,1,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,40000 +75799,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +75800,both interview and exam,male,9,NA,mexican american,1,118,NA,NA,FALSE,FALSE,7.5,3,NA,NA,NA,FALSE,22500 +75801,both interview and exam,male,3,NA,mexican american,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +75802,both interview and exam,male,15,NA,mexican american,1,192,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,NA +75803,both interview and exam,male,40,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +75804,both interview and exam,male,0,8,white,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75805,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,22500 +75806,both interview and exam,male,7,NA,white,2,94,NA,NA,FALSE,FALSE,3,2,NA,NA,NA,TRUE,NA +75807,both interview and exam,female,32,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +75808,both interview and exam,male,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +75809,both interview and exam,male,13,NA,white,2,159,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +75810,both interview and exam,male,7,NA,white,2,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +75811,both interview and exam,female,8,NA,mexican american,2,102,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +75812,interview only,female,1,13,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75813,both interview and exam,female,6,NA,black,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +75814,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,2500 +75815,both interview and exam,male,7,NA,other,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +75816,both interview and exam,female,17,NA,asian,2,214,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,60000 +75817,both interview and exam,female,53,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,1,married,NA,TRUE,50000 +75818,both interview and exam,female,6,NA,black,1,79,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +75819,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +75820,both interview and exam,female,43,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,no,TRUE,100000 +75821,interview only,male,25,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,5,never_married,NA,TRUE,70000 +75822,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,100000 +75823,both interview and exam,female,43,NA,other,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,no,TRUE,100000 +75824,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +75825,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,no,TRUE,40000 +75826,both interview and exam,male,70,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +75827,both interview and exam,female,14,NA,other,2,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,87500 +75828,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +75829,both interview and exam,male,5,NA,mexican american,1,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +75830,both interview and exam,female,18,NA,black,1,218,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +75831,both interview and exam,female,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +75832,both interview and exam,female,14,NA,mexican american,2,169,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +75833,both interview and exam,male,15,NA,black,2,185,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +75834,both interview and exam,male,0,7,other,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +75835,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +75836,both interview and exam,male,16,NA,other,2,195,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +75837,both interview and exam,male,55,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +75838,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +75839,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,no,TRUE,30000 +75840,both interview and exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75841,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +75842,both interview and exam,male,23,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +75843,both interview and exam,female,0,0,mexican american,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +75844,both interview and exam,female,16,NA,white,1,194,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +75845,both interview and exam,male,59,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,4,separated,NA,TRUE,50000 +75846,both interview and exam,female,7,NA,mexican american,1,88,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,7500 +75847,both interview and exam,female,6,NA,black,1,77,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +75848,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75849,both interview and exam,female,3,NA,other hispanic,2,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75850,both interview and exam,female,37,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,no,TRUE,100000 +75851,both interview and exam,male,11,NA,other hispanic,2,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +75852,both interview and exam,male,7,NA,white,2,85,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +75853,both interview and exam,female,19,NA,mexican american,2,239,FALSE,NA,FALSE,FALSE,3,11,NA,NA,NA,FALSE,12500 +75854,both interview and exam,male,18,NA,white,2,221,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,50000 +75855,both interview and exam,female,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +75856,both interview and exam,female,28,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +75857,both interview and exam,female,7,NA,black,2,95,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +75858,both interview and exam,female,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,yes,TRUE,40000 +75859,both interview and exam,female,11,NA,mexican american,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +75860,both interview and exam,male,60,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,87500 +75861,both interview and exam,female,52,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,60000 +75862,both interview and exam,female,10,NA,other hispanic,2,124,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +75863,both interview and exam,female,62,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +75864,both interview and exam,female,4,NA,black,2,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +75865,both interview and exam,female,5,NA,black,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +75866,both interview and exam,male,12,NA,mexican american,2,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +75867,both interview and exam,male,1,22,asian,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75868,both interview and exam,female,0,7,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +75869,both interview and exam,male,27,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +75870,both interview and exam,female,40,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,60000 +75871,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +75872,both interview and exam,female,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,12500 +75873,both interview and exam,male,9,NA,white,2,109,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +75874,both interview and exam,male,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +75875,both interview and exam,male,14,NA,black,1,169,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +75876,both interview and exam,male,4,NA,white,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75877,both interview and exam,male,1,21,white,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +75878,both interview and exam,female,12,NA,mexican american,1,156,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,30000 +75879,both interview and exam,male,56,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,12500 +75880,both interview and exam,female,13,NA,asian,1,158,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +75881,both interview and exam,female,25,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,never_married,no,FALSE,40000 +75882,both interview and exam,male,54,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +75883,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +75884,both interview and exam,female,3,NA,white,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +75885,both interview and exam,male,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75886,both interview and exam,male,12,NA,mexican american,2,155,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,NA +75887,both interview and exam,female,56,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +75888,both interview and exam,female,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,40000 +75889,interview only,male,4,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +75890,both interview and exam,female,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,50000 +75891,both interview and exam,male,2,NA,white,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +75892,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +75893,both interview and exam,female,49,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,TRUE,87500 +75894,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +75895,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +75896,both interview and exam,male,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,40000 +75897,both interview and exam,female,0,7,white,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75898,both interview and exam,male,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,40000 +75899,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,NA +75900,both interview and exam,male,21,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,never_married,NA,TRUE,40000 +75901,both interview and exam,female,19,NA,white,2,238,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,60000 +75902,both interview and exam,male,19,NA,other hispanic,1,231,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,22500 +75903,both interview and exam,male,28,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,17500 +75904,both interview and exam,female,70,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,widowed,NA,FALSE,30000 +75905,both interview and exam,female,39,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,never_married,no,TRUE,87500 +75906,both interview and exam,male,17,NA,white,1,210,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +75907,both interview and exam,male,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +75908,both interview and exam,female,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +75909,both interview and exam,female,77,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,FALSE,7500 +75910,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +75911,both interview and exam,male,67,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,separated,NA,TRUE,50000 +75912,both interview and exam,male,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +75913,both interview and exam,female,32,NA,white,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,never_married,no,TRUE,NA +75914,both interview and exam,male,1,14,other hispanic,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75915,both interview and exam,female,63,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +75916,both interview and exam,male,7,NA,white,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +75917,interview only,female,13,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +75918,both interview and exam,female,7,NA,white,1,89,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +75919,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,NA +75920,both interview and exam,male,11,NA,mexican american,2,134,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +75921,both interview and exam,male,76,NA,black,1,NA,FALSE,NA,FALSE,TRUE,55,NA,4,married,NA,TRUE,87500 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exam,male,18,NA,asian,2,227,FALSE,NA,FALSE,FALSE,7.5,13,NA,NA,NA,TRUE,40000 +75932,both interview and exam,male,41,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,100000 +75933,both interview and exam,female,53,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +75934,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,7500 +75935,both interview and exam,male,4,NA,mexican american,1,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +75936,both interview and exam,female,35,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,never_married,no,FALSE,12500 +75937,both interview and exam,male,77,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +75938,both interview and exam,female,33,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +75939,both interview and exam,male,13,NA,black,1,163,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +75940,both interview and exam,male,4,NA,white,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75941,both interview and exam,male,8,NA,white,2,98,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +75942,both interview and exam,male,78,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +75943,both interview and exam,male,2,NA,mexican american,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,2500 +75944,both interview and exam,male,16,NA,asian,1,202,NA,NA,FALSE,TRUE,12.5,10,NA,NA,NA,TRUE,100000 +75945,both interview and exam,male,60,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,married,NA,TRUE,60000 +75946,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +75947,both interview and exam,female,13,NA,black,1,159,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +75948,both interview and exam,female,5,NA,mexican american,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75949,both interview and exam,female,40,NA,mexican 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exam,female,29,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,4,married,no,TRUE,100000 +75959,both interview and exam,female,0,11,white,1,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75960,both interview and exam,male,76,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +75961,both interview and exam,male,10,NA,mexican american,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +75962,both interview and exam,male,64,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,40000 +75963,both interview and exam,female,6,NA,mexican american,1,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,50000 +75964,both interview and exam,male,71,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75965,both interview and exam,female,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,12500 +75966,both interview and exam,female,37,NA,white,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,never_married,no,TRUE,70000 +75967,both interview and exam,female,7,NA,black,1,88,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +75968,interview only,male,2,24,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75969,both interview and exam,male,69,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,divorced,NA,TRUE,60000 +75970,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +75971,both interview and exam,male,12,NA,black,1,150,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +75972,both interview and exam,female,5,NA,mexican american,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75973,both interview and exam,male,65,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75974,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +75975,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,30000 +75976,both interview and exam,male,67,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,22500 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interview and exam,male,61,NA,black,2,NA,FALSE,NA,FALSE,FALSE,35,NA,3,living_with_partner,NA,TRUE,NA +75997,both interview and exam,female,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +75998,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +75999,both interview and exam,male,19,NA,asian,2,238,FALSE,NA,FALSE,FALSE,3,14,NA,NA,NA,TRUE,7500 +76000,both interview and exam,female,0,2,other hispanic,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76001,both interview and exam,male,16,NA,black,2,204,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +76002,both interview and exam,female,0,5,mexican american,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76003,both interview and exam,female,10,NA,white,2,129,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +76004,both interview and exam,female,58,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,2500 +76005,both interview and exam,female,14,NA,mexican 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exam,male,67,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76024,both interview and exam,female,40,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +76025,both interview and exam,male,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +76026,both interview and exam,female,9,NA,white,2,114,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +76027,both interview and exam,female,5,NA,asian,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +76028,both interview and exam,female,57,NA,black,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,never_married,NA,TRUE,22500 +76029,both interview and exam,male,3,NA,asian,2,46,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76030,both interview and exam,male,32,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76031,both interview and exam,male,4,NA,white,2,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76032,both interview and exam,male,18,NA,mexican 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exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +76042,both interview and exam,female,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,40000 +76043,both interview and exam,female,64,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +76044,both interview and exam,male,11,NA,mexican american,1,140,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,17500 +76045,both interview and exam,female,12,NA,mexican american,2,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +76046,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +76047,both interview and exam,male,9,NA,white,2,114,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +76048,both interview and exam,male,49,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +76049,both interview and exam,male,54,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,60000 +76050,both interview and exam,male,7,NA,black,2,88,NA,NA,FALSE,FALSE,7.5,1,NA,NA,NA,TRUE,12500 +76051,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,NA +76052,both interview and exam,female,10,NA,mexican american,1,121,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,22500 +76053,both interview and exam,female,5,NA,other hispanic,1,66,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,TRUE,100000 +76054,both interview and exam,female,22,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,no,TRUE,17500 +76055,both interview and exam,female,18,NA,black,1,224,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,7500 +76056,both interview and exam,male,17,NA,black,1,204,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,7500 +76057,both interview and exam,male,18,NA,white,1,221,FALSE,NA,FALSE,TRUE,12.5,13,NA,NA,NA,TRUE,40000 +76058,both interview and exam,female,0,10,other hispanic,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +76059,both interview and exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,70000 +76060,both interview and exam,female,32,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76061,both interview and exam,female,10,NA,black,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +76062,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,40000 +76063,both interview and exam,female,0,3,asian,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +76064,both interview and exam,male,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,70000 +76065,both interview and exam,male,1,21,asian,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76066,both interview and exam,male,17,NA,other hispanic,1,216,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +76067,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +76068,both interview and exam,female,13,NA,black,1,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +76069,both interview and exam,male,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76070,interview only,male,15,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +76071,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76072,both interview and exam,male,73,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,1,married,NA,TRUE,12500 +76073,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +76074,both interview and exam,male,70,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,60000 +76075,both interview and exam,male,35,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +76076,both interview and exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,22500 +76077,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +76078,both interview and exam,male,48,NA,other hispanic,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76079,both interview and exam,female,19,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,22500 +76080,both interview and exam,female,6,NA,mexican american,1,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,22500 +76081,both interview and exam,male,35,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76082,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76083,both interview and exam,male,11,NA,white,2,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +76084,both interview and exam,male,48,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76085,both interview and exam,male,2,NA,other hispanic,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76086,both interview and exam,male,18,NA,white,2,224,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +76087,both interview and exam,male,55,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,FALSE,100000 +76088,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76089,both interview and exam,female,17,NA,white,1,214,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,22500 +76090,both interview and exam,male,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +76091,both interview and exam,female,66,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,100000 +76092,both interview and exam,female,74,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,NA +76093,both interview and exam,female,11,NA,white,2,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +76094,both interview and exam,male,18,NA,other hispanic,1,219,FALSE,NA,FALSE,FALSE,0.5,9,NA,NA,NA,FALSE,22500 +76095,both interview and exam,female,41,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,no,FALSE,NA +76096,both interview and exam,male,37,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76097,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76098,both interview and exam,male,5,NA,other,2,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76099,both interview and exam,female,14,NA,other,2,176,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +76100,both interview and exam,female,6,NA,white,1,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +76101,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,2500 +76102,both interview and exam,male,16,NA,other,2,194,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +76103,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76104,both interview and exam,female,45,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +76105,both interview and exam,male,7,NA,other hispanic,2,96,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,2500 +76106,both interview and exam,male,39,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +76107,both interview and exam,female,59,NA,other,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,22500 +76108,both interview and exam,male,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,100000 +76109,both interview and exam,male,36,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +76110,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +76111,both interview and exam,male,2,NA,black,1,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76112,both interview and exam,male,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76113,interview only,female,5,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76114,both interview and exam,male,18,NA,white,1,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +76115,both interview and exam,female,15,NA,asian,2,192,NA,NA,FALSE,FALSE,0.5,9,NA,NA,NA,TRUE,40000 +76116,both interview and exam,male,68,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +76117,both interview and exam,female,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +76118,both interview and exam,female,60,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,never_married,NA,TRUE,40000 +76119,both interview and exam,male,49,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +76120,both interview and exam,male,40,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +76121,both interview and exam,male,11,NA,black,1,140,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +76122,both interview and exam,female,0,8,mexican american,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +76123,both interview and exam,male,0,4,other hispanic,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +76124,both interview and exam,male,0,9,white,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76125,both interview and exam,male,12,NA,white,1,146,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +76126,both interview and exam,female,27,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,12500 +76127,both interview and exam,male,67,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +76128,both interview and exam,female,74,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,2500 +76129,both interview and exam,female,41,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,never_married,no,TRUE,87500 +76130,both interview and exam,female,4,NA,mexican american,1,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +76131,both interview and exam,female,0,7,white,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76132,both interview and exam,female,18,NA,other hispanic,1,218,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +76133,both interview and exam,female,47,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,never_married,NA,TRUE,87500 +76134,both interview and exam,male,58,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +76135,both interview and exam,male,16,NA,black,1,200,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +76136,both interview and exam,female,53,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,NA,FALSE,50000 +76137,both interview and exam,male,56,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +76138,both interview and exam,female,39,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +76139,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +76140,both interview and exam,female,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,30000 +76141,interview only,female,40,NA,white,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,unable to ascertain,TRUE,NA +76142,interview only,male,2,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76143,both interview and exam,female,1,16,mexican american,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +76144,both interview and exam,male,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +76145,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +76146,both interview and exam,female,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +76147,both interview and exam,male,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,NA +76148,both interview and exam,female,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,30000 +76149,both interview and exam,female,68,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,70000 +76150,both interview and exam,female,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,7500 +76151,both interview and exam,male,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,7500 +76152,both interview and exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76153,both interview and exam,male,16,NA,other hispanic,2,201,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,7500 +76154,both interview and exam,female,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,50000 +76155,both interview and exam,male,10,NA,mexican american,1,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +76156,both interview and exam,male,61,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,separated,NA,TRUE,87500 +76157,interview only,female,50,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +76158,both interview and exam,female,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +76159,both interview and exam,male,75,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,30000 +76160,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,yes,TRUE,30000 +76161,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +76162,both interview and exam,female,10,NA,other hispanic,2,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +76163,interview only,female,10,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +76164,both interview and exam,female,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +76165,both interview and exam,female,7,NA,mexican american,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,40000 +76166,interview only,female,8,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +76167,both interview and exam,female,42,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,no,TRUE,NA +76168,both interview and exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,22500 +76169,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,50000 +76170,both interview and exam,female,55,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,divorced,NA,TRUE,100000 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exam,male,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,2500 +76181,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +76182,both interview and exam,male,3,NA,white,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76183,both interview and exam,female,17,NA,white,2,216,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,60000 +76184,both interview and exam,male,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +76185,both interview and exam,female,3,NA,asian,2,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76186,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,married,NA,TRUE,NA +76187,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76188,both interview and exam,female,74,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,divorced,NA,TRUE,12500 +76189,both interview and exam,female,15,NA,mexican american,2,181,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,22500 +76190,both interview and exam,male,48,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +76191,both interview and exam,female,18,NA,mexican american,1,225,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,FALSE,17500 +76192,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +76193,both interview and exam,female,39,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,no,TRUE,12500 +76194,both interview and exam,male,0,6,black,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +76195,both interview and exam,male,18,NA,other,1,217,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +76196,both interview and exam,male,3,NA,other hispanic,2,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +76197,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,2500 +76198,both interview and exam,female,11,NA,white,2,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 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exam,male,51,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76209,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76210,both interview and exam,female,17,NA,mexican american,2,207,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +76211,both interview and exam,male,17,NA,mexican american,1,212,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +76212,both interview and exam,female,34,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,no,TRUE,60000 +76213,both interview and exam,male,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +76214,both interview and exam,female,18,NA,mexican american,2,218,FALSE,NA,FALSE,FALSE,12.5,11,NA,NA,NA,TRUE,40000 +76215,both interview and exam,female,43,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +76216,both interview and exam,male,13,NA,white,2,167,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +76217,both interview and exam,female,53,NA,mexican 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exam,female,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,30000 +76389,interview only,male,1,19,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +76390,both interview and exam,male,23,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,never_married,NA,TRUE,7500 +76391,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +76392,interview only,male,10,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,NA +76393,both interview and exam,female,8,NA,black,2,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,60000 +76394,both interview and exam,female,12,NA,mexican american,2,146,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,30000 +76395,both interview and exam,male,71,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +76396,both interview and exam,male,2,NA,mexican american,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76397,both interview and exam,male,69,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +76398,both interview and exam,female,15,NA,black,1,184,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +76399,interview only,male,51,NA,other hispanic,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +76400,both interview and exam,male,61,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,NA,FALSE,87500 +76401,both interview and exam,female,18,NA,asian,2,221,FALSE,NA,FALSE,FALSE,3,11,NA,NA,NA,TRUE,30000 +76402,both interview and exam,female,80,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,7500 +76403,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,2500 +76404,both interview and exam,female,68,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,NA +76405,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,87500 +76406,both interview and exam,male,36,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,30000 +76407,interview only,female,41,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,unable to ascertain,TRUE,NA +76408,both interview and exam,male,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +76409,both interview and exam,female,20,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,12500 +76410,both interview and exam,male,3,NA,mexican american,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +76411,both interview and exam,female,63,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,FALSE,17500 +76412,both interview and exam,female,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,NA,never_married,no,TRUE,87500 +76413,both interview and exam,female,66,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,divorced,NA,TRUE,12500 +76414,both interview and exam,male,6,NA,mexican american,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,17500 +76415,both interview and exam,male,25,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,22500 +76416,both interview and exam,male,6,NA,mexican american,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +76417,both interview and exam,male,4,NA,black,1,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76418,both interview and exam,male,40,NA,black,1,NA,TRUE,TRUE,FALSE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76419,both interview and exam,male,7,NA,black,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +76420,both interview and exam,female,2,NA,white,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76421,both interview and exam,female,0,3,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76422,both interview and exam,male,69,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +76423,both interview and exam,female,74,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +76424,both interview and exam,male,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +76425,both interview and exam,male,29,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,87500 +76426,both interview and exam,female,3,NA,black,1,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76427,both interview and exam,male,37,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,50000 +76428,interview only,male,6,NA,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +76429,both interview and exam,male,63,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,NA +76430,interview only,male,1,17,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76431,both interview and exam,male,13,NA,mexican american,2,166,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +76432,both interview and exam,male,18,NA,white,1,220,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +76433,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +76434,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,NA +76435,both interview and exam,female,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76436,both interview and exam,male,78,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +76437,both interview and exam,male,64,NA,other hispanic,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +76438,interview only,female,59,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +76439,both interview and exam,male,28,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,30000 +76440,both interview and exam,female,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +76441,both interview and exam,female,7,NA,mexican american,1,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +76442,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +76443,both interview and exam,male,63,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,7500 +76444,both interview and exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76445,both interview and exam,male,5,NA,other,2,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +76446,both interview and exam,female,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,30000 +76447,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +76448,interview only,male,15,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,17500 +76449,both interview and exam,male,0,1,mexican american,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76450,both interview and exam,male,6,NA,white,2,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +76451,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +76452,both interview and exam,male,2,NA,white,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76453,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76454,both interview and exam,male,16,NA,asian,1,195,NA,NA,FALSE,FALSE,12.5,8,NA,NA,NA,TRUE,100000 +76455,both interview and exam,female,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +76456,both interview and exam,male,7,NA,white,2,87,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +76457,both interview and exam,female,4,NA,white,1,54,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,100000 +76458,both interview and exam,male,17,NA,black,1,216,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +76459,both interview and exam,male,33,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +76460,interview only,female,2,NA,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76461,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +76462,both interview and exam,female,0,0,mexican american,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76463,both interview and exam,male,6,NA,white,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +76464,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76465,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +76466,both interview and exam,female,39,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,30000 +76467,both interview and exam,female,5,NA,black,1,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76468,both interview and exam,male,73,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,70000 +76469,both interview and exam,male,72,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +76470,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,NA +76471,both interview and exam,female,2,NA,other,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +76472,both interview and exam,female,52,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +76473,both interview and exam,male,4,NA,mexican american,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +76474,both interview and exam,female,17,NA,asian,2,205,FALSE,NA,FALSE,TRUE,3,11,NA,NA,NA,TRUE,NA +76475,interview only,female,72,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +76476,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,50000 +76477,both interview and exam,female,73,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,separated,NA,FALSE,50000 +76478,both interview and exam,male,4,NA,other,2,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76479,both interview and exam,male,14,NA,white,2,176,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +76480,both interview and exam,female,24,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +76481,both interview and exam,female,67,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,TRUE,100000 +76482,both interview and exam,female,42,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +76483,both interview and exam,male,12,NA,mexican american,2,147,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +76484,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,40000 +76485,both interview and exam,female,12,NA,mexican american,2,155,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,12500 +76486,both interview and exam,female,24,NA,black,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,never_married,no,TRUE,30000 +76487,both interview and exam,female,23,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,never_married,no,TRUE,30000 +76488,both interview and exam,male,41,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,NA,FALSE,22500 +76489,both interview and exam,male,39,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,70000 +76490,both interview and exam,female,68,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +76491,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,yes,TRUE,40000 +76492,interview only,female,55,NA,white,NA,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,100000 +76493,both interview and exam,male,38,NA,black,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,living_with_partner,NA,TRUE,NA +76494,both interview and exam,male,29,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,divorced,NA,TRUE,22500 +76495,both interview and exam,male,3,NA,asian,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76496,both interview and exam,female,23,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,separated,no,FALSE,7500 +76497,both interview and exam,female,7,NA,mexican american,1,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +76498,both interview and exam,male,6,NA,asian,2,81,NA,NA,FALSE,FALSE,7.5,1,NA,NA,NA,TRUE,40000 +76499,both interview and exam,female,7,NA,black,1,95,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +76500,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +76501,both interview and exam,female,9,NA,other hispanic,2,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,40000 +76502,both interview and exam,male,10,NA,asian,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,NA +76503,both interview and exam,female,15,NA,other,2,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +76504,both interview and exam,male,3,NA,asian,2,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76505,both interview and exam,male,14,NA,black,2,169,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,22500 +76506,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +76507,both interview and exam,female,2,NA,black,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76508,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +76509,both interview and exam,male,24,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,NA +76510,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,12500 +76511,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +76512,both interview and exam,male,13,NA,other hispanic,1,161,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,22500 +76513,both interview and exam,male,15,NA,mexican american,2,186,NA,NA,FALSE,FALSE,12.5,9,NA,NA,NA,FALSE,NA +76514,both interview and exam,female,26,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,no,TRUE,60000 +76515,both interview and exam,female,72,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,1,never_married,NA,FALSE,12500 +76516,interview only,female,2,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76517,interview only,female,11,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,2500 +76518,both interview and exam,male,47,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +76519,both interview and exam,male,17,NA,black,1,209,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,2500 +76520,both interview and exam,male,9,NA,mexican american,1,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,60000 +76521,both interview and exam,female,14,NA,other hispanic,2,180,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,70000 +76522,both interview and exam,female,13,NA,other hispanic,2,167,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,2500 +76523,both interview and exam,female,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,yes,TRUE,NA +76524,both interview and exam,male,18,NA,other hispanic,2,219,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +76525,both interview and exam,female,17,NA,asian,2,213,FALSE,NA,FALSE,FALSE,7.5,11,NA,NA,NA,TRUE,40000 +76526,both interview and exam,male,7,NA,black,1,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +76527,both interview and exam,male,68,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 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exam,male,15,NA,mexican american,1,187,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,7500 +76538,both interview and exam,female,1,23,other hispanic,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76539,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76540,both interview and exam,male,69,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +76541,both interview and exam,male,26,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,2,married,NA,TRUE,30000 +76542,both interview and exam,female,64,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +76543,both interview and exam,male,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +76544,both interview and exam,male,10,NA,mexican american,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,NA +76545,both interview and exam,female,2,NA,black,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +76546,both interview and exam,female,7,NA,black,2,95,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +76547,both interview and exam,male,16,NA,asian,2,197,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +76548,both interview and exam,male,62,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +76549,both interview and exam,male,74,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,7500 +76550,both interview and exam,male,70,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,30000 +76551,both interview and exam,female,56,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,100000 +76552,both interview and exam,female,31,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,yes,TRUE,17500 +76553,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +76554,both interview and exam,female,10,NA,other,2,123,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +76555,both interview and exam,female,2,NA,white,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +76556,both interview and exam,male,45,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,FALSE,60000 +76557,both interview and exam,male,54,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,NA,FALSE,22500 +76558,both interview and exam,female,64,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,87500 +76559,both interview and exam,female,15,NA,white,2,184,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +76560,both interview and exam,male,57,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,50000 +76561,both interview and exam,male,61,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +76562,both interview and exam,female,2,NA,other hispanic,2,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +76563,both interview and exam,female,16,NA,other,2,204,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +76564,both interview and exam,female,2,NA,other hispanic,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +76565,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,87500 +76566,both interview and exam,female,4,NA,mexican american,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +76567,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +76568,both interview and exam,female,64,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,70000 +76569,both interview and exam,male,45,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,17500 +76570,both interview and exam,male,3,NA,black,2,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76571,both interview and exam,male,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,87500 +76572,both interview and exam,female,6,NA,white,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,70000 +76573,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,87500 +76574,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +76575,both interview and exam,female,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76576,both interview and exam,female,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,87500 +76577,both interview and exam,female,23,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,30000 +76578,both interview and exam,male,43,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,living_with_partner,NA,FALSE,50000 +76579,both interview and exam,female,16,NA,mexican american,2,193,NA,NA,FALSE,FALSE,12.5,8,NA,NA,NA,FALSE,12500 +76580,both interview and exam,female,71,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,40000 +76581,both interview and exam,female,13,NA,white,1,161,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,70000 +76582,both interview and exam,male,3,NA,black,2,46,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +76583,both interview and exam,male,15,NA,black,1,192,NA,NA,FALSE,FALSE,7.5,9,NA,NA,NA,TRUE,22500 +76584,both interview and exam,female,49,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76585,both interview and exam,female,6,NA,black,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,60000 +76586,both interview and exam,female,45,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,7500 +76587,both interview and exam,male,62,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,100000 +76588,both interview and exam,female,13,NA,mexican american,2,165,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,22500 +76589,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +76590,both interview and exam,female,67,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,50000 +76591,both interview and exam,female,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +76592,both interview and exam,male,5,NA,mexican american,1,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76593,both interview and exam,male,76,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,widowed,NA,TRUE,7500 +76594,both interview and exam,male,10,NA,white,2,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +76595,both interview and exam,female,11,NA,asian,1,143,NA,NA,FALSE,FALSE,3,6,NA,NA,NA,TRUE,7500 +76596,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +76597,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +76598,both interview and exam,male,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,4,divorced,NA,TRUE,60000 +76599,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +76600,both interview and exam,female,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,yes,TRUE,2500 +76601,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +76602,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +76603,both interview and exam,male,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,2500 +76604,both interview and exam,male,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,22500 +76605,both interview and exam,male,12,NA,other hispanic,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,17500 +76606,both interview and exam,female,57,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,NA,TRUE,100000 +76607,both interview and exam,male,2,NA,other hispanic,1,31,NA,NA,FALSE,TRUE,0.5,NA,NA,NA,NA,TRUE,7500 +76608,both interview and exam,female,38,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,12500 +76609,both interview and exam,female,21,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,never_married,no,TRUE,17500 +76610,both interview and exam,male,7,NA,black,2,90,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +76611,both interview and exam,male,16,NA,mexican american,1,201,NA,NA,FALSE,FALSE,12.5,10,NA,NA,NA,TRUE,22500 +76612,both interview and exam,male,62,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,FALSE,100000 +76613,both interview and exam,male,32,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,100000 +76614,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +76615,both interview and exam,male,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +76616,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +76617,both interview and exam,male,18,NA,black,1,219,FALSE,NA,FALSE,FALSE,12.5,12,NA,NA,NA,TRUE,22500 +76618,both interview and exam,male,9,NA,black,1,121,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +76619,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,12500 +76620,both interview and exam,female,3,NA,asian,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76621,both interview and exam,female,1,21,other,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76622,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +76623,both interview and exam,male,41,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +76624,both interview and exam,male,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +76625,both interview and exam,male,10,NA,black,1,128,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +76626,both interview and exam,female,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76627,both interview and exam,female,76,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +76628,both interview and exam,male,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76629,both interview and exam,male,25,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +76630,both interview and exam,female,39,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,divorced,no,TRUE,7500 +76631,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,17500 +76632,both interview and exam,male,49,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,TRUE,70000 +76633,both interview and exam,male,48,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +76634,both interview and exam,female,43,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,no,TRUE,40000 +76635,both interview and exam,male,59,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +76636,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,yes,TRUE,30000 +76637,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +76638,both interview and exam,female,63,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +76639,both interview and exam,male,43,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,2500 +76640,both interview and exam,female,6,NA,white,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +76641,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,22500 +76642,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,no,TRUE,60000 +76643,both interview and exam,female,41,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,87500 +76644,both interview and exam,male,10,NA,mexican american,1,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +76645,both interview and exam,male,52,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +76646,both interview and exam,female,1,23,mexican american,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +76647,both interview and exam,female,8,NA,white,2,107,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +76648,both interview and exam,female,74,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,NA +76649,both interview and exam,male,59,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,NA,TRUE,12500 +76650,both interview and exam,female,8,NA,white,1,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +76651,both interview and exam,female,0,8,asian,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76652,both interview and exam,male,3,NA,other hispanic,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76653,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +76654,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +76655,both interview and exam,female,64,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,divorced,NA,FALSE,7500 +76656,both interview and exam,female,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,40000 +76657,both interview and exam,female,49,NA,black,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,never_married,NA,TRUE,NA +76658,both interview and exam,female,9,NA,white,2,111,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +76659,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,NA +76660,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,FALSE,FALSE,45,NA,3,widowed,NA,TRUE,12500 +76661,both interview and exam,female,9,NA,black,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +76662,both interview and exam,male,12,NA,mexican american,2,156,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +76663,both interview and exam,male,71,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,NA +76664,both interview and exam,female,0,6,white,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76665,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76666,both interview and exam,female,65,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,widowed,NA,TRUE,12500 +76667,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76668,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76669,both interview and exam,male,63,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,never_married,NA,FALSE,60000 +76670,both interview and exam,male,49,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,70000 +76671,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76672,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +76673,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76674,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,living_with_partner,no,TRUE,22500 +76675,both interview and exam,male,48,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +76676,both interview and exam,male,41,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,50000 +76677,both interview and exam,female,18,NA,mexican american,1,220,FALSE,NA,FALSE,FALSE,12.5,14,NA,NA,NA,TRUE,30000 +76678,both interview and exam,male,10,NA,white,1,123,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +76679,both interview and exam,female,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +76680,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76681,both interview and exam,male,1,16,black,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76682,both interview and exam,female,13,NA,black,1,167,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +76683,both interview and exam,male,15,NA,other hispanic,1,192,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +76684,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +76685,both interview and exam,female,4,NA,mexican american,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76686,both interview and exam,male,34,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,married,NA,FALSE,NA +76687,both interview and exam,male,79,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,22500 +76688,both interview and exam,male,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,40000 +76689,interview only,female,69,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +76690,both interview and exam,female,14,NA,black,2,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,NA +76691,both interview and exam,male,38,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,4,never_married,NA,TRUE,NA +76692,both interview and exam,female,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +76693,both interview and exam,male,7,NA,black,1,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +76694,both interview and exam,male,8,NA,white,2,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +76695,interview only,female,80,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +76696,both interview and exam,female,7,NA,other,1,92,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,2500 +76697,both interview and exam,male,24,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,30000 +76698,both interview and exam,female,66,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,50000 +76699,both interview and exam,female,16,NA,black,1,201,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +76700,both interview and exam,male,53,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,FALSE,17500 +76701,both interview and exam,female,3,NA,black,2,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76702,both interview and exam,male,62,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +76703,both interview and exam,male,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +76704,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +76705,both interview and exam,female,50,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +76706,both interview and exam,male,60,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +76707,both interview and exam,female,46,NA,black,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,never_married,NA,TRUE,22500 +76708,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,2500 +76709,both interview and exam,male,74,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +76710,both interview and exam,male,1,13,asian,2,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76711,both interview and exam,male,11,NA,black,2,134,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,60000 +76712,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76713,both interview and exam,female,2,NA,other,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76714,both interview and exam,female,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +76715,both interview and exam,male,74,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +76716,both interview and exam,female,18,NA,white,2,221,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +76717,both interview and exam,female,0,5,black,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76718,both interview and exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +76719,both interview and exam,female,39,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,50000 +76720,both interview and exam,female,15,NA,mexican american,2,191,NA,NA,FALSE,FALSE,3,10,NA,NA,NA,FALSE,30000 +76721,both interview and exam,female,9,NA,white,2,117,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +76722,both interview and exam,male,73,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76723,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +76724,both interview and exam,female,13,NA,asian,2,165,NA,NA,FALSE,FALSE,7.5,8,NA,NA,NA,TRUE,30000 +76725,both interview and exam,male,14,NA,white,2,170,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +76726,both interview and exam,female,0,0,asian,1,0,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76727,both interview and exam,female,7,NA,mexican american,1,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,60000 +76728,both interview and exam,male,8,NA,black,1,104,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +76729,both interview and exam,female,0,7,asian,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76730,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +76731,both interview and exam,male,41,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,FALSE,70000 +76732,both interview and exam,female,19,NA,mexican american,2,231,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,87500 +76733,both interview and exam,male,77,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +76734,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +76735,both interview and exam,female,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +76736,both interview and exam,female,30,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,yes,TRUE,100000 +76737,both interview and exam,female,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +76738,both interview and exam,female,63,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,divorced,NA,TRUE,100000 +76739,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,17500 +76740,both interview and exam,female,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76741,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +76742,both interview and exam,male,40,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +76743,both interview and exam,male,2,NA,white,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76744,both interview and exam,female,5,NA,asian,1,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +76745,both interview and exam,male,70,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,widowed,NA,FALSE,87500 +76746,both interview and exam,male,55,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,25,NA,5,never_married,NA,TRUE,NA +76747,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +76748,both interview and exam,male,1,13,white,1,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76749,both interview and exam,male,7,NA,mexican american,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,30000 +76750,both interview and exam,female,9,NA,mexican american,1,116,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,17500 +76751,both interview and exam,female,36,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,unable to ascertain,FALSE,70000 +76752,both interview and exam,male,4,NA,other hispanic,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76753,both interview and exam,male,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,70000 +76754,both interview and exam,male,76,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76755,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +76756,both interview and exam,male,44,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,TRUE,17500 +76757,both interview and exam,male,79,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,separated,NA,TRUE,40000 +76758,both interview and exam,male,15,NA,other,2,187,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +76759,both interview and exam,male,0,1,black,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76760,both interview and exam,female,16,NA,mexican american,1,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +76761,both interview and exam,female,0,10,mexican american,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +76762,both interview and exam,female,3,NA,mexican american,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76763,both interview and exam,female,12,NA,mexican american,1,146,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,60000 +76764,both interview and exam,female,61,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +76765,both interview and exam,female,13,NA,black,2,166,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +76766,both interview and exam,female,11,NA,black,1,135,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 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exam,male,5,NA,asian,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76777,both interview and exam,male,29,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +76778,both interview and exam,male,18,NA,mexican american,2,218,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +76779,both interview and exam,female,71,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,widowed,NA,FALSE,22500 +76780,both interview and exam,female,7,NA,white,2,92,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +76781,both interview and exam,male,1,22,white,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76782,interview only,female,2,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +76783,both interview and exam,female,9,NA,black,1,113,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +76784,both interview and exam,female,11,NA,white,2,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +76785,both interview and exam,male,22,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +76786,both interview and exam,female,9,NA,white,1,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +76787,both interview and exam,male,11,NA,mexican american,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +76788,both interview and exam,male,4,NA,mexican american,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +76789,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76790,both interview and exam,female,6,NA,black,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +76791,both interview and exam,female,15,NA,mexican american,1,189,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +76792,both interview and exam,female,38,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,40000 +76793,both interview and exam,female,45,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +76794,both interview and exam,female,12,NA,black,2,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +76795,both interview and exam,male,11,NA,black,1,144,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +76796,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +76797,both interview and exam,female,60,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,12500 +76798,both interview and exam,female,5,NA,other hispanic,2,62,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +76799,both interview and exam,male,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +76800,both interview and exam,male,18,NA,white,2,225,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,12500 +76801,both interview and exam,male,0,4,other hispanic,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76802,both interview and exam,male,57,NA,black,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,TRUE,17500 +76803,both interview and exam,male,12,NA,mexican american,2,146,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +76804,both interview and exam,male,10,NA,white,1,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +76805,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +76806,both interview and exam,female,14,NA,white,1,178,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +76807,both interview and exam,female,72,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +76808,interview only,female,4,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76809,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +76810,both interview and exam,female,54,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,2,married,NA,FALSE,NA +76811,both interview and exam,female,27,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,never_married,no,TRUE,50000 +76812,both interview and exam,female,4,NA,asian,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76813,interview only,female,31,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,unable to ascertain,TRUE,22500 +76814,both interview and exam,male,62,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76815,both interview and exam,male,44,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,NA +76816,interview only,female,30,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,unable to ascertain,TRUE,7500 +76817,both interview and exam,male,54,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +76818,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +76819,both interview and exam,female,54,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,35,NA,5,married,NA,TRUE,100000 +76820,both interview and exam,male,46,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +76821,both interview and exam,male,18,NA,mexican american,1,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +76822,both interview and exam,female,16,NA,mexican american,2,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,30000 +76823,both interview and exam,female,6,NA,other,2,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +76824,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +76825,both interview and exam,male,28,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,30000 +76826,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +76827,both interview and exam,female,72,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,widowed,NA,FALSE,12500 +76828,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,no,TRUE,22500 +76829,both interview and exam,male,12,NA,black,2,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,22500 +76830,both interview and exam,male,10,NA,white,2,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +76831,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,40000 +76832,both interview and exam,female,5,NA,white,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76833,both interview and exam,female,7,NA,mexican american,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,70000 +76834,both interview and exam,female,16,NA,mexican american,2,194,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,30000 +76835,both interview and exam,female,40,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,12500 +76836,interview only,female,3,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +76837,both interview and exam,male,40,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,TRUE,100000 +76838,both interview and exam,female,2,NA,asian,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76839,both interview and exam,female,6,NA,mexican american,2,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,22500 +76840,both interview and exam,female,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +76841,both interview and exam,male,6,NA,white,1,79,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 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exam,female,73,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,1,living_with_partner,NA,FALSE,NA +76852,both interview and exam,male,0,2,white,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +76853,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76854,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76855,both interview and exam,female,0,8,mexican american,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +76856,both interview and exam,male,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +76857,both interview and exam,male,13,NA,white,2,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,70000 +76858,both interview and exam,female,8,NA,other,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +76859,both interview and exam,male,32,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,100000 +76860,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,40000 +76861,both interview and exam,female,3,NA,mexican american,1,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +76862,interview only,female,9,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +76863,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +76864,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,22500 +76865,both interview and exam,male,18,NA,black,1,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +76866,both interview and exam,male,11,NA,black,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +76867,both interview and exam,male,51,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +76868,both interview and exam,male,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +76869,both interview and exam,female,16,NA,mexican american,2,205,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,12500 +76870,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +76871,both interview and exam,female,70,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +76872,both interview and exam,male,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +76873,both interview and exam,female,5,NA,black,1,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76874,both interview and exam,male,10,NA,asian,1,121,NA,NA,FALSE,FALSE,7.5,3,NA,NA,NA,TRUE,7500 +76875,both interview and exam,male,4,NA,white,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76876,both interview and exam,male,1,18,mexican american,1,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76877,both interview and exam,female,52,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +76878,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +76879,both interview and exam,female,17,NA,black,1,215,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +76880,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +76881,both interview and exam,female,11,NA,other,2,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,NA +76882,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +76883,both interview and exam,male,7,NA,other hispanic,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +76884,both interview and exam,female,55,NA,black,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +76885,both interview and exam,male,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76886,both interview and exam,male,54,NA,other hispanic,2,NA,TRUE,FALSE,FALSE,TRUE,35,NA,2,married,NA,TRUE,NA +76887,interview only,male,11,NA,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +76888,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 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hispanic,1,235,FALSE,NA,FALSE,FALSE,17.5,14,NA,NA,NA,TRUE,50000 +76899,both interview and exam,male,60,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +76900,both interview and exam,female,25,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,living_with_partner,no,FALSE,22500 +76901,both interview and exam,female,52,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +76902,both interview and exam,male,56,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76903,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +76904,both interview and exam,female,17,NA,white,2,205,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,100000 +76905,both interview and exam,female,33,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,no,TRUE,7500 +76906,both interview and exam,female,10,NA,black,1,131,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +76907,both interview and exam,male,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +76908,both interview and exam,female,22,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,NA +76909,both interview and exam,female,18,NA,white,1,222,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +76910,both interview and exam,female,10,NA,black,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +76911,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +76912,both interview and exam,male,74,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,17500 +76913,both interview and exam,female,0,3,black,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76914,both interview and exam,female,34,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,unable to ascertain,TRUE,NA +76915,both interview and exam,male,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76916,both interview and exam,male,15,NA,mexican american,1,182,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +76917,both interview and exam,male,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +76918,both interview and exam,male,17,NA,white,2,216,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +76919,both interview and exam,male,37,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76920,both interview and exam,female,23,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,17500 +76921,both interview and exam,male,64,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,55,NA,1,never_married,NA,FALSE,12500 +76922,both interview and exam,male,1,15,white,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76923,interview only,male,33,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +76924,both interview and exam,male,19,NA,black,2,233,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +76925,both interview and exam,female,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,7500 +76926,both interview and exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +76927,both interview and exam,female,11,NA,black,1,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +76928,both interview and exam,male,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +76929,both interview and exam,male,19,NA,other,2,237,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +76930,both interview and exam,male,5,NA,mexican american,2,63,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,2500 +76931,both interview and exam,male,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +76932,both interview and exam,male,73,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +76933,both interview and exam,female,4,NA,other,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76934,both interview and exam,male,41,NA,other,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76935,both interview and exam,male,43,NA,other 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exam,male,39,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +76964,both interview and exam,male,16,NA,white,1,194,NA,NA,FALSE,TRUE,7.5,9,NA,NA,NA,TRUE,100000 +76965,both interview and exam,male,35,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +76966,both interview and exam,female,48,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76967,both interview and exam,female,3,NA,white,1,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +76968,both interview and exam,male,34,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,30000 +76969,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +76970,both interview and exam,female,19,NA,asian,2,229,FALSE,NA,FALSE,TRUE,17.5,13,NA,NA,NA,TRUE,60000 +76971,both interview and exam,male,6,NA,asian,1,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +76972,both interview and exam,male,57,NA,mexican 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exam,female,6,NA,black,1,72,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +76982,both interview and exam,female,8,NA,asian,2,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +76983,both interview and exam,male,11,NA,other,1,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +76984,both interview and exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +76985,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76986,both interview and exam,male,2,NA,mexican american,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76987,both interview and exam,female,33,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,3,living_with_partner,no,FALSE,17500 +76988,both interview and exam,male,67,NA,asian,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76989,both interview and exam,female,9,NA,black,1,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +76990,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +76991,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,married,NA,TRUE,30000 +76992,both interview and exam,male,67,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,100000 +76993,both interview and exam,female,16,NA,black,2,204,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +76994,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,yes,TRUE,NA +76995,both interview and exam,female,15,NA,black,1,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +76996,both interview and exam,male,36,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,never_married,NA,FALSE,NA +76997,both interview and exam,male,18,NA,other hispanic,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +76998,both interview and exam,female,14,NA,mexican american,1,174,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,NA +76999,both interview and exam,male,19,NA,white,1,235,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +77000,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +77001,both interview and exam,female,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +77002,both interview and exam,male,16,NA,mexican american,1,196,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +77003,both interview and exam,male,42,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,NA +77004,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,100000 +77005,both interview and exam,male,4,NA,black,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77006,both interview and exam,female,34,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,30000 +77007,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,40000 +77008,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +77009,both interview and exam,male,10,NA,white,1,130,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77010,both interview and exam,male,44,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +77011,both interview and exam,female,63,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,60000 +77012,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77013,both interview and exam,male,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +77014,both interview and exam,female,52,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,50000 +77015,interview only,female,67,NA,other hispanic,NA,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,FALSE,100000 +77016,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +77017,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +77018,interview only,female,4,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77019,both interview and exam,female,28,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +77020,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +77021,both interview and exam,male,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77022,both interview and exam,male,54,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +77023,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,60000 +77024,both interview and exam,male,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +77025,both interview and exam,male,55,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,TRUE,60000 +77026,both interview and exam,female,14,NA,mexican american,2,172,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +77027,both interview and exam,male,0,4,black,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +77028,both interview and exam,male,54,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,7500 +77029,both interview and exam,male,48,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,never_married,NA,FALSE,7500 +77030,both interview and exam,male,70,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +77031,both interview and exam,male,6,NA,black,1,81,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +77032,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77033,both interview and exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +77034,both interview and exam,male,1,23,black,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77035,both interview and exam,male,64,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +77036,both interview and exam,male,12,NA,mexican american,2,153,NA,NA,FALSE,FALSE,3,6,NA,NA,NA,FALSE,22500 +77037,both interview and exam,female,9,NA,mexican american,1,113,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +77038,both interview and exam,male,9,NA,other,2,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +77039,both interview and exam,female,16,NA,mexican american,2,199,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +77040,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +77041,both interview and exam,male,73,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +77042,both interview and exam,male,6,NA,mexican american,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +77043,both interview and exam,female,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +77044,both interview and exam,male,2,NA,black,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +77045,both interview and exam,male,30,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +77046,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +77047,both interview and exam,male,28,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +77048,both interview and exam,female,1,19,white,2,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77049,both interview and exam,female,66,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,widowed,NA,TRUE,50000 +77050,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +77051,both interview and exam,female,21,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,living_with_partner,no,TRUE,12500 +77052,both interview and exam,female,12,NA,other,2,146,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,17500 +77053,both interview and exam,male,8,NA,white,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +77054,both interview and exam,male,54,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,100000 +77055,both interview and exam,female,45,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +77056,interview only,male,16,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +77057,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +77058,both interview and exam,female,17,NA,mexican american,2,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +77059,both interview and exam,female,6,NA,black,1,83,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +77060,both interview and exam,female,72,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +77061,both interview and exam,female,3,NA,mexican american,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +77062,both interview and exam,male,1,15,white,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77063,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +77064,both interview and exam,male,2,NA,white,2,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +77065,both interview and exam,male,6,NA,white,2,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,22500 +77066,both interview and exam,female,62,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,separated,NA,FALSE,NA +77067,both interview and exam,female,67,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +77068,both interview and exam,male,15,NA,mexican american,1,185,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,40000 +77069,interview only,female,0,2,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77070,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +77071,both interview and exam,male,14,NA,asian,2,181,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,70000 +77072,both interview and exam,male,70,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +77073,both interview and exam,female,67,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +77074,both interview and exam,male,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,40000 +77075,both interview and exam,female,42,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +77076,both interview and exam,male,35,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77077,both interview and exam,male,50,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,NA +77078,both interview and exam,female,4,NA,black,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77079,both interview and exam,male,2,NA,black,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +77080,both interview and exam,female,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,12500 +77081,both interview and exam,male,67,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +77082,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +77083,both interview and exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,50000 +77084,both interview and exam,female,3,NA,mexican american,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +77085,both interview and exam,female,0,2,asian,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77086,both interview and exam,female,12,NA,mexican american,2,156,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,7500 +77087,both interview and exam,male,10,NA,black,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +77088,both interview and exam,female,7,NA,mexican american,2,95,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +77089,both interview and exam,male,4,NA,black,1,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77090,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,unable to ascertain,TRUE,50000 +77091,both interview and exam,female,31,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,NA +77092,both interview and exam,male,3,NA,white,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77093,both interview and exam,female,2,NA,white,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77094,both interview and exam,female,57,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,60000 +77095,both interview and exam,male,46,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77096,both interview and exam,female,75,NA,white,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,widowed,NA,TRUE,12500 +77097,both interview and exam,male,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +77098,both interview and exam,male,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +77099,both interview and exam,male,14,NA,mexican american,1,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,17500 +77100,both interview and exam,male,63,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,2,married,NA,FALSE,70000 +77101,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77102,both interview and exam,male,12,NA,black,1,150,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +77103,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,FALSE,50000 +77104,both interview and exam,female,13,NA,black,2,162,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +77105,both interview and exam,male,76,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +77106,both interview and exam,male,6,NA,black,1,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +77107,both interview and exam,female,7,NA,white,1,93,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +77108,both interview and exam,male,19,NA,black,1,231,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,30000 +77109,both interview and exam,male,38,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,FALSE,40000 +77110,both interview and exam,male,3,NA,mexican american,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77111,both interview and exam,male,61,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +77112,both interview and exam,female,27,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,no,FALSE,30000 +77113,both interview and exam,female,58,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,100000 +77114,both interview and exam,female,73,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +77115,both interview and exam,female,5,NA,white,2,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77116,both interview and exam,male,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,30000 +77117,both interview and exam,female,11,NA,other hispanic,2,143,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +77118,both interview and exam,female,1,21,white,2,21,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77119,both interview and exam,male,15,NA,other hispanic,1,188,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,12500 +77120,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +77121,both interview and exam,female,42,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,87500 +77122,both interview and exam,female,14,NA,other hispanic,2,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,40000 +77123,both interview and exam,female,50,NA,other,1,NA,FALSE,NA,FALSE,TRUE,55,NA,4,divorced,NA,TRUE,50000 +77124,both interview and exam,female,9,NA,other hispanic,2,111,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +77125,both interview and exam,male,6,NA,mexican american,1,81,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,22500 +77126,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +77127,both interview and exam,female,41,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,2500 +77128,both interview and exam,male,19,NA,white,1,236,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +77129,both interview and exam,female,10,NA,black,1,132,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +77130,both interview and exam,male,16,NA,other hispanic,1,199,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +77131,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,100000 +77132,both interview and exam,male,25,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77133,both interview and exam,female,2,NA,black,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77134,both interview and exam,male,7,NA,black,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,17500 +77135,both interview and exam,male,10,NA,white,1,124,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +77136,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +77137,both interview and exam,female,5,NA,other,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77138,both interview and exam,female,15,NA,black,1,181,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +77139,both interview and exam,female,71,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,2,widowed,NA,TRUE,12500 +77140,both interview and exam,male,58,NA,mexican american,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +77141,both interview and exam,female,42,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,separated,no,FALSE,30000 +77142,both interview and exam,male,68,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +77143,both interview and exam,female,2,NA,black,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77144,both interview and exam,female,27,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +77145,interview only,male,43,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +77146,both interview and exam,male,2,NA,white,2,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77147,both interview and exam,male,45,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,married,NA,TRUE,60000 +77148,both interview and exam,male,4,NA,other hispanic,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77149,both interview and exam,male,11,NA,black,2,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +77150,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77151,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +77152,both interview and exam,male,10,NA,black,1,131,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +77153,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +77154,both interview and exam,female,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +77155,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +77156,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +77157,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77158,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +77159,both interview and exam,female,38,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,no,TRUE,50000 +77160,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +77161,interview only,female,28,NA,other hispanic,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,unable to ascertain,TRUE,87500 +77162,both interview and exam,female,72,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +77163,both interview and exam,female,66,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,widowed,NA,FALSE,40000 +77164,both interview and exam,female,56,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,TRUE,22500 +77165,both interview and exam,male,10,NA,other hispanic,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77166,both interview and exam,female,2,NA,white,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77167,both interview and exam,female,40,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,no,TRUE,7500 +77168,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +77169,both interview and exam,male,10,NA,black,2,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,17500 +77170,both interview and exam,female,58,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,FALSE,87500 +77171,both interview and exam,female,69,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,widowed,NA,TRUE,30000 +77172,both interview and exam,male,42,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,NA +77173,both interview and exam,female,16,NA,asian,2,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +77174,both interview and exam,male,22,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +77175,both interview and exam,female,4,NA,other hispanic,2,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +77176,both interview and exam,female,41,NA,mexican 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exam,male,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +77215,both interview and exam,male,38,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,40000 +77216,both interview and exam,male,1,19,other hispanic,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +77217,both interview and exam,female,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,70000 +77218,both interview and exam,female,5,NA,mexican american,1,69,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,TRUE,87500 +77219,both interview and exam,female,3,NA,black,1,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77220,both interview and exam,female,25,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +77221,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,17500 +77222,both interview and exam,male,7,NA,white,2,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +77223,both interview and exam,female,65,NA,other 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interview and exam,female,1,12,other,2,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77234,both interview and exam,female,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,30000 +77235,both interview and exam,female,32,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,no,TRUE,40000 +77236,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +77237,both interview and exam,female,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,2500 +77238,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,NA +77239,both interview and exam,female,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,unable to ascertain,TRUE,7500 +77240,both interview and exam,male,35,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,40000 +77241,both interview and exam,male,27,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,50000 +77242,both interview and exam,male,7,NA,black,1,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +77243,both interview and exam,female,7,NA,other,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +77244,both interview and exam,male,42,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,100000 +77245,both interview and exam,female,73,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,40000 +77246,both interview and exam,male,68,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,17500 +77247,both interview and exam,female,67,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,NA,FALSE,12500 +77248,both interview and exam,female,22,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,living_with_partner,no,TRUE,60000 +77249,both interview and exam,male,16,NA,other hispanic,2,196,NA,NA,FALSE,FALSE,3,10,NA,NA,NA,TRUE,50000 +77250,both interview and exam,male,78,NA,mexican american,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +77251,both interview and exam,female,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +77252,both interview and exam,female,12,NA,black,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +77253,both interview and exam,female,3,NA,other hispanic,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77254,both interview and exam,male,36,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +77255,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,30000 +77256,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,30000 +77257,both interview and exam,male,61,NA,other hispanic,1,NA,TRUE,TRUE,FALSE,TRUE,55,NA,3,married,NA,TRUE,87500 +77258,both interview and exam,female,4,NA,black,1,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +77259,both interview and exam,male,24,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +77260,interview only,male,53,NA,other hispanic,NA,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,never_married,NA,FALSE,40000 +77261,both interview and exam,female,0,6,white,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77262,both interview and exam,female,19,NA,mexican american,1,236,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,60000 +77263,both interview and exam,female,44,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,no,FALSE,NA +77264,both interview and exam,female,15,NA,black,2,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,60000 +77265,both interview and exam,female,41,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +77266,both interview and exam,male,4,NA,mexican american,1,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77267,interview only,female,17,NA,asian,NA,NA,FALSE,NA,FALSE,FALSE,7.5,11,NA,NA,NA,TRUE,100000 +77268,both interview and exam,female,9,NA,mexican american,2,110,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +77269,both interview and exam,male,19,NA,other,1,239,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +77270,both interview and exam,male,11,NA,black,1,137,NA,NA,FALSE,FALSE,3,5,NA,NA,NA,TRUE,87500 +77271,both interview and exam,female,16,NA,white,2,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,2500 +77272,both interview and exam,male,3,NA,black,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77273,both interview and exam,female,5,NA,black,2,72,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77274,both interview and exam,male,8,NA,black,1,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +77275,both interview and exam,male,60,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,3,married,NA,FALSE,87500 +77276,both interview and exam,male,2,NA,white,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77277,both interview and exam,male,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +77278,both interview and exam,male,4,NA,white,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77279,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +77280,both interview and exam,male,42,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +77281,both interview and exam,female,13,NA,white,1,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,2500 +77282,both interview and exam,male,20,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,3,NA,2,never_married,NA,TRUE,NA +77283,interview only,female,46,NA,asian,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77284,both interview and exam,male,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +77285,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,12500 +77286,both interview and exam,female,4,NA,mexican american,1,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,2500 +77287,both interview and exam,female,53,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77288,both interview and exam,female,0,11,black,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +77289,both interview and exam,male,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +77290,both interview and exam,female,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,no,TRUE,17500 +77291,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,no,TRUE,7500 +77292,both interview and exam,female,8,NA,mexican american,2,109,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,12500 +77293,both interview and exam,male,5,NA,mexican american,2,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +77294,both interview and exam,female,12,NA,mexican american,1,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,17500 +77295,both interview and exam,male,30,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,70000 +77296,both interview and exam,female,0,6,white,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +77297,both interview and exam,female,5,NA,black,1,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77298,both interview and exam,male,63,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,30000 +77299,both interview and exam,female,67,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,60000 +77300,both interview and exam,male,24,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +77301,both interview and exam,female,7,NA,mexican american,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +77302,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77303,both interview and exam,female,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +77304,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,yes,TRUE,7500 +77305,both interview and exam,female,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,7500 +77306,both interview and exam,male,73,NA,other 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exam,female,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,40000 +77316,both interview and exam,female,16,NA,other hispanic,1,201,NA,NA,FALSE,TRUE,7.5,14,NA,NA,NA,TRUE,7500 +77317,interview only,female,77,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,17500 +77318,both interview and exam,male,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +77319,both interview and exam,male,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +77320,both interview and exam,female,35,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,17500 +77321,interview only,male,7,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +77322,both interview and exam,male,24,NA,black,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,living_with_partner,NA,TRUE,60000 +77323,both interview and exam,female,28,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,87500 +77324,both interview and exam,female,4,NA,black,1,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +77325,both interview and exam,male,16,NA,other hispanic,2,198,NA,NA,FALSE,FALSE,12.5,9,NA,NA,NA,TRUE,50000 +77326,both interview and exam,male,12,NA,other,2,150,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +77327,both interview and exam,male,2,NA,mexican american,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77328,both interview and exam,female,43,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,no,TRUE,100000 +77329,both interview and exam,male,4,NA,white,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77330,interview only,male,11,NA,asian,NA,NA,NA,NA,FALSE,FALSE,7.5,4,NA,NA,NA,TRUE,22500 +77331,both interview and exam,male,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77332,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +77333,both interview and exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77334,both 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exam,male,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77476,both interview and exam,male,9,NA,black,2,112,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +77477,both interview and exam,male,59,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,NA,TRUE,100000 +77478,both interview and exam,male,4,NA,other hispanic,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +77479,both interview and exam,male,4,NA,black,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +77480,both interview and exam,male,11,NA,black,1,139,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +77481,both interview and exam,female,54,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,22500 +77482,both interview and exam,female,5,NA,mexican american,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77483,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +77484,both interview and exam,male,40,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,7500 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exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +77495,both interview and exam,male,10,NA,other,2,131,NA,NA,FALSE,TRUE,7.5,5,NA,NA,NA,TRUE,17500 +77496,both interview and exam,male,1,22,other hispanic,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +77497,both interview and exam,male,9,NA,black,2,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +77498,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77499,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77500,both interview and exam,female,3,NA,mexican american,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77501,both interview and exam,male,5,NA,other,2,73,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77502,both interview and exam,female,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77503,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,2500 +77504,both interview and exam,female,14,NA,asian,2,176,NA,NA,FALSE,TRUE,12.5,8,NA,NA,NA,TRUE,100000 +77505,both interview and exam,female,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +77506,both interview and exam,male,0,9,white,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77507,both interview and exam,male,43,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,87500 +77508,both interview and exam,female,18,NA,other hispanic,2,219,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,100000 +77509,both interview and exam,male,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +77510,both interview and exam,female,4,NA,black,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +77511,both interview and exam,male,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,50000 +77512,both interview and exam,male,1,20,mexican american,1,21,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +77513,both interview and exam,male,34,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,separated,NA,TRUE,100000 +77514,both interview and exam,male,1,16,other,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77515,both interview and exam,female,66,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +77516,both interview and exam,male,16,NA,black,2,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,50000 +77517,both interview and exam,female,15,NA,white,1,187,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +77518,both interview and exam,male,16,NA,white,1,204,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,50000 +77519,both interview and exam,female,16,NA,mexican american,2,197,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,7500 +77520,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +77521,both interview and exam,male,41,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77522,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,40000 +77523,interview only,female,72,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +77524,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +77525,interview only,male,1,18,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77526,both interview and exam,female,0,5,mexican american,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77527,both interview and exam,male,47,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,NA,FALSE,NA +77528,both interview and exam,male,40,NA,asian,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77529,both interview and exam,male,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77530,both interview and exam,female,2,NA,black,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77531,both interview and exam,male,5,NA,black,1,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77532,both interview and exam,male,15,NA,other,2,187,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +77533,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +77534,both interview and exam,female,15,NA,white,1,186,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +77535,both interview and exam,male,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,40000 +77536,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,divorced,NA,TRUE,40000 +77537,both interview and exam,male,8,NA,black,1,103,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +77538,both interview and exam,male,23,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +77539,both interview and exam,female,38,NA,black,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,no,TRUE,100000 +77540,both interview and exam,male,43,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +77541,both interview and exam,male,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77542,both interview and exam,male,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,22500 +77543,both interview and exam,male,43,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +77544,both interview and exam,male,0,8,mexican american,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +77545,both interview and exam,male,1,17,other hispanic,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77546,both interview and exam,male,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +77547,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +77548,both interview and exam,male,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +77549,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +77550,both interview and exam,male,26,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +77551,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +77552,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +77553,both interview and exam,female,2,NA,other hispanic,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +77554,both interview and exam,female,5,NA,mexican american,1,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77555,both interview and exam,male,9,NA,mexican american,2,120,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +77556,both interview and exam,male,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +77557,both interview and exam,female,8,NA,other hispanic,1,106,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +77558,both interview and exam,female,2,NA,white,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77559,both interview and exam,female,0,5,mexican american,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +77560,both interview and exam,female,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,87500 +77561,both interview and exam,female,7,NA,mexican american,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,40000 +77562,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,40000 +77563,both interview and exam,male,36,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +77564,both interview and exam,male,1,23,mexican american,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77565,both interview and exam,female,2,NA,black,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77566,both interview and exam,female,0,2,mexican american,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +77567,interview only,female,1,19,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +77568,both interview and exam,male,3,NA,black,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77569,both interview and exam,female,48,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,FALSE,7500 +77570,both interview and exam,female,9,NA,mexican american,2,116,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,2500 +77571,both interview and exam,female,18,NA,other,2,220,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +77572,both interview and exam,male,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77573,both interview and exam,male,9,NA,mexican american,2,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,30000 +77574,both interview and exam,male,10,NA,other hispanic,2,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +77575,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +77576,both interview and exam,female,0,4,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77577,both interview and exam,female,33,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +77578,both interview and exam,male,45,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,married,NA,FALSE,40000 +77579,both interview and exam,male,15,NA,other hispanic,1,190,NA,NA,FALSE,TRUE,12.5,9,NA,NA,NA,TRUE,22500 +77580,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +77581,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +77582,both interview and exam,male,10,NA,asian,1,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77583,both interview and exam,female,7,NA,mexican american,1,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,17500 +77584,both interview and exam,female,35,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,50000 +77585,both interview and exam,male,36,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,living_with_partner,NA,FALSE,40000 +77586,both interview and exam,male,65,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77587,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +77588,both interview and exam,female,6,NA,other,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +77589,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +77590,both interview and exam,male,9,NA,other hispanic,1,109,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,17500 +77591,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77592,both interview and exam,female,52,NA,black,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,divorced,NA,TRUE,40000 +77593,both interview and exam,female,3,NA,other,2,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +77594,both interview and exam,male,3,NA,other hispanic,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +77595,both interview and exam,female,13,NA,black,1,168,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +77596,both interview and exam,male,49,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,FALSE,NA +77597,both interview and exam,male,58,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,2,married,NA,FALSE,30000 +77598,both interview and exam,male,79,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,17500 +77599,both interview and exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +77600,both interview and exam,female,58,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,divorced,NA,TRUE,40000 +77601,both interview and exam,male,42,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77602,both interview and exam,male,14,NA,white,2,171,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +77603,both interview and exam,female,56,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,70000 +77604,both interview and exam,male,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +77605,both interview and exam,male,55,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,50000 +77606,both interview and exam,male,14,NA,white,1,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +77607,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,no,TRUE,40000 +77608,both interview and exam,male,7,NA,mexican american,2,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +77609,both interview and exam,female,61,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,60000 +77610,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +77611,both interview and exam,female,35,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,never_married,no,TRUE,100000 +77612,both interview and exam,male,22,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77613,both interview and exam,male,19,NA,other hispanic,2,234,FALSE,NA,FALSE,FALSE,3,9,NA,NA,NA,FALSE,22500 +77614,both interview and exam,female,9,NA,other,2,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +77615,both interview and exam,female,19,NA,other hispanic,2,230,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +77616,both interview and exam,female,35,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +77617,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,2500 +77618,both interview and exam,female,25,NA,other,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,never_married,no,TRUE,12500 +77619,both interview and exam,male,0,9,asian,1,9,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,70000 +77620,both interview and exam,female,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +77621,both interview and exam,female,68,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +77622,both interview and exam,female,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +77623,both interview and exam,female,79,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,60000 +77624,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +77625,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,30000 +77626,both interview and exam,female,18,NA,mexican american,2,224,FALSE,NA,FALSE,FALSE,7.5,12,NA,NA,NA,FALSE,30000 +77627,both interview and exam,female,3,NA,black,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77628,both interview and exam,male,7,NA,mexican american,2,95,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +77629,both interview and exam,male,17,NA,black,2,204,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +77630,both interview and exam,male,45,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77631,both interview and exam,female,59,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,divorced,NA,TRUE,30000 +77632,both interview and exam,male,39,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +77633,interview only,female,11,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +77634,both interview and exam,female,67,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,5,divorced,NA,FALSE,7500 +77635,both interview and exam,male,6,NA,other,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +77636,both interview and exam,male,6,NA,other hispanic,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +77637,both interview and exam,female,6,NA,other,1,76,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +77638,both interview and exam,female,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +77639,both interview and exam,female,28,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,never_married,no,FALSE,40000 +77640,both interview and exam,male,46,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +77641,both interview and exam,male,16,NA,asian,2,200,NA,NA,FALSE,FALSE,7.5,10,NA,NA,NA,TRUE,NA +77642,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,17500 +77643,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,no,FALSE,30000 +77644,both interview and exam,male,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77645,both interview and exam,female,52,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,TRUE,87500 +77646,both interview and exam,male,18,NA,mexican american,1,221,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,100000 +77647,both interview and exam,male,68,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,55,NA,4,married,NA,TRUE,100000 +77648,both interview and exam,male,0,7,other hispanic,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77649,both interview and exam,male,7,NA,white,1,90,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +77650,both interview and exam,female,0,3,mexican 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exam,male,23,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,2500 +77856,both interview and exam,male,33,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,87500 +77857,both interview and exam,male,10,NA,mexican american,1,126,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +77858,both interview and exam,female,37,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,12500 +77859,both interview and exam,female,0,6,mexican american,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +77860,both interview and exam,male,13,NA,black,1,164,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,17500 +77861,both interview and exam,female,68,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,NA,TRUE,22500 +77862,both interview and exam,male,18,NA,white,2,227,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,87500 +77863,both interview and exam,male,0,4,asian,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77864,both interview and 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interview and exam,male,6,NA,other hispanic,2,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +77902,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,NA +77903,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +77904,both interview and exam,male,6,NA,other hispanic,2,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,50000 +77905,both interview and exam,female,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,7500 +77906,both interview and exam,male,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,7500 +77907,both interview and exam,female,26,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,60000 +77908,both interview and exam,female,17,NA,mexican american,1,211,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +77909,both interview and exam,female,78,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +77910,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +77911,both interview and exam,male,8,NA,white,2,102,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +77912,both interview and exam,female,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,no,TRUE,22500 +77913,both interview and exam,female,11,NA,white,2,134,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,22500 +77914,both interview and exam,male,13,NA,asian,2,157,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +77915,both interview and exam,female,57,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,40000 +77916,both interview and exam,female,2,NA,mexican american,2,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +77917,both interview and exam,female,68,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,widowed,NA,FALSE,NA +77918,both interview and exam,male,6,NA,other hispanic,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +77919,both interview and exam,female,17,NA,other 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exam,male,15,NA,other hispanic,1,186,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +77930,both interview and exam,male,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +77931,both interview and exam,male,36,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,3,married,NA,TRUE,12500 +77932,both interview and exam,male,28,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +77933,both interview and exam,female,18,NA,white,2,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +77934,both interview and exam,male,12,NA,white,1,152,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +77935,both interview and exam,female,48,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +77936,both interview and exam,female,43,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,NA +77937,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,12500 +77938,both interview and exam,male,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,50000 +77939,both interview and exam,female,55,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +77940,both interview and exam,male,16,NA,mexican american,1,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +77941,both interview and exam,male,50,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,12500 +77942,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,87500 +77943,both interview and exam,male,38,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +77944,both interview and exam,male,4,NA,other hispanic,2,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +77945,interview only,female,69,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,2500 +77946,interview only,female,9,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,60000 +77947,both interview and exam,male,12,NA,black,1,150,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,2500 +77948,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +77949,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +77950,both interview and exam,male,80,NA,mexican american,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77951,both interview and exam,male,1,17,mexican american,1,18,NA,NA,FALSE,TRUE,0.5,NA,NA,NA,NA,FALSE,70000 +77952,both interview and exam,male,27,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,87500 +77953,both interview and exam,female,33,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,no,TRUE,NA +77954,both interview and exam,female,44,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,no,TRUE,87500 +77955,both interview and exam,male,4,NA,black,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77956,both interview and exam,male,5,NA,black,2,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77957,both interview and exam,female,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,70000 +77958,both interview and exam,male,1,23,black,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77959,both interview and exam,male,44,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77960,both interview and exam,female,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,60000 +77961,both interview and exam,female,11,NA,white,2,134,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77962,both interview and exam,female,8,NA,black,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +77963,both interview and exam,male,32,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77964,both interview and exam,female,3,NA,black,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +77965,both interview and exam,male,47,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 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exam,male,11,NA,asian,1,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77976,both interview and exam,male,73,NA,other,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,12500 +77977,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +77978,both interview and exam,female,3,NA,other hispanic,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +77979,both interview and exam,female,69,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,35,NA,4,married,NA,TRUE,2500 +77980,both interview and exam,male,1,17,other hispanic,2,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77981,both interview and exam,male,1,13,other hispanic,2,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77982,both interview and exam,female,16,NA,black,1,204,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +77983,both interview and exam,male,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +77984,both interview and exam,male,10,NA,white,1,121,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +77985,both interview and exam,female,24,NA,black,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,never_married,no,TRUE,30000 +77986,both interview and exam,male,2,NA,black,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77987,both interview and exam,female,17,NA,other hispanic,2,214,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +77988,both interview and exam,male,17,NA,other hispanic,1,205,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,60000 +77989,both interview and exam,male,53,NA,other hispanic,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +77990,both interview and exam,male,66,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,22500 +77991,both interview and exam,female,30,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,no,TRUE,40000 +77992,both interview and exam,male,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +77993,both interview and exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +77994,both interview and exam,male,64,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +77995,both interview and exam,male,20,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77996,both interview and exam,male,1,16,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77997,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +77998,both interview and exam,male,8,NA,white,2,106,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +77999,both interview and exam,male,51,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +78000,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +78001,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,60000 +78002,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,unable to ascertain,TRUE,100000 +78003,both interview and exam,female,14,NA,other hispanic,2,168,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,NA +78004,both interview and exam,male,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +78005,both interview and exam,female,15,NA,mexican american,1,181,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,17500 +78006,both interview and exam,male,2,NA,black,1,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78007,both interview and exam,female,80,NA,black,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,17500 +78008,both interview and exam,female,33,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,NA +78009,both interview and exam,male,80,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +78010,both interview and exam,male,73,NA,other,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +78011,both interview and exam,male,0,2,black,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78012,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +78013,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,60000 +78014,both interview and exam,female,6,NA,other hispanic,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +78015,both interview and exam,male,47,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,separated,NA,FALSE,7500 +78016,both interview and exam,male,12,NA,white,2,152,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +78017,both interview and exam,male,7,NA,mexican american,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,22500 +78018,both interview and exam,female,47,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,separated,NA,FALSE,22500 +78019,both interview and exam,male,65,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,40000 +78020,both interview and exam,female,42,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,4,married,no,TRUE,40000 +78021,both interview and exam,female,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +78022,both interview and exam,female,2,NA,asian,2,31,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,TRUE,12500 +78023,both interview and exam,male,0,0,mexican american,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78024,both interview and exam,male,33,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +78025,both interview and exam,male,15,NA,white,1,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +78026,both interview and exam,male,4,NA,black,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78027,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +78028,both interview and exam,male,64,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +78029,both interview and exam,male,1,12,other 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exam,male,43,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,100000 +78049,both interview and exam,female,7,NA,asian,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +78050,both interview and exam,male,17,NA,mexican american,2,211,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +78051,both interview and exam,male,40,NA,other,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +78052,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78053,both interview and exam,male,4,NA,black,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78054,both interview and exam,female,23,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,living_with_partner,no,FALSE,NA +78055,both interview and exam,male,9,NA,white,2,120,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +78056,both interview and exam,male,75,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +78057,both interview and exam,male,14,NA,black,1,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +78058,interview only,male,50,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +78059,both interview and exam,male,4,NA,black,1,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78060,both interview and exam,female,2,NA,white,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78061,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78062,both interview and exam,female,0,4,black,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +78063,both interview and exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,22500 +78064,both interview and exam,female,12,NA,black,1,154,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,22500 +78065,both interview and exam,female,13,NA,mexican american,1,164,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,22500 +78066,both interview and exam,male,2,NA,mexican american,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +78067,both interview and exam,female,10,NA,white,2,129,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +78068,both interview and exam,male,19,NA,white,2,235,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +78069,both interview and exam,female,3,NA,black,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78070,both interview and exam,male,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +78071,both interview and exam,female,6,NA,mexican american,2,85,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,17500 +78072,both interview and exam,male,77,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,22500 +78073,both interview and exam,male,14,NA,white,2,176,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +78074,both interview and exam,male,51,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,divorced,NA,FALSE,NA +78075,both interview and exam,male,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +78076,both interview and exam,female,56,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +78077,both interview and exam,male,10,NA,mexican american,1,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,30000 +78078,both interview and exam,male,19,NA,mexican american,1,231,FALSE,NA,FALSE,FALSE,0.5,13,NA,NA,NA,FALSE,22500 +78079,both interview and exam,female,40,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,50000 +78080,both interview and exam,male,58,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,never_married,NA,TRUE,87500 +78081,both interview and exam,female,63,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,87500 +78082,both interview and exam,male,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +78083,both interview and exam,male,53,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +78084,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,12500 +78085,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,never_married,NA,TRUE,100000 +78086,both interview and exam,male,80,NA,black,1,NA,FALSE,NA,FALSE,TRUE,55,NA,1,married,NA,TRUE,17500 +78087,both interview and exam,male,16,NA,black,2,201,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +78088,both interview and exam,male,66,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +78089,both interview and exam,male,62,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,never_married,NA,FALSE,50000 +78090,both interview and exam,female,15,NA,white,1,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +78091,both interview and exam,female,18,NA,other,1,225,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,7500 +78092,both interview and exam,female,6,NA,asian,1,72,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +78093,both interview and exam,male,29,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +78094,both interview and exam,female,39,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +78095,both interview and exam,female,51,NA,other 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exam,female,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,2500 +78115,both interview and exam,male,11,NA,white,2,143,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +78116,both interview and exam,female,7,NA,other hispanic,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,50000 +78117,both interview and exam,male,8,NA,other hispanic,1,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +78118,both interview and exam,female,11,NA,other hispanic,1,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +78119,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,87500 +78120,both interview and exam,male,9,NA,asian,2,119,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +78121,both interview and exam,male,22,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +78122,both interview and exam,female,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +78123,both interview and exam,male,0,8,black,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 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exam,male,5,NA,white,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78385,both interview and exam,male,13,NA,mexican american,2,169,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +78386,both interview and exam,male,44,NA,asian,2,NA,TRUE,FALSE,FALSE,TRUE,25,NA,5,married,NA,TRUE,70000 +78387,both interview and exam,male,10,NA,asian,1,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +78388,both interview and exam,female,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,17500 +78389,both interview and exam,male,16,NA,asian,1,192,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,12500 +78390,both interview and exam,male,4,NA,asian,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +78391,both interview and exam,male,55,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,TRUE,87500 +78392,both interview and exam,female,67,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +78393,both interview and 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exam,female,30,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +78440,both interview and exam,male,57,NA,white,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,4,never_married,NA,TRUE,2500 +78441,both interview and exam,male,27,NA,other,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +78442,both interview and exam,female,59,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,17500 +78443,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78444,both interview and exam,female,52,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +78445,both interview and exam,male,63,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +78446,both interview and exam,female,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,yes,TRUE,100000 +78447,both interview and exam,female,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,40000 +78448,both interview and exam,male,3,NA,other 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exam,male,15,NA,mexican american,1,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,2500 +78459,interview only,male,25,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +78460,both interview and exam,male,32,NA,black,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,TRUE,87500 +78461,both interview and exam,female,16,NA,other hispanic,2,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +78462,both interview and exam,male,58,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,17500 +78463,interview only,male,51,NA,black,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,TRUE,NA +78464,both interview and exam,female,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +78465,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,2500 +78466,both interview and exam,female,5,NA,other,2,70,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,2500 +78467,both interview and exam,female,69,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +78468,both interview and exam,female,30,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,no,TRUE,30000 +78469,both interview and exam,male,2,24,other hispanic,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78470,both interview and exam,female,12,NA,mexican american,1,155,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +78471,both interview and exam,male,6,NA,white,2,84,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +78472,both interview and exam,male,11,NA,mexican american,1,137,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +78473,both interview and exam,male,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +78474,both interview and exam,male,45,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,never_married,NA,FALSE,40000 +78475,both interview and exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +78476,both interview and exam,male,9,NA,asian,1,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +78477,both interview and exam,female,14,NA,white,2,171,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +78478,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78479,both interview and exam,male,28,NA,white,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,70000 +78480,both interview and exam,female,47,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,60000 +78481,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +78482,both interview and exam,male,5,NA,other hispanic,2,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +78483,both interview and exam,female,15,NA,mexican american,1,188,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,22500 +78484,both interview and exam,female,79,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +78485,both interview and exam,female,8,NA,white,2,102,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +78486,both interview and exam,female,60,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78487,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +78488,both interview and exam,female,0,2,other,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +78489,both interview and exam,female,31,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,no,TRUE,87500 +78490,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +78491,both interview and exam,female,11,NA,black,1,139,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +78492,both interview and exam,female,4,NA,other,2,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +78493,both interview and exam,male,11,NA,white,2,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +78494,both interview and exam,female,0,5,mexican american,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +78495,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,30000 +78496,both interview and exam,female,19,NA,mexican american,1,232,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,17500 +78497,both interview and exam,male,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +78498,both interview and exam,female,78,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +78499,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,30000 +78500,both interview and exam,male,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +78501,both interview and exam,female,19,NA,other,2,229,FALSE,NA,FALSE,FALSE,0.5,9,NA,NA,NA,TRUE,2500 +78502,both interview and exam,female,1,16,mexican american,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78503,both interview and exam,female,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,2,widowed,NA,TRUE,12500 +78504,both interview and exam,female,60,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +78505,interview only,male,0,1,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78506,both interview and exam,male,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +78507,both interview and exam,male,2,24,black,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78508,both interview and exam,male,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +78509,both interview and exam,female,13,NA,mexican american,2,162,NA,NA,FALSE,FALSE,7.5,7,NA,NA,NA,FALSE,17500 +78510,both interview and exam,male,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78511,both interview and exam,male,15,NA,black,2,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +78512,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +78513,both interview and exam,female,2,NA,white,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 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exam,female,60,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,50000 +78524,both interview and exam,female,1,17,white,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +78525,both interview and exam,male,11,NA,other hispanic,1,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +78526,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,never_married,NA,TRUE,87500 +78527,both interview and exam,female,72,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +78528,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,87500 +78529,both interview and exam,female,19,NA,other hispanic,2,234,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,NA +78530,both interview and exam,female,7,NA,black,1,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +78531,both interview and exam,male,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78532,interview only,male,28,NA,mexican 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exam,male,11,NA,asian,1,140,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,70000 +78542,both interview and exam,female,41,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,living_with_partner,no,FALSE,30000 +78543,both interview and exam,female,3,NA,white,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78544,both interview and exam,male,1,23,white,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +78545,both interview and exam,male,1,20,black,1,21,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +78546,both interview and exam,female,10,NA,mexican american,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +78547,both interview and exam,male,7,NA,white,2,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +78548,both interview and exam,female,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,NA +78549,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +78550,interview only,female,2,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78551,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +78552,both interview and exam,female,68,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,7500 +78553,both interview and exam,female,10,NA,white,2,125,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +78554,both interview and exam,male,10,NA,mexican american,2,122,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +78555,both interview and exam,male,5,NA,mexican american,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,60000 +78556,both interview and exam,female,60,NA,white,1,NA,FALSE,NA,FALSE,FALSE,55,NA,3,divorced,NA,TRUE,2500 +78557,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +78558,both interview and exam,female,5,NA,other hispanic,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +78559,both interview and exam,female,11,NA,white,1,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +78560,both interview and exam,male,22,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +78561,both interview and exam,male,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +78562,both interview and exam,male,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +78563,both interview and exam,male,9,NA,asian,2,109,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +78564,both interview and exam,male,8,NA,other hispanic,1,102,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +78565,both interview and exam,male,6,NA,black,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +78566,both interview and exam,male,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +78567,both interview and exam,female,0,3,white,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78568,both interview and exam,female,29,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,30000 +78569,both interview and exam,female,19,NA,white,2,233,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,7500 +78570,both interview and exam,male,0,4,white,1,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78571,both interview and exam,female,0,8,mexican american,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +78572,both interview and exam,male,51,NA,white,2,NA,FALSE,NA,FALSE,TRUE,45,NA,5,widowed,NA,TRUE,40000 +78573,both interview and exam,male,5,NA,mexican american,1,68,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,FALSE,12500 +78574,both interview and exam,female,10,NA,black,2,120,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +78575,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,2500 +78576,both interview and exam,female,15,NA,black,2,182,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +78577,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,NA +78578,both interview and exam,female,11,NA,mexican american,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +78579,both interview and exam,male,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +78580,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +78581,both interview and exam,female,44,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,no,TRUE,50000 +78582,both interview and exam,female,15,NA,white,2,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +78583,both interview and exam,male,54,NA,other hispanic,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +78584,both interview and exam,female,11,NA,white,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +78585,both interview and exam,male,8,NA,black,1,107,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +78586,both interview and exam,female,41,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +78587,both interview and exam,female,57,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,NA,TRUE,60000 +78588,both interview and exam,male,49,NA,other 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interview and exam,male,33,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,3,married,NA,TRUE,NA +78766,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78767,both interview and exam,male,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +78768,both interview and exam,female,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +78769,both interview and exam,male,19,NA,mexican american,2,236,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +78770,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +78771,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +78772,both interview and exam,female,30,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,no,FALSE,2500 +78773,both interview and exam,female,8,NA,other,1,96,NA,NA,FALSE,TRUE,3,1,NA,NA,NA,TRUE,NA +78774,both interview and 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exam,male,0,9,asian,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78915,both interview and exam,male,0,2,white,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78916,both interview and exam,female,60,NA,black,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,70000 +78917,interview only,female,26,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,12500 +78918,both interview and exam,male,67,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,0.5,NA,3,married,NA,TRUE,100000 +78919,both interview and exam,female,47,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78920,both interview and exam,male,20,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,FALSE,30000 +78921,both interview and exam,male,47,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +78922,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +78923,both interview and exam,female,15,NA,white,2,186,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,NA +78924,both interview and exam,female,50,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78925,both interview and exam,female,19,NA,asian,1,229,FALSE,NA,FALSE,FALSE,3,13,NA,NA,NA,TRUE,2500 +78926,both interview and exam,male,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +78927,both interview and exam,male,8,NA,black,2,104,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,50000 +78928,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +78929,both interview and exam,female,71,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,30000 +78930,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +78931,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +78932,both interview and exam,male,13,NA,asian,1,167,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 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exam,female,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,87500 +78943,both interview and exam,male,12,NA,other hispanic,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +78944,both interview and exam,female,56,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +78945,both interview and exam,female,5,NA,black,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +78946,both interview and exam,male,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +78947,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +78948,both interview and exam,female,5,NA,black,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78949,both interview and exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +78950,both interview and exam,female,73,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,7500 +78951,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +78952,both interview and exam,female,44,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,TRUE,100000 +78953,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +78954,interview only,male,34,NA,white,NA,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,TRUE,17500 +78955,both interview and exam,female,6,NA,mexican american,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,7500 +78956,both interview and exam,female,1,18,white,2,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +78957,both interview and exam,male,19,NA,black,2,238,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,12500 +78958,both interview and exam,female,14,NA,other hispanic,2,178,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +78959,both interview and exam,female,39,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,no,TRUE,100000 +78960,both interview and exam,female,3,NA,black,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +78961,both interview and exam,male,6,NA,white,1,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +78962,both interview and exam,female,52,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,100000 +78963,both interview and exam,male,52,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +78964,both interview and exam,male,35,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,TRUE,30000 +78965,both interview and exam,male,6,NA,mexican american,1,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +78966,both interview and exam,female,18,NA,white,1,222,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,30000 +78967,both interview and exam,female,41,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,no,TRUE,100000 +78968,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +78969,both interview and exam,female,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,17500 +78970,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78971,both interview and exam,female,10,NA,black,1,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +78972,both interview and exam,female,4,NA,white,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +78973,both interview and exam,female,27,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,30000 +78974,both interview and exam,male,54,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +78975,both interview and exam,male,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,2500 +78976,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +78977,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,40000 +78978,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +78979,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78980,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,22500 +78981,both interview and exam,female,71,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,55,NA,1,widowed,NA,TRUE,12500 +78982,both interview and exam,female,9,NA,mexican american,2,108,NA,NA,FALSE,FALSE,3,2,NA,NA,NA,FALSE,50000 +78983,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78984,both interview and exam,male,17,NA,white,2,215,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,7500 +78985,both interview and exam,female,5,NA,white,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78986,interview only,female,19,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,12500 +78987,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,NA +78988,both interview and exam,male,2,NA,other,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 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exam,male,8,NA,white,2,98,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +78999,both interview and exam,male,23,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,70000 +79000,both interview and exam,male,36,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,50000 +79001,both interview and exam,male,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,7500 +79002,both interview and exam,female,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,50000 +79003,both interview and exam,female,7,NA,mexican american,2,85,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +79004,both interview and exam,male,2,NA,black,1,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +79005,both interview and exam,male,44,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +79006,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,FALSE,TRUE,55,NA,3,married,NA,TRUE,100000 +79007,both interview and 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exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +79017,both interview and exam,male,61,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,30000 +79018,both interview and exam,female,18,NA,white,2,221,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +79019,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +79020,both interview and exam,male,0,7,white,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +79021,both interview and exam,female,7,NA,black,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +79022,both interview and exam,male,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,2500 +79023,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +79024,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +79025,both interview and exam,female,54,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +79026,both interview and exam,male,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +79027,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +79028,both interview and exam,male,12,NA,mexican american,1,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,30000 +79029,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +79030,both interview and exam,male,4,NA,mexican american,2,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +79031,both interview and exam,male,68,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +79032,both interview and exam,male,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +79033,both interview and exam,male,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,100000 +79034,interview 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exam,female,14,NA,white,1,170,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +79044,both interview and exam,male,31,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,50000 +79045,both interview and exam,female,11,NA,mexican american,1,134,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,NA +79046,both interview and exam,female,0,1,asian,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79047,both interview and exam,female,13,NA,white,1,169,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +79048,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +79049,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,50000 +79050,both interview and exam,female,74,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,3,married,NA,TRUE,87500 +79051,both interview and exam,female,14,NA,other,2,174,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +79052,both interview and exam,male,4,NA,white,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 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exam,male,4,NA,asian,1,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +79063,both interview and exam,female,51,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +79064,both interview and exam,male,48,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,40000 +79065,both interview and exam,female,4,NA,mexican american,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +79066,both interview and exam,male,14,NA,black,1,178,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,7500 +79067,both interview and exam,male,26,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,living_with_partner,NA,FALSE,87500 +79068,both interview and exam,female,36,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,no,TRUE,100000 +79069,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +79070,both interview and exam,male,17,NA,black,2,209,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +79071,interview 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exam,female,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,12500 +79090,both interview and exam,male,7,NA,black,1,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +79091,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,NA +79092,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +79093,both interview and exam,male,4,NA,other hispanic,2,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +79094,both interview and exam,female,14,NA,black,2,177,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +79095,both interview and exam,female,80,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,widowed,NA,TRUE,100000 +79096,both interview and exam,male,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +79097,both interview and exam,female,15,NA,black,2,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,70000 +79098,both interview and exam,male,19,NA,white,2,229,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +79099,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,60000 +79100,both interview and exam,female,28,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +79101,both interview and exam,female,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +79102,both interview and exam,male,3,NA,black,1,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +79103,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,NA,NA,TRUE,NA +79104,both interview and exam,male,5,NA,black,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +79105,both interview and exam,male,15,NA,mexican american,2,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +79106,both interview and exam,male,78,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,7500 +79107,both interview and exam,female,1,15,white,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 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exam,male,9,NA,white,1,109,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,70000 +79118,both interview and exam,male,8,NA,black,1,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +79119,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +79120,both interview and exam,male,11,NA,white,2,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +79121,both interview and exam,female,62,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,30000 +79122,both interview and exam,female,9,NA,other hispanic,1,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +79123,both interview and exam,male,4,NA,mexican american,2,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +79124,both interview and exam,female,3,NA,mexican american,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +79125,both interview and exam,female,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +79126,interview only,male,3,NA,other hispanic,NA,NA,NA,NA,NA,TRUE,NA,NA,NA,NA,NA,TRUE,NA 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american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,NA,FALSE,30000 +79137,both interview and exam,male,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +79138,both interview and exam,female,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +79139,both interview and exam,female,13,NA,mexican american,1,159,NA,NA,FALSE,FALSE,12.5,7,NA,NA,NA,FALSE,30000 +79140,interview only,female,34,NA,other,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,unable to ascertain,TRUE,70000 +79141,both interview and exam,male,7,NA,asian,1,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +79142,both interview and exam,female,49,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +79143,interview only,female,1,15,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79144,interview only,male,39,NA,white,NA,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +79145,both interview and exam,male,2,NA,black,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +79146,both interview and exam,female,26,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,no,TRUE,30000 +79147,both interview and exam,female,38,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,no,TRUE,30000 +79148,both interview and exam,male,33,NA,mexican american,1,NA,FALSE,NA,FALSE,NA,7.5,NA,2,living_with_partner,NA,FALSE,22500 +79149,both interview and exam,female,6,NA,asian,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +79150,both interview and exam,male,10,NA,mexican american,2,130,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +79151,interview only,female,37,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,12500 +79152,both interview and exam,male,53,NA,white,2,NA,TRUE,FALSE,FALSE,TRUE,55,NA,5,married,NA,TRUE,30000 +79153,both interview and exam,female,29,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +79154,both interview and exam,male,71,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,100000 +79155,both interview and exam,female,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +79156,interview only,female,8,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +79157,both interview and exam,male,4,NA,black,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +79158,interview only,male,4,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +79159,interview only,male,62,NA,other hispanic,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,NA,FALSE,22500 +79160,both interview and exam,female,14,NA,white,2,178,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +79161,both interview and exam,female,55,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,NA,FALSE,30000 +79162,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +79163,both interview and exam,male,19,NA,white,2,239,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,2500 +79164,both interview and exam,male,33,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 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exam,female,1,20,asian,2,21,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79175,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +79176,both interview and exam,male,55,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +79177,both interview and exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +79178,both interview and exam,male,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,never_married,NA,TRUE,100000 +79179,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +79180,both interview and exam,female,69,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,widowed,NA,FALSE,50000 +79181,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,separated,no,TRUE,7500 +79182,both interview and exam,male,12,NA,other,1,154,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +79183,both interview and exam,female,4,NA,white,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +79184,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +79185,both interview and exam,male,79,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,22500 +79186,both interview and exam,female,80,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,30000 +79187,both interview and exam,female,52,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +79188,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,NA +79189,both interview and exam,male,74,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +79190,both interview and exam,male,41,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,100000 +79191,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +79192,both interview and exam,female,1,13,mexican 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exam,male,75,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +79202,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +79203,both interview and exam,female,4,NA,asian,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79204,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +79205,both interview and exam,male,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +79206,both interview and exam,male,72,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +79207,both interview and exam,female,25,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +79208,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +79209,both interview and exam,male,6,NA,white,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +79210,both interview and exam,male,25,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +79211,both interview and exam,female,39,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,never_married,no,TRUE,12500 +79212,both interview and exam,female,0,2,other hispanic,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +79213,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,40000 +79214,both interview and exam,female,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +79215,both interview and exam,female,28,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,living_with_partner,yes,TRUE,50000 +79216,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,100000 +79217,both interview and exam,male,33,NA,black,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,4,married,NA,TRUE,100000 +79218,both interview and exam,male,14,NA,black,1,170,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +79219,both interview and 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interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,50000 +79545,both interview and exam,female,33,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,never_married,no,FALSE,17500 +79546,both interview and exam,female,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +79547,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,7500 +79548,interview only,female,62,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +79549,both interview and exam,female,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,50000 +79550,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,yes,TRUE,2500 +79551,both interview and exam,female,1,22,white,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79552,both interview and exam,female,5,NA,mexican american,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +79553,both interview and 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interview and exam,male,12,NA,other hispanic,1,151,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,22500 +79618,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,no,TRUE,2500 +79619,both interview and exam,male,14,NA,white,2,170,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +79620,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +79621,both interview and exam,female,76,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,7500 +79622,both interview and exam,male,5,NA,other,2,72,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +79623,interview only,female,80,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,22500 +79624,interview only,male,2,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79625,both interview and exam,female,16,NA,black,2,193,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +79626,both interview and exam,male,16,NA,white,2,198,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +79627,both interview 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exam,male,14,NA,white,1,169,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +79637,interview only,male,78,NA,other,NA,NA,FALSE,NA,FALSE,FALSE,55,NA,3,divorced,NA,TRUE,40000 +79638,both interview and exam,male,42,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +79639,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +79640,both interview and exam,female,30,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,living_with_partner,no,FALSE,30000 +79641,both interview and exam,male,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +79642,both interview and exam,male,17,NA,mexican american,1,216,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,NA +79643,both interview and exam,male,2,NA,other,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +79644,both interview and exam,male,47,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +79645,both interview and 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exam,male,47,NA,black,1,NA,FALSE,NA,FALSE,FALSE,25,NA,5,divorced,NA,TRUE,60000 +80007,both interview and exam,male,73,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,7500 +80008,both interview and exam,female,67,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,1,widowed,NA,FALSE,NA +80009,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +80010,both interview and exam,male,39,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80011,both interview and exam,female,2,NA,white,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80012,both interview and exam,male,1,19,other,2,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +80013,both interview and exam,female,62,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +80014,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80015,both interview and exam,male,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80016,both interview and exam,male,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,living_with_partner,NA,FALSE,22500 +80017,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +80018,both interview and exam,male,10,NA,other,2,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +80019,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,22500 +80020,both interview and exam,female,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,50000 +80021,both interview and exam,female,16,NA,other,1,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,NA +80022,both interview and exam,male,21,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +80023,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80024,both interview and exam,female,48,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,2,married,NA,TRUE,40000 +80025,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,no,TRUE,22500 +80026,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +80027,both interview and exam,female,32,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,never_married,no,FALSE,70000 +80028,interview only,female,54,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80029,both interview and exam,male,7,NA,white,1,89,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +80030,both interview and exam,male,63,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,35,NA,5,married,NA,TRUE,100000 +80031,both interview and exam,male,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +80032,both interview and exam,male,11,NA,other hispanic,1,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80033,both interview and exam,male,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +80034,both interview and exam,female,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,no,TRUE,40000 +80035,both interview and exam,male,4,NA,white,2,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80036,both interview and exam,female,16,NA,other hispanic,1,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +80037,both interview and exam,male,64,NA,mexican american,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +80038,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,NA +80039,both interview and exam,male,3,NA,asian,2,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80040,both interview and exam,female,70,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,7500 +80041,both interview and exam,female,42,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,TRUE,22500 +80042,both interview and exam,female,10,NA,white,2,121,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,NA +80043,both interview and exam,female,38,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +80044,both interview and exam,male,77,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +80045,both interview and exam,male,3,NA,black,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80046,both interview and exam,female,1,13,mexican american,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +80047,both interview and exam,female,22,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +80048,both interview and exam,male,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +80049,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80050,both interview and exam,male,8,NA,white,1,104,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +80051,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +80052,both interview and exam,female,62,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,never_married,NA,FALSE,NA +80053,both interview and exam,male,16,NA,black,2,198,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +80054,both interview and exam,male,13,NA,other hispanic,1,161,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +80055,both interview and exam,female,44,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,no,FALSE,50000 +80056,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,70000 +80057,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +80058,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,17500 +80059,both interview and exam,female,47,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,22500 +80060,both interview and exam,female,42,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +80061,both interview and exam,female,50,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +80062,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +80063,both interview and exam,male,80,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +80064,both interview and exam,male,32,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,22500 +80065,both interview and exam,male,2,NA,mexican american,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80066,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,87500 +80067,both interview and exam,male,65,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,NA,FALSE,2500 +80068,both interview and exam,female,9,NA,asian,1,120,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +80069,both interview and exam,male,10,NA,black,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +80070,both interview and exam,female,1,17,white,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80071,interview only,female,66,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +80072,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,22500 +80073,both interview and exam,female,57,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,50000 +80074,both interview and exam,female,10,NA,mexican american,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,40000 +80075,both interview and exam,male,32,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +80076,both interview and exam,female,2,NA,other hispanic,1,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +80077,both interview and exam,female,12,NA,white,1,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80078,both interview and exam,male,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,1,widowed,NA,TRUE,12500 +80079,both interview and exam,male,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +80080,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80081,both interview and exam,female,1,17,mexican american,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80082,both interview and exam,female,79,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,50000 +80083,both interview and exam,male,41,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,30000 +80084,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +80085,both interview and exam,male,7,NA,black,2,95,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +80086,both interview and exam,female,0,1,other hispanic,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80087,both interview and exam,female,30,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,100000 +80088,both interview and exam,male,22,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,never_married,NA,TRUE,12500 +80089,both interview and exam,female,51,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,2,never_married,NA,TRUE,12500 +80090,both interview and exam,female,0,8,white,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80091,both interview and exam,male,65,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +80092,both interview and exam,female,65,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80093,both interview and exam,female,8,NA,asian,2,104,NA,NA,FALSE,FALSE,3,2,NA,NA,NA,TRUE,100000 +80094,both interview and exam,female,69,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,60000 +80095,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +80096,both interview and exam,female,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,NA +80097,both interview and exam,male,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80098,both interview and exam,male,15,NA,mexican american,2,185,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +80099,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,70000 +80100,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +80101,both interview and exam,male,29,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,70000 +80102,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,separated,NA,TRUE,40000 +80103,both interview and exam,male,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,87500 +80104,both interview and exam,male,11,NA,mexican american,1,138,NA,NA,FALSE,FALSE,NA,3,NA,NA,NA,FALSE,30000 +80105,both interview and exam,male,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,30000 +80106,both interview and exam,female,19,NA,mexican american,1,238,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +80107,both interview and exam,female,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +80108,both interview and exam,female,4,NA,other hispanic,2,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +80109,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,yes,TRUE,87500 +80110,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +80111,both interview and exam,female,18,NA,black,2,228,FALSE,NA,FALSE,TRUE,12.5,13,NA,NA,NA,TRUE,NA +80112,both interview and exam,male,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +80113,both interview and exam,male,1,16,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80114,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +80115,both interview and exam,male,80,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +80116,interview only,female,61,NA,black,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,separated,NA,TRUE,2500 +80117,both interview and exam,male,0,0,black,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80118,both interview and exam,female,8,NA,white,2,102,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +80119,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,70000 +80120,both interview and exam,female,65,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +80121,both interview and exam,male,68,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,TRUE,NA +80122,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +80123,both interview and exam,male,71,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +80124,both interview and exam,male,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +80125,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,unable to ascertain,TRUE,22500 +80126,both interview and exam,male,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +80127,both interview and exam,male,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80128,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,22500 +80129,both interview and exam,male,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +80130,both interview and exam,male,51,NA,other,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,NA,TRUE,100000 +80131,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,7500 +80132,both interview and exam,male,37,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,never_married,NA,TRUE,NA +80133,both interview and exam,male,80,NA,black,2,NA,TRUE,FALSE,FALSE,TRUE,55,NA,5,married,NA,TRUE,100000 +80134,both interview and exam,female,18,NA,mexican american,2,223,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,30000 +80135,interview only,female,22,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,NA,never_married,unable to ascertain,TRUE,NA +80136,both interview and exam,male,65,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,FALSE,22500 +80137,both interview and exam,male,30,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,married,NA,TRUE,40000 +80138,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +80139,both interview and exam,female,39,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,divorced,no,TRUE,50000 +80140,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +80141,both interview and exam,male,16,NA,black,1,204,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +80142,both interview and exam,male,3,NA,white,1,38,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,100000 +80143,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,never_married,NA,TRUE,NA +80144,both interview and exam,male,50,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +80145,both interview and exam,male,22,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,FALSE,7500 +80146,both interview and exam,male,33,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,FALSE,7500 +80147,both interview and exam,female,0,4,white,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80148,both interview and exam,male,80,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,7500 +80149,both interview and exam,female,20,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,NA +80150,both interview and exam,female,12,NA,other hispanic,2,151,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,22500 +80151,both interview and exam,male,6,NA,white,2,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +80152,both interview and exam,male,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +80153,both interview and exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80154,both interview and exam,female,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +80155,both interview and exam,male,52,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,FALSE,NA +80156,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +80157,interview only,female,42,NA,mexican american,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,unable to ascertain,FALSE,22500 +80158,both interview and exam,male,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +80159,both interview and exam,male,7,NA,black,2,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,2500 +80160,both interview and exam,female,13,NA,white,1,161,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +80161,both interview and exam,female,10,NA,other hispanic,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,50000 +80162,both interview and exam,female,17,NA,white,2,211,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,60000 +80163,both interview and exam,female,63,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +80164,both interview and exam,male,19,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,12500 +80165,both interview and exam,female,65,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,60000 +80166,both interview and exam,male,17,NA,other hispanic,1,210,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +80167,both interview and exam,female,9,NA,white,1,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +80168,both interview and exam,male,38,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +80169,both interview and exam,female,42,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,no,FALSE,NA +80170,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 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exam,male,9,NA,other,1,117,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +80181,both interview and exam,female,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,30000 +80182,both interview and exam,female,14,NA,asian,1,171,NA,NA,FALSE,FALSE,0.5,7,NA,NA,NA,TRUE,2500 +80183,both interview and exam,male,75,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +80184,both interview and exam,male,13,NA,other hispanic,2,166,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +80185,both interview and exam,male,61,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,2,married,NA,TRUE,30000 +80186,both interview and exam,female,10,NA,black,2,131,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80187,both interview and exam,male,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +80188,both interview and exam,male,55,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,50000 +80189,both interview and exam,male,18,NA,other,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +80190,both interview and exam,female,33,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +80191,both interview and exam,male,6,NA,other,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,50000 +80192,both interview and exam,male,0,6,black,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80193,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,60000 +80194,both interview and exam,female,18,NA,mexican american,1,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +80195,both interview and exam,male,1,13,mexican american,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +80196,both interview and exam,male,13,NA,mexican american,2,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,70000 +80197,both interview and exam,male,44,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,living_with_partner,NA,FALSE,30000 +80198,both interview and exam,female,7,NA,white,1,91,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +80199,both interview and exam,female,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,50000 +80200,both interview and exam,male,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +80201,both interview and exam,female,63,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,divorced,NA,TRUE,30000 +80202,both interview and exam,male,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +80203,both interview and exam,male,67,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,NA +80204,both interview and exam,male,59,NA,white,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,TRUE,40000 +80205,both interview and exam,male,75,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +80206,both interview and exam,female,63,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,2,married,NA,FALSE,12500 +80207,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +80208,interview only,male,1,20,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80209,both interview and exam,male,0,3,black,2,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80210,both interview and exam,male,37,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,FALSE,87500 +80211,both interview and exam,female,7,NA,mexican american,1,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +80212,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +80213,both interview and exam,female,0,5,mexican american,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80214,both interview and exam,male,46,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +80215,both interview and exam,male,22,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +80216,both interview and exam,female,8,NA,white,2,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +80217,both interview and exam,female,28,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +80218,both interview and exam,female,72,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,NA +80219,both interview and exam,female,5,NA,other hispanic,1,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80220,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,100000 +80221,interview only,male,33,NA,mexican american,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,living_with_partner,NA,FALSE,30000 +80222,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +80223,both interview and exam,female,11,NA,other,1,136,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +80224,both interview and exam,female,0,6,other hispanic,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80225,both interview and exam,female,40,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,divorced,no,FALSE,12500 +80226,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +80227,both interview and exam,male,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +80228,both interview and exam,male,10,NA,white,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +80229,both interview and exam,female,1,14,other hispanic,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +80230,interview only,female,23,NA,other,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,unable to ascertain,TRUE,17500 +80231,both interview and exam,female,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +80232,both interview and exam,female,15,NA,black,1,181,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,NA +80233,both interview and exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +80234,both interview and exam,female,50,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,FALSE,50000 +80235,both interview and exam,female,44,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,no,TRUE,60000 +80236,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +80237,both interview and exam,male,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80238,both interview and exam,male,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,60000 +80239,both interview and exam,male,10,NA,black,1,131,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +80240,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +80241,both interview and exam,female,61,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,divorced,NA,FALSE,22500 +80242,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +80243,both interview and exam,female,12,NA,white,2,152,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +80244,both interview and exam,female,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,yes,TRUE,100000 +80245,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +80246,both interview and exam,male,4,NA,white,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80247,both interview and exam,female,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,17500 +80248,both interview and exam,female,29,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +80249,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +80250,both interview and exam,male,72,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +80251,both interview and exam,female,27,NA,black,2,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,no,TRUE,40000 +80252,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +80253,both interview and exam,male,8,NA,asian,2,104,NA,NA,FALSE,FALSE,7.5,2,NA,NA,NA,TRUE,87500 +80254,both interview and exam,female,31,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,unable to ascertain,TRUE,60000 +80255,interview only,female,3,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80256,both interview and exam,male,2,NA,other hispanic,1,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +80257,both interview and exam,female,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +80258,both interview and exam,male,19,NA,black,2,229,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +80259,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,40000 +80260,both interview and exam,male,40,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,TRUE,87500 +80261,both interview and exam,female,38,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,100000 +80262,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +80263,both interview and exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +80264,both interview and exam,female,21,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,NA +80265,both interview and exam,female,35,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,100000 +80266,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +80267,both interview and exam,male,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +80268,both interview and exam,male,71,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,60000 +80269,both interview and exam,male,25,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,never_married,NA,TRUE,40000 +80270,interview only,male,37,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +80271,both interview and exam,male,2,NA,mexican american,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80272,both interview and exam,female,41,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,no,FALSE,22500 +80273,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +80274,both interview and exam,female,70,NA,white,1,NA,FALSE,NA,FALSE,FALSE,45,NA,2,widowed,NA,TRUE,40000 +80275,both interview and exam,male,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +80276,both interview and exam,male,0,7,mexican american,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +80277,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,40000 +80278,both interview and exam,male,47,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,NA +80279,both interview and exam,male,38,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80280,both interview and exam,female,31,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,living_with_partner,no,FALSE,100000 +80281,both interview and exam,female,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +80282,both interview and exam,female,5,NA,mexican american,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +80283,both interview and exam,female,13,NA,other hispanic,1,162,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,2500 +80284,both interview and exam,male,11,NA,black,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80285,both interview and exam,male,50,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +80286,both interview and exam,male,38,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,40000 +80287,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,60000 +80288,both interview and exam,male,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,17500 +80289,both interview and exam,female,37,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,no,TRUE,12500 +80290,both interview and exam,male,1,13,black,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80291,both interview and exam,male,31,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +80292,both interview and exam,female,69,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +80293,both interview and exam,female,11,NA,black,2,142,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +80294,both interview and exam,female,75,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +80295,both interview and exam,female,38,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,no,TRUE,87500 +80296,both interview and exam,female,64,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,22500 +80297,both interview and exam,female,16,NA,mexican american,2,194,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +80298,both interview and exam,female,4,NA,other hispanic,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80299,both interview and exam,male,15,NA,black,1,181,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +80300,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +80301,both interview and exam,male,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +80302,both interview and exam,female,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,unable to ascertain,TRUE,12500 +80303,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +80304,both interview and exam,male,43,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,30000 +80305,both interview and exam,female,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +80306,both interview and exam,female,4,NA,mexican american,2,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80307,both interview and exam,female,75,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +80308,both interview and exam,male,39,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,TRUE,60000 +80309,both interview and exam,female,44,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,no,FALSE,NA +80310,both interview and exam,male,18,NA,black,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +80311,both interview and exam,female,11,NA,black,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +80312,both interview and exam,male,40,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +80313,both interview and exam,female,2,NA,white,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80314,both interview and exam,female,10,NA,black,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +80315,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +80316,both interview and exam,female,11,NA,black,2,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,NA +80317,both interview and exam,female,14,NA,white,1,177,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +80318,both interview and exam,female,2,NA,black,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +80319,both interview and exam,female,8,NA,mexican american,1,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +80320,both interview and exam,female,9,NA,black,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +80321,both interview and exam,male,72,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +80322,both interview and exam,female,55,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,TRUE,70000 +80323,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,2500 +80324,both interview and exam,female,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +80325,both interview and exam,female,19,NA,mexican american,1,234,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,22500 +80326,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +80327,both interview and exam,male,27,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,5,never_married,NA,TRUE,12500 +80328,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +80329,both interview and exam,female,69,NA,mexican american,1,NA,FALSE,NA,FALSE,NA,35,NA,1,separated,NA,TRUE,70000 +80330,both interview and exam,male,73,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,50000 +80331,both interview and exam,male,27,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +80332,both interview and exam,male,24,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,17500 +80333,both interview and exam,female,45,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,NA +80334,both interview and exam,female,14,NA,white,2,173,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +80335,both interview and exam,male,28,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,30000 +80336,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +80337,both interview and exam,female,14,NA,asian,2,180,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +80338,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,30000 +80339,both interview and exam,female,37,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,living_with_partner,no,FALSE,17500 +80340,both interview and exam,male,61,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +80341,both interview and exam,female,8,NA,white,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,70000 +80342,both interview and exam,female,2,NA,black,1,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80343,both interview and exam,female,24,NA,other 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exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,40000 +80353,both interview and exam,female,9,NA,mexican american,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +80354,both interview and exam,female,12,NA,asian,2,151,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +80355,both interview and exam,female,70,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,separated,NA,FALSE,12500 +80356,both interview and exam,male,12,NA,black,1,145,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +80357,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,12500 +80358,both interview and exam,male,4,NA,black,1,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80359,both interview and exam,male,4,NA,other hispanic,2,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +80360,both interview and exam,female,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80361,both interview and exam,male,19,NA,white,2,231,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,100000 +80362,both interview and exam,female,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80363,both interview and exam,female,13,NA,asian,2,162,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +80364,both interview and exam,female,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +80365,both interview and exam,female,34,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,never_married,no,TRUE,100000 +80366,both interview and exam,male,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80367,both interview and exam,female,71,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,FALSE,22500 +80368,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +80369,both interview and exam,female,31,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,no,TRUE,30000 +80370,both interview and exam,male,0,10,black,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80371,both interview and exam,female,39,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,no,TRUE,40000 +80372,both interview and exam,male,42,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80373,both interview and exam,female,1,16,mexican american,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80374,both interview and exam,female,0,5,black,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +80375,both interview and exam,male,47,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,100000 +80376,both interview and exam,female,3,NA,white,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +80377,both interview and exam,male,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +80378,both interview and exam,female,3,NA,mexican american,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80379,both interview and exam,male,67,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,30000 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exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,12500 +80390,both interview and exam,female,65,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +80391,both interview and exam,male,23,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,never_married,NA,FALSE,22500 +80392,both interview and exam,female,16,NA,white,1,195,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +80393,both interview and exam,male,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +80394,both interview and exam,male,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,87500 +80395,both interview and exam,male,9,NA,mexican american,1,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +80396,both interview and exam,male,31,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +80397,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,NA +80398,both interview and exam,female,17,NA,asian,1,205,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +80399,interview only,male,3,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80400,both interview and exam,male,0,1,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80401,both interview and exam,female,19,NA,black,2,239,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,17500 +80402,both interview and exam,male,66,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +80403,both interview and exam,female,38,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,no,TRUE,40000 +80404,both interview and exam,male,0,1,black,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +80405,both interview and exam,female,24,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,yes,TRUE,22500 +80406,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,NA +80407,both interview and exam,female,15,NA,white,2,192,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +80408,both interview and exam,female,43,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,widowed,no,TRUE,40000 +80409,both interview and exam,female,5,NA,white,1,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80410,both interview and exam,male,47,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,NA,TRUE,NA +80411,both interview and exam,male,41,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,living_with_partner,NA,FALSE,22500 +80412,both interview and exam,male,3,NA,white,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80413,both interview and exam,male,46,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +80414,both interview and exam,male,24,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,never_married,NA,FALSE,40000 +80415,both interview and exam,male,6,NA,white,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +80416,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +80417,both interview and exam,female,60,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,TRUE,22500 +80418,both interview and exam,male,2,NA,other hispanic,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +80419,both interview and exam,female,12,NA,black,1,152,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +80420,both interview and exam,female,6,NA,black,2,73,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +80421,both interview and exam,female,13,NA,white,2,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +80422,both interview and exam,female,0,1,white,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80423,both interview and exam,male,8,NA,white,1,104,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +80424,both interview and exam,female,14,NA,other hispanic,1,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +80425,both interview and exam,male,19,NA,mexican american,2,231,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,22500 +80426,both interview and exam,female,0,9,mexican american,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 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american,2,NA,FALSE,NA,FALSE,TRUE,55,NA,2,widowed,NA,FALSE,12500 +80437,both interview and exam,female,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80438,both interview and exam,female,37,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,no,TRUE,12500 +80439,both interview and exam,female,1,20,mexican american,2,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80440,both interview and exam,female,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +80441,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +80442,both interview and exam,female,41,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,no,FALSE,NA +80443,both interview and exam,female,8,NA,mexican american,2,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +80444,both interview and exam,female,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,unable to ascertain,TRUE,NA +80445,both interview and exam,male,22,NA,other 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exam,female,13,NA,black,2,161,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +80474,both interview and exam,female,20,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +80475,both interview and exam,male,16,NA,black,1,201,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +80476,both interview and exam,male,12,NA,other,2,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80477,both interview and exam,male,49,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,100000 +80478,both interview and exam,female,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80479,both interview and exam,male,62,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +80480,both interview and exam,male,16,NA,other hispanic,1,203,NA,NA,FALSE,FALSE,0.5,8,NA,NA,NA,FALSE,22500 +80481,both interview and exam,male,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,17500 +80482,both interview and 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exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80519,both interview and exam,female,36,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,no,FALSE,40000 +80520,both interview and exam,female,40,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,50000 +80521,both interview and exam,male,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80522,both interview and exam,male,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +80523,both interview and exam,male,52,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,never_married,NA,FALSE,12500 +80524,both interview and exam,female,12,NA,other,2,148,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +80525,both interview and exam,female,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,30000 +80526,both interview and exam,female,35,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,2500 +80527,both interview and exam,male,0,10,mexican 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interview and exam,male,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +80538,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +80539,both interview and exam,male,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +80540,both interview and exam,female,18,NA,black,2,224,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,12500 +80541,both interview and exam,male,4,NA,white,1,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +80542,both interview and exam,female,36,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +80543,both interview and exam,male,28,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +80544,both interview and exam,female,9,NA,mexican american,1,111,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +80545,both interview and exam,male,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +80546,both interview and exam,female,3,NA,mexican 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interview and exam,male,51,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,FALSE,17500 +80557,both interview and exam,female,0,9,mexican american,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,40000 +80558,both interview and exam,female,9,NA,mexican american,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,70000 +80559,both interview and exam,male,26,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +80560,both interview and exam,male,25,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +80561,both interview and exam,male,41,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,100000 +80562,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,60000 +80563,both interview and exam,female,12,NA,white,1,151,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +80564,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80565,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +80566,both interview and exam,female,6,NA,mexican american,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +80567,interview only,male,12,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +80568,both interview and exam,female,2,24,white,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80569,both interview and exam,female,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,100000 +80570,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80571,both interview and exam,male,9,NA,asian,1,112,NA,NA,FALSE,TRUE,7.5,2,NA,NA,NA,TRUE,50000 +80572,interview only,female,8,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,7500 +80573,both interview and exam,female,63,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,married,NA,TRUE,100000 +80574,both interview and exam,female,12,NA,other hispanic,1,147,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,NA +80575,both interview and exam,female,16,NA,mexican american,1,193,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +80576,both interview and exam,male,1,21,white,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80577,interview only,female,5,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80578,both interview and exam,male,44,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +80579,both interview and exam,male,11,NA,black,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +80580,both interview and exam,male,0,8,other,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80581,both interview and exam,male,8,NA,white,1,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +80582,both interview and exam,female,4,NA,white,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +80583,both interview and exam,female,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +80584,both interview and exam,female,10,NA,other hispanic,1,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,50000 +80585,both interview and exam,male,41,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +80586,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +80587,both interview and exam,male,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +80588,both interview and exam,female,59,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,100000 +80589,both interview and exam,female,28,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,yes,TRUE,12500 +80590,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,no,TRUE,22500 +80591,both interview and exam,male,9,NA,white,2,109,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +80592,both interview and exam,male,20,NA,mexican american,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +80593,both interview and exam,male,63,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,50000 +80594,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80595,both interview and exam,female,66,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +80596,both interview and exam,male,32,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +80597,both interview and exam,female,5,NA,white,1,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80598,both interview and exam,female,7,NA,black,1,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +80599,both interview and exam,male,77,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +80600,both interview and exam,female,3,NA,black,1,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80601,both interview and exam,female,71,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +80602,both interview and exam,female,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +80603,both interview and exam,female,31,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,yes,TRUE,50000 +80604,both interview and exam,male,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +80605,both interview and exam,male,14,NA,black,2,170,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +80606,both interview and exam,male,0,5,mexican american,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80607,both interview and exam,male,16,NA,mexican american,2,201,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +80608,both interview and exam,male,11,NA,white,2,139,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +80609,both interview and exam,male,0,11,white,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80610,both interview and exam,female,0,9,asian,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80611,both interview and exam,female,42,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,no,TRUE,100000 +80612,both interview and exam,female,1,13,white,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80613,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +80614,both interview and exam,female,4,NA,white,2,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80615,both interview and exam,male,1,18,other hispanic,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80616,both interview and exam,female,14,NA,mexican american,2,178,NA,NA,FALSE,TRUE,7.5,8,NA,NA,NA,FALSE,87500 +80617,interview only,male,29,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,12500 +80618,both interview and exam,male,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +80619,both interview and exam,male,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +80620,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +80621,both interview and exam,female,5,NA,black,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80622,both interview and exam,female,45,NA,mexican 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exam,female,2,NA,white,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80725,both interview and exam,female,0,6,other hispanic,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +80726,both interview and exam,female,38,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,no,TRUE,70000 +80727,both interview and exam,female,12,NA,white,1,151,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +80728,both interview and exam,male,2,NA,asian,1,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80729,both interview and exam,male,31,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,never_married,NA,TRUE,60000 +80730,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +80731,both interview and exam,female,32,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +80732,both interview and exam,male,52,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +80733,both interview and 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exam,female,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +80872,both interview and exam,male,66,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,TRUE,NA +80873,both interview and exam,female,36,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,no,TRUE,100000 +80874,interview only,female,74,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +80875,both interview and exam,female,0,5,mexican american,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80876,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,70000 +80877,both interview and exam,male,8,NA,black,1,106,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +80878,both interview and exam,female,65,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +80879,both interview and exam,female,48,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +80880,both interview and 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interview and exam,male,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +80947,both interview and exam,male,12,NA,white,1,156,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +80948,both interview and exam,male,18,NA,black,1,219,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +80949,both interview and exam,female,7,NA,mexican american,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +80950,both interview and exam,male,0,4,other hispanic,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80951,both interview and exam,female,5,NA,white,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +80952,both interview and exam,female,1,15,other hispanic,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,70000 +80953,both interview and exam,male,15,NA,mexican american,2,188,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +80954,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +80955,both interview and exam,female,72,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +80956,both interview and exam,female,18,NA,asian,2,221,FALSE,NA,FALSE,FALSE,0.5,12,NA,NA,NA,TRUE,2500 +80957,both interview and exam,male,12,NA,black,1,156,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +80958,both interview and exam,male,9,NA,mexican american,2,113,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +80959,interview only,female,24,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,living_with_partner,unable to ascertain,TRUE,70000 +80960,both interview and exam,male,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,30000 +80961,both interview and exam,female,41,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,87500 +80962,both interview and exam,female,72,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,22500 +80963,both interview and exam,male,4,NA,black,1,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80964,both interview and exam,female,19,NA,white,1,238,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,60000 +80965,both interview and exam,male,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +80966,both interview and exam,female,27,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +80967,both interview and exam,male,40,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,22500 +80968,both interview and exam,male,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +80969,interview only,female,17,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +80970,both interview and exam,male,14,NA,mexican american,1,171,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +80971,both interview and exam,male,8,NA,white,2,103,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +80972,both interview and exam,male,8,NA,asian,1,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +80973,both interview and exam,female,47,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,NA,TRUE,12500 +80974,both interview and exam,female,14,NA,other,2,175,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +80975,both interview and exam,female,26,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +80976,both interview and exam,male,59,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +80977,both interview and exam,male,0,8,mexican american,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +80978,both interview and exam,male,0,1,other,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80979,both interview and exam,male,29,NA,other hispanic,1,NA,TRUE,FALSE,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +80980,both interview and exam,female,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,50000 +80981,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +80982,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +80983,both interview and exam,female,5,NA,black,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80984,both interview and exam,female,7,NA,other,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +80985,both interview and exam,male,46,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,25,NA,5,married,NA,TRUE,87500 +80986,both interview and exam,female,1,19,other,2,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80987,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,30000 +80988,both interview and exam,female,65,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,30000 +80989,both interview and exam,male,46,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +80990,both interview and exam,male,35,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,NA +80991,both interview and exam,female,11,NA,black,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 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hispanic,2,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,40000 +81002,both interview and exam,male,9,NA,white,1,109,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +81003,both interview and exam,female,16,NA,white,2,192,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +81004,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +81005,both interview and exam,female,1,16,white,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81006,both interview and exam,female,10,NA,mexican american,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +81007,interview only,female,3,NA,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81008,both interview and exam,male,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81009,both interview and exam,female,56,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,TRUE,17500 +81010,both interview and exam,male,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +81011,both interview and exam,female,60,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81012,both interview and exam,male,34,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,12500 +81013,both interview and exam,male,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81014,both interview and exam,male,27,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +81015,both interview and exam,female,20,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +81016,both interview and exam,male,6,NA,other hispanic,1,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +81017,both interview and exam,male,15,NA,white,2,187,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,60000 +81018,both interview and exam,female,9,NA,black,2,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,50000 +81019,both interview and exam,female,14,NA,black,1,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +81020,both interview and exam,male,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +81021,interview only,male,2,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81022,both interview and exam,male,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,30000 +81023,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,yes,TRUE,17500 +81024,both interview and exam,male,6,NA,white,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +81025,both interview and exam,female,69,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,divorced,NA,FALSE,NA +81026,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,30000 +81027,both interview and exam,female,0,9,black,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81028,both interview and exam,male,12,NA,other hispanic,1,147,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,NA +81029,both interview and exam,male,43,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,married,NA,FALSE,NA +81030,both interview and exam,male,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +81031,both interview and exam,male,9,NA,black,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,2500 +81032,both interview and exam,male,71,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +81033,both interview and exam,female,9,NA,mexican american,1,120,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,30000 +81034,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +81035,both interview and exam,male,10,NA,white,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +81036,both interview and exam,male,2,NA,black,1,37,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81037,both interview and exam,male,60,NA,black,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,NA,TRUE,87500 +81038,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +81039,both interview and exam,male,64,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,7500 +81040,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,60000 +81041,both interview and exam,female,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +81042,both interview and exam,male,63,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,separated,NA,TRUE,100000 +81043,both interview and exam,female,18,NA,white,2,218,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +81044,both interview and exam,male,10,NA,mexican american,1,130,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,30000 +81045,both interview and exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81046,interview only,female,4,NA,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81047,both interview and exam,female,8,NA,mexican american,2,108,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +81048,both interview and exam,female,13,NA,black,1,162,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,2500 +81049,both interview and exam,female,12,NA,other hispanic,1,146,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81050,both interview and exam,female,38,NA,other,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,no,TRUE,50000 +81051,both interview and exam,male,41,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81052,both interview and exam,female,44,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,70000 +81053,both interview and exam,male,3,NA,mexican american,1,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +81054,both interview and exam,female,66,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,22500 +81055,both interview and exam,female,48,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,40000 +81056,both interview and exam,female,49,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +81057,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +81058,both interview and exam,female,5,NA,white,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81059,both interview and exam,male,4,NA,other hispanic,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81060,both interview and exam,female,14,NA,white,2,172,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +81061,both interview and exam,male,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +81062,interview only,female,48,NA,asian,NA,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +81063,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,22500 +81064,both interview and exam,male,11,NA,white,2,141,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +81065,both interview and exam,female,19,NA,black,2,231,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +81066,both interview and exam,female,1,18,white,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81067,both interview and exam,female,7,NA,white,1,85,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +81068,both interview and exam,male,59,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81069,both interview and exam,female,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,no,TRUE,7500 +81070,both interview and exam,male,31,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,NA,FALSE,40000 +81071,both interview and exam,male,2,NA,mexican american,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81072,both interview and exam,male,17,NA,mexican american,2,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,22500 +81073,both interview and exam,female,13,NA,black,2,164,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,NA +81074,both interview and exam,female,19,NA,other hispanic,1,234,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,22500 +81075,both interview and exam,male,30,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +81076,both interview and exam,female,18,NA,asian,2,224,FALSE,NA,FALSE,TRUE,7.5,13,NA,NA,NA,TRUE,30000 +81077,both interview and exam,male,0,8,mexican american,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81078,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,4,never_married,NA,FALSE,NA +81079,both interview and exam,male,76,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +81080,both interview and exam,female,12,NA,black,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81081,both interview and exam,male,3,NA,black,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81082,both interview and exam,female,60,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,never_married,NA,FALSE,NA +81083,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81084,both interview and exam,female,26,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,never_married,no,TRUE,100000 +81085,both interview and exam,male,4,NA,other,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81086,interview only,female,9,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +81087,both interview and exam,female,36,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81088,both interview and exam,female,54,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,30000 +81089,both interview and exam,male,11,NA,other hispanic,1,144,NA,NA,FALSE,FALSE,7.5,6,NA,NA,NA,FALSE,NA +81090,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,22500 +81091,both interview and exam,female,11,NA,black,1,136,NA,NA,FALSE,FALSE,NA,5,NA,NA,NA,TRUE,30000 +81092,both interview and exam,male,29,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,living_with_partner,NA,TRUE,12500 +81093,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,17500 +81094,both interview and exam,male,6,NA,other hispanic,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +81095,both interview and exam,male,51,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,40000 +81096,both interview and exam,female,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,unable to ascertain,TRUE,7500 +81097,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,30000 +81098,both interview and exam,female,5,NA,white,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81099,both interview and exam,female,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +81100,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +81101,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +81102,both interview and exam,male,4,NA,mexican american,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +81103,both interview and exam,male,80,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +81104,both interview and exam,female,67,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,7500 +81105,both interview and exam,male,63,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +81106,both interview and exam,female,10,NA,mexican american,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +81107,both interview and exam,female,54,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81108,both interview and exam,female,13,NA,mexican american,1,167,NA,NA,FALSE,FALSE,12.5,7,NA,NA,NA,FALSE,30000 +81109,both interview and exam,female,77,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81110,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81111,both interview and exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +81112,both interview and exam,female,3,NA,white,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81113,interview only,female,80,NA,other,NA,NA,FALSE,NA,FALSE,TRUE,55,NA,3,married,NA,TRUE,40000 +81114,both interview and exam,female,9,NA,black,1,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +81115,both interview and exam,male,60,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,100000 +81116,both interview and exam,female,16,NA,mexican american,1,200,NA,NA,FALSE,FALSE,7.5,10,NA,NA,NA,TRUE,22500 +81117,both interview and exam,male,19,NA,mexican american,1,236,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,FALSE,40000 +81118,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,no,TRUE,60000 +81119,both interview and exam,female,37,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +81120,both interview and exam,male,3,NA,other hispanic,1,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81121,both interview and exam,male,61,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +81122,both interview and exam,female,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,22500 +81123,both interview and exam,male,8,NA,white,1,103,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81124,both interview and exam,female,15,NA,white,2,190,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,7500 +81125,both interview and exam,male,15,NA,white,2,192,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +81126,both interview and exam,female,11,NA,other hispanic,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +81127,both interview and exam,male,9,NA,white,2,112,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +81128,both interview and exam,female,10,NA,other,2,125,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +81129,both interview and exam,male,12,NA,black,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +81130,both interview and exam,male,18,NA,asian,2,226,FALSE,NA,FALSE,TRUE,12.5,14,NA,NA,NA,TRUE,100000 +81131,both interview and exam,male,49,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +81132,both interview and exam,male,6,NA,black,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +81133,both interview and exam,female,17,NA,white,2,210,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81134,both interview and exam,female,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81135,both interview and exam,male,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,60000 +81136,both interview and exam,female,78,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,widowed,NA,TRUE,22500 +81137,both interview and exam,female,16,NA,mexican american,1,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +81138,both interview and exam,female,42,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,4,married,no,TRUE,100000 +81139,both interview and exam,male,23,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,4,never_married,NA,TRUE,87500 +81140,both interview and exam,male,6,NA,asian,1,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81141,both interview and exam,male,70,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,22500 +81142,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +81143,interview only,female,80,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +81144,both interview and exam,male,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +81145,both interview and exam,female,3,NA,black,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81146,both interview and exam,female,8,NA,other,2,99,NA,NA,FALSE,FALSE,0.5,0,NA,NA,NA,TRUE,2500 +81147,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81148,both interview and exam,female,73,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +81149,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81150,both interview and exam,male,13,NA,mexican american,2,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +81151,both interview and exam,male,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81152,both interview and exam,female,34,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,yes,TRUE,40000 +81153,both interview and exam,female,30,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,no,TRUE,30000 +81154,both interview and exam,male,50,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,FALSE,70000 +81155,both interview and exam,female,56,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +81156,both interview and exam,male,7,NA,black,1,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +81157,both interview and exam,female,3,NA,mexican american,2,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81158,both interview and exam,female,13,NA,mexican american,1,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,NA +81159,both interview and exam,female,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,60000 +81160,both interview and exam,male,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +81161,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,17500 +81162,both interview and exam,female,80,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,widowed,NA,TRUE,87500 +81163,both interview and exam,female,79,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,30000 +81164,both interview and exam,male,5,NA,black,1,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81165,both interview and exam,male,51,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,FALSE,100000 +81166,both interview and exam,female,73,NA,white,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,NA,TRUE,7500 +81167,both interview and exam,male,7,NA,white,1,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81168,both interview and exam,female,28,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,never_married,no,TRUE,60000 +81169,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +81170,both interview and exam,female,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,40000 +81171,both interview and exam,female,49,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,60000 +81172,both interview and exam,female,4,NA,white,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +81173,both interview and exam,female,50,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +81174,both interview and exam,female,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,30000 +81175,both interview and exam,male,80,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +81176,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,no,FALSE,40000 +81177,both interview and exam,female,48,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81178,both interview and exam,male,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +81179,interview only,male,80,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,NA +81180,both interview and exam,female,14,NA,mexican american,2,176,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +81181,both interview and exam,male,4,NA,white,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81182,both interview and exam,female,16,NA,asian,1,203,NA,NA,FALSE,FALSE,3,9,NA,NA,NA,TRUE,7500 +81183,both interview and exam,female,5,NA,mexican american,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81184,both interview and exam,male,7,NA,white,2,91,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81185,interview only,female,25,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,unable to ascertain,TRUE,100000 +81186,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +81187,both interview and exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,22500 +81188,both interview and exam,female,14,NA,mexican american,2,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +81189,both interview and exam,male,5,NA,white,2,63,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81190,both interview and exam,female,23,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +81191,both interview and exam,female,14,NA,asian,2,176,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +81192,both interview and exam,female,41,NA,other,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,TRUE,70000 +81193,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +81194,both interview and exam,female,11,NA,mexican american,2,144,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +81195,both interview and exam,female,4,NA,mexican american,1,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +81196,both interview and exam,female,41,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,divorced,no,TRUE,40000 +81197,both interview and exam,female,47,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,NA +81198,both interview and exam,male,0,7,black,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81199,both interview and exam,female,10,NA,asian,2,122,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +81200,both interview and exam,male,5,NA,black,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81201,both interview and exam,male,56,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,40000 +81202,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,22500 +81203,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81204,both interview and exam,female,65,NA,black,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,TRUE,NA +81205,both interview and exam,female,4,NA,white,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81206,both interview and exam,male,47,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +81207,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,NA,TRUE,100000 +81208,both interview and exam,female,2,NA,black,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +81209,both interview and exam,male,58,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,100000 +81210,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,100000 +81211,both interview and exam,male,3,NA,asian,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81212,both interview and exam,female,37,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +81213,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,40000 +81214,both interview and exam,male,50,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,NA,TRUE,30000 +81215,both interview and exam,female,0,7,white,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81216,both interview and exam,female,30,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81217,both interview and exam,male,45,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +81218,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81219,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,40000 +81220,both interview and exam,male,12,NA,white,2,150,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81221,both interview and exam,female,68,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,widowed,NA,FALSE,100000 +81222,both interview and exam,male,14,NA,white,2,174,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +81223,both interview and exam,female,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,17500 +81224,both interview and exam,female,18,NA,white,2,221,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,100000 +81225,both interview and exam,male,37,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +81226,both interview and exam,male,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,12500 +81227,both interview and exam,female,12,NA,white,1,150,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,NA +81228,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81229,both interview and exam,male,74,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,widowed,NA,FALSE,2500 +81230,both interview and exam,female,52,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +81231,both interview and exam,female,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +81232,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +81233,both interview and exam,male,10,NA,white,2,122,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +81234,both interview and exam,male,67,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,55,NA,5,divorced,NA,TRUE,NA +81235,both interview and exam,male,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +81236,both interview and exam,female,7,NA,black,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +81237,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +81238,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,40000 +81239,both interview and exam,female,14,NA,white,2,179,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,22500 +81240,both interview and exam,male,7,NA,black,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +81241,both interview and exam,male,51,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,50000 +81242,both interview and exam,male,14,NA,mexican american,1,177,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,17500 +81243,both interview and exam,male,8,NA,black,1,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +81244,both interview and exam,female,47,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81245,interview only,female,16,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +81246,both interview and exam,male,17,NA,black,1,215,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,22500 +81247,both interview and exam,male,15,NA,black,1,187,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +81248,both interview and exam,female,68,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +81249,both interview and exam,female,7,NA,white,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81250,both interview and exam,male,50,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,7500 +81251,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,FALSE,TRUE,55,NA,3,widowed,NA,TRUE,22500 +81252,both interview and exam,male,15,NA,black,2,189,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +81253,both interview and exam,male,4,NA,mexican american,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81254,both interview and exam,female,12,NA,other hispanic,2,156,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,NA +81255,both interview and exam,female,1,20,white,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81256,both interview and exam,male,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,12500 +81257,both interview and exam,male,7,NA,black,1,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +81258,both interview and exam,male,2,NA,other,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +81259,both interview and exam,male,75,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +81260,both interview and exam,male,44,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +81261,both interview and exam,female,14,NA,white,2,177,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +81262,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81263,both interview and exam,male,2,NA,black,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81264,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,87500 +81265,both interview and exam,male,7,NA,other,2,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +81266,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +81267,both interview and exam,female,75,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +81268,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,12500 +81269,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +81270,both interview and exam,male,43,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,100000 +81271,interview only,male,1,14,other,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81272,both interview and exam,female,46,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,never_married,NA,FALSE,NA +81273,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +81274,both interview and exam,male,13,NA,mexican american,2,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +81275,both interview and exam,female,50,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,FALSE,30000 +81276,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81277,both interview and exam,male,3,NA,mexican american,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +81278,both interview and exam,male,18,NA,other,2,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +81279,both interview and exam,male,7,NA,other,2,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +81280,both interview and exam,male,15,NA,asian,1,182,NA,NA,FALSE,FALSE,12.5,8,NA,NA,NA,TRUE,100000 +81281,both interview and exam,male,17,NA,black,1,207,FALSE,NA,FALSE,FALSE,NA,11,NA,NA,NA,TRUE,NA +81282,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +81283,both interview and exam,female,67,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,TRUE,40000 +81284,both interview and exam,female,64,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,FALSE,30000 +81285,both interview and exam,female,74,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +81286,both interview and exam,female,16,NA,asian,1,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +81287,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,60000 +81288,both interview and exam,female,71,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,widowed,NA,TRUE,17500 +81289,both interview and exam,female,17,NA,white,2,211,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81290,both interview and exam,male,30,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,2500 +81291,both interview and exam,male,21,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +81292,both interview and exam,male,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,87500 +81293,both interview and exam,male,7,NA,black,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81294,both interview and exam,male,18,NA,black,1,220,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +81295,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81296,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +81297,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +81298,both interview and exam,male,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,5,married,NA,TRUE,NA +81299,both interview and exam,female,2,NA,white,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81300,both interview and exam,male,17,NA,white,1,215,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +81301,both interview and exam,male,3,NA,white,1,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81302,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +81303,both interview and exam,male,20,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +81304,both interview and exam,female,20,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,never_married,unable to ascertain,FALSE,87500 +81305,both interview and exam,female,2,NA,mexican american,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +81306,both interview and exam,male,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +81307,both interview and exam,female,8,NA,mexican american,2,106,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +81308,both interview and exam,male,4,NA,mexican american,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +81309,both interview and exam,female,55,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,40000 +81310,both interview and exam,male,19,NA,mexican american,2,239,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +81311,both interview and exam,male,68,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,NA +81312,both interview and exam,female,19,NA,asian,2,237,FALSE,NA,FALSE,FALSE,3,13,NA,NA,NA,TRUE,22500 +81313,both interview and exam,male,20,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +81314,both interview and exam,male,10,NA,other,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +81315,both interview and exam,male,3,NA,other,2,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81316,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,40000 +81317,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81318,both interview and exam,female,16,NA,white,2,198,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +81319,both interview and exam,female,38,NA,black,1,NA,FALSE,NA,FALSE,FALSE,35,NA,4,divorced,no,TRUE,40000 +81320,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +81321,both interview and exam,female,80,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,2,widowed,NA,TRUE,70000 +81322,both interview and exam,female,55,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,divorced,NA,TRUE,40000 +81323,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81324,both interview and exam,male,1,22,black,1,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +81325,both interview and exam,female,9,NA,asian,2,112,NA,NA,FALSE,TRUE,7.5,3,NA,NA,NA,TRUE,100000 +81326,both interview and exam,female,16,NA,mexican american,2,201,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,50000 +81327,both interview and exam,male,11,NA,white,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81328,both interview and exam,male,18,NA,white,1,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +81329,both interview and exam,female,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +81330,both interview and exam,female,6,NA,mexican american,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +81331,both interview and exam,female,27,NA,white,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,never_married,no,TRUE,50000 +81332,both interview and exam,female,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +81333,both interview and exam,male,2,NA,black,2,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 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interview and exam,male,59,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,70000 +81345,both interview and exam,female,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,40000 +81346,both interview and exam,male,2,NA,white,1,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81347,both interview and exam,male,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81348,both interview and exam,male,21,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,never_married,NA,FALSE,50000 +81349,both interview and exam,male,36,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,living_with_partner,NA,FALSE,17500 +81350,both interview and exam,female,58,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,FALSE,30000 +81351,both interview and exam,female,14,NA,other,2,175,NA,NA,FALSE,FALSE,0.5,7,NA,NA,NA,TRUE,2500 +81352,both interview and exam,male,58,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,22500 +81353,both interview and exam,male,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81354,both interview and exam,female,3,NA,white,1,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81355,both interview and exam,female,6,NA,black,1,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +81356,both interview and exam,male,12,NA,black,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +81357,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +81358,both interview and exam,female,77,NA,black,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,widowed,NA,TRUE,7500 +81359,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +81360,both interview and exam,male,0,5,other hispanic,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81361,both interview and exam,female,8,NA,mexican american,2,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +81362,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,NA 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exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,70000 +81373,both interview and exam,male,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +81374,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,no,TRUE,60000 +81375,both interview and exam,female,41,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,no,TRUE,87500 +81376,both interview and exam,female,5,NA,asian,1,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81377,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81378,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +81379,both interview and exam,male,48,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +81380,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,12500 +81381,both interview and exam,female,73,NA,white,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,1,widowed,NA,TRUE,12500 +81382,both interview and exam,male,71,NA,mexican american,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81383,both interview and exam,male,16,NA,white,2,196,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +81384,both interview and exam,male,40,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,100000 +81385,both interview and exam,male,69,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81386,both interview and exam,female,18,NA,mexican american,1,220,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 +81387,both interview and exam,female,52,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,never_married,NA,TRUE,12500 +81388,both interview and exam,male,26,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,TRUE,22500 +81389,both interview and exam,male,13,NA,asian,2,160,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,70000 +81390,both interview and exam,male,3,NA,other,1,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81391,both interview and exam,male,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +81392,both interview and exam,female,11,NA,mexican american,2,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,70000 +81393,both interview and exam,female,16,NA,other hispanic,2,201,NA,NA,FALSE,FALSE,3,9,NA,NA,NA,FALSE,NA +81394,both interview and exam,female,10,NA,mexican american,1,130,NA,NA,FALSE,FALSE,7.5,4,NA,NA,NA,FALSE,40000 +81395,both interview and exam,male,23,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +81396,both interview and exam,male,21,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,never_married,NA,TRUE,50000 +81397,interview only,male,15,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,22500 +81398,both interview and exam,female,2,NA,white,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81399,interview 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exam,female,65,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,70000 +81410,both interview and exam,male,6,NA,white,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,60000 +81411,both interview and exam,male,15,NA,asian,2,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +81412,both interview and exam,male,67,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,5,divorced,NA,TRUE,22500 +81413,both interview and exam,female,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,70000 +81414,both interview and exam,male,13,NA,black,2,163,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +81415,both interview and exam,male,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81416,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +81417,both interview and exam,male,2,NA,black,1,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +81418,both interview and exam,female,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +81419,both interview and exam,female,14,NA,mexican american,1,169,NA,NA,FALSE,FALSE,12.5,7,NA,NA,NA,TRUE,22500 +81420,both interview and exam,male,1,15,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81421,both interview and exam,female,7,NA,black,1,85,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +81422,both interview and exam,male,4,NA,mexican american,2,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81423,both interview and exam,male,7,NA,asian,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +81424,both interview and exam,female,27,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +81425,both interview and exam,male,2,NA,black,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81426,both interview and exam,female,12,NA,black,1,155,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +81427,both interview and exam,male,52,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,living_with_partner,NA,FALSE,17500 +81428,both interview and exam,female,26,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +81429,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81430,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81431,interview only,male,5,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81432,both interview and exam,male,8,NA,black,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +81433,both interview and exam,male,17,NA,mexican american,1,206,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +81434,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +81435,both interview and exam,male,18,NA,white,1,216,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +81436,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,7500 +81437,both interview and exam,male,16,NA,black,1,195,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +81438,both interview and exam,female,56,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +81439,both interview and exam,male,0,3,white,1,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81440,both interview and exam,female,2,NA,other hispanic,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81441,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +81442,both interview and exam,female,32,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,divorced,no,FALSE,NA +81443,both interview and exam,male,1,12,white,1,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81444,both interview and exam,female,51,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,FALSE,70000 +81445,both interview and exam,male,10,NA,mexican american,1,129,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,NA +81446,both interview and exam,female,11,NA,mexican american,1,136,NA,NA,FALSE,FALSE,12.5,5,NA,NA,NA,FALSE,30000 +81447,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,7500 +81448,both interview and exam,male,18,NA,other hispanic,2,226,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,7500 +81449,both interview and exam,male,6,NA,black,2,79,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81450,both interview and exam,female,56,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,divorced,NA,TRUE,50000 +81451,both interview and exam,male,19,NA,white,1,236,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,40000 +81452,both interview and exam,male,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +81453,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +81454,both interview and exam,male,15,NA,other,1,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,22500 +81455,both interview and exam,male,1,15,black,2,16,NA,NA,FALSE,TRUE,0.5,NA,NA,NA,NA,TRUE,100000 +81456,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +81457,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,100000 +81458,both interview and exam,female,0,9,mexican american,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81459,both interview and exam,female,1,23,mexican american,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +81460,both interview and exam,female,46,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,87500 +81461,both interview and exam,male,24,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,NA,TRUE,22500 +81462,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,FALSE,NA +81463,both interview and exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,22500 +81464,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81465,both interview and exam,female,68,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,married,NA,TRUE,12500 +81466,both interview and exam,male,0,4,mexican american,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +81467,both interview and exam,female,7,NA,asian,1,85,NA,NA,FALSE,TRUE,3,0,NA,NA,NA,TRUE,100000 +81468,both interview and exam,male,74,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81469,both interview and exam,male,16,NA,mexican american,1,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,NA +81470,both interview and exam,female,43,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,87500 +81471,both interview and exam,female,14,NA,asian,1,170,NA,NA,FALSE,FALSE,0.5,7,NA,NA,NA,TRUE,87500 +81472,both interview and exam,male,29,NA,other,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,never_married,NA,TRUE,NA +81473,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,unable to ascertain,TRUE,17500 +81474,both interview and exam,female,78,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,40000 +81475,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,22500 +81476,both interview and exam,male,12,NA,white,2,147,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +81477,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +81478,both interview and exam,female,4,NA,black,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81479,both interview and exam,male,11,NA,black,2,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81480,both interview and exam,male,12,NA,black,1,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,60000 +81481,both interview and exam,female,28,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,married,no,TRUE,60000 +81482,both interview and exam,male,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81483,both interview and exam,male,5,NA,mexican american,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 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exam,male,5,NA,black,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81494,both interview and exam,male,38,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +81495,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +81496,both interview and exam,male,14,NA,white,2,174,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,87500 +81497,both interview and exam,female,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,50000 +81498,both interview and exam,female,11,NA,mexican american,2,133,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81499,both interview and exam,female,18,NA,mexican american,2,220,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +81500,both interview and exam,female,10,NA,mexican american,1,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +81501,both interview and exam,female,6,NA,black,1,75,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +81502,both interview and exam,male,17,NA,black,2,205,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +81503,both interview and exam,female,43,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,never_married,no,TRUE,87500 +81504,both interview and exam,male,80,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,2,married,NA,FALSE,30000 +81505,both interview and exam,male,8,NA,black,1,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +81506,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,7500 +81507,both interview and exam,female,2,NA,white,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81508,both interview and exam,female,52,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,TRUE,60000 +81509,both interview and exam,male,42,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,7500 +81510,both interview and exam,female,13,NA,mexican american,2,163,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +81511,both interview and exam,male,16,NA,white,2,194,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,22500 +81512,both interview and exam,male,69,NA,asian,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +81513,both interview and exam,male,7,NA,black,2,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +81514,both interview and exam,male,23,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +81515,both interview and exam,male,2,NA,mexican american,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81516,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +81517,both interview and exam,female,15,NA,asian,1,191,NA,NA,FALSE,FALSE,7.5,9,NA,NA,NA,TRUE,17500 +81518,both interview and exam,female,13,NA,black,1,159,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +81519,both interview and exam,male,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81520,interview only,female,15,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,22500 +81521,both interview and exam,female,55,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,100000 +81522,both interview and exam,female,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +81523,both interview and exam,female,57,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +81524,both interview and exam,male,73,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,50000 +81525,both interview and exam,male,10,NA,mexican american,1,120,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +81526,both interview and exam,female,16,NA,other,2,203,NA,NA,FALSE,FALSE,0.5,8,NA,NA,NA,TRUE,2500 +81527,both interview and exam,male,35,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +81528,both interview and exam,female,41,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,17500 +81529,both interview and exam,female,1,13,mexican american,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +81530,both interview and exam,female,73,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81531,both interview and exam,female,5,NA,other hispanic,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +81532,both interview and exam,male,5,NA,asian,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81533,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +81534,both interview and exam,female,49,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,17500 +81535,both interview and exam,female,46,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +81536,both interview and exam,female,8,NA,other hispanic,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +81537,both interview and exam,female,55,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,NA,FALSE,NA +81538,both interview and exam,male,12,NA,mexican american,2,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,7500 +81539,both interview and exam,male,7,NA,mexican american,2,94,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +81540,both interview and exam,female,7,NA,black,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81541,both interview and exam,female,15,NA,black,1,188,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +81542,both interview and exam,male,3,NA,white,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81543,both interview and exam,male,14,NA,white,2,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81544,both interview and exam,male,37,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,87500 +81545,both interview and exam,male,16,NA,mexican american,2,200,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +81546,both interview and exam,male,6,NA,black,1,82,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +81547,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,12500 +81548,both interview and exam,male,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,40000 +81549,both interview and exam,female,6,NA,white,2,81,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +81550,both interview and exam,male,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81551,both interview and exam,female,15,NA,mexican american,2,191,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +81552,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +81553,both interview and exam,female,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81554,both interview and exam,female,8,NA,mexican american,2,98,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,40000 +81555,both interview and exam,female,6,NA,black,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +81556,both interview and exam,female,25,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +81557,both interview and exam,male,13,NA,other,1,160,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +81558,both interview and exam,female,7,NA,white,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81559,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81560,both interview and exam,male,1,15,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81561,both interview and exam,male,10,NA,white,1,127,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +81562,both interview and exam,male,2,NA,other hispanic,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81563,both interview and exam,male,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +81564,both interview and exam,male,50,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,TRUE,17500 +81565,both interview and exam,male,9,NA,mexican american,1,119,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,17500 +81566,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +81567,both interview and exam,male,3,NA,asian,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81568,both interview and exam,female,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,50000 +81569,both interview and exam,male,1,12,asian,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81570,both interview and exam,female,58,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +81571,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,yes,TRUE,30000 +81572,both interview and exam,female,15,NA,black,1,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +81573,both interview and exam,female,64,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,never_married,NA,TRUE,2500 +81574,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81575,both interview and exam,male,11,NA,mexican american,2,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,60000 +81576,both interview and exam,female,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,no,FALSE,NA +81577,both interview and exam,male,9,NA,mexican american,2,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +81578,both interview and exam,male,60,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81579,both interview and exam,female,73,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,1,never_married,NA,FALSE,22500 +81580,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +81581,both interview and exam,male,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,widowed,NA,TRUE,12500 +81582,both interview and exam,male,72,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,22500 +81583,both interview and exam,female,18,NA,mexican american,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +81584,both interview and exam,female,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81585,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,22500 +81586,both interview and exam,male,6,NA,other hispanic,1,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +81587,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +81588,both interview and exam,female,11,NA,black,2,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +81589,both interview and exam,female,9,NA,asian,2,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +81590,both interview and exam,male,28,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,living_with_partner,NA,FALSE,30000 +81591,both interview and exam,female,14,NA,other,2,170,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +81592,interview only,female,4,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81593,both interview and exam,male,68,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,3,separated,NA,FALSE,17500 +81594,both interview and exam,male,60,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +81595,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +81596,both interview and exam,male,35,NA,white,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,NA,TRUE,22500 +81597,interview only,male,63,NA,black,NA,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,50000 +81598,both interview and exam,male,50,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,30000 +81599,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81600,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81601,both interview and exam,male,65,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,17500 +81602,both interview and exam,female,37,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,NA +81603,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +81604,both interview and exam,female,29,NA,black,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,never_married,no,TRUE,30000 +81605,both interview and exam,male,43,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,100000 +81606,both interview and exam,female,42,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,100000 +81607,both interview and exam,female,29,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +81608,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81609,both interview and exam,male,54,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,FALSE,NA +81610,both interview and exam,male,60,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,NA +81611,both interview and exam,male,31,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,separated,NA,FALSE,NA +81612,both interview and exam,female,3,NA,mexican american,1,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +81613,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,17500 +81614,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +81615,both interview and exam,female,10,NA,mexican american,2,127,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,17500 +81616,both interview and exam,female,10,NA,mexican american,1,122,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,17500 +81617,both interview and exam,male,52,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,never_married,NA,FALSE,NA +81618,both interview and exam,female,19,NA,white,1,230,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +81619,both interview and exam,female,18,NA,mexican american,2,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,40000 +81620,both interview and exam,male,26,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +81621,both interview and exam,female,15,NA,white,2,186,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +81622,both interview and exam,female,65,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +81623,both interview and exam,female,63,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,50000 +81624,both interview and exam,female,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81625,both interview and exam,female,41,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,married,no,TRUE,70000 +81626,both interview and exam,female,40,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,separated,no,TRUE,30000 +81627,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,NA +81628,both interview and exam,female,66,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +81629,both interview and exam,female,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81630,both interview and exam,female,14,NA,white,1,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,60000 +81631,both interview and exam,male,1,15,other,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +81632,both interview and exam,female,3,NA,black,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81633,both interview and exam,male,51,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +81634,both interview and exam,male,14,NA,white,2,175,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +81635,both interview and exam,female,5,NA,other hispanic,1,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81636,both interview and exam,male,79,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +81637,both interview and exam,male,5,NA,mexican american,1,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +81638,both interview and exam,female,15,NA,mexican american,1,188,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,22500 +81639,both interview and exam,female,13,NA,black,1,158,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +81640,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +81641,both interview and exam,female,9,NA,black,2,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +81642,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +81643,both interview and exam,female,50,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,22500 +81644,both interview and exam,male,6,NA,white,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81645,both interview and exam,female,52,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,FALSE,100000 +81646,both interview and exam,male,0,9,black,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81647,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +81648,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +81649,both interview and exam,female,19,NA,mexican american,1,237,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,70000 +81650,both interview and exam,male,9,NA,mexican american,1,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,30000 +81651,both interview and exam,male,2,NA,white,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81652,both interview and exam,male,0,0,black,2,0,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81653,both interview and exam,male,14,NA,mexican american,1,173,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,NA +81654,both interview and exam,male,67,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81655,interview only,male,80,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +81656,both interview and exam,male,14,NA,other,2,175,NA,NA,FALSE,FALSE,0.5,7,NA,NA,NA,TRUE,2500 +81657,both interview and exam,male,3,NA,white,2,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +81658,both interview and exam,female,2,NA,other hispanic,2,25,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,87500 +81659,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,separated,no,FALSE,7500 +81660,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,22500 +81661,both interview and exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +81662,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +81663,both interview and exam,female,9,NA,mexican american,2,116,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,12500 +81664,both interview and exam,female,51,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,60000 +81665,both interview and exam,male,36,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +81666,both interview and exam,female,37,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,NA +81667,both interview and exam,female,19,NA,black,2,229,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,50000 +81668,both interview and exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +81669,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,30000 +81670,both interview and exam,female,15,NA,asian,2,181,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,NA +81671,both interview and exam,male,65,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,40000 +81672,both interview and exam,female,33,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,separated,no,TRUE,12500 +81673,both interview and exam,female,2,NA,white,1,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81674,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,22500 +81675,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +81676,both interview and exam,female,14,NA,other hispanic,1,173,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +81677,both interview and exam,male,60,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,FALSE,87500 +81678,both interview and exam,male,17,NA,black,1,213,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +81679,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81680,both interview and exam,female,18,NA,mexican american,1,222,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,70000 +81681,both interview and exam,female,42,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,3,married,no,FALSE,87500 +81682,both interview and exam,female,6,NA,other hispanic,1,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +81683,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +81684,both interview and exam,female,2,NA,white,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81685,both interview and exam,male,12,NA,white,1,153,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81686,both interview and exam,female,55,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,70000 +81687,both interview and exam,male,13,NA,mexican american,1,168,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +81688,both interview and exam,female,3,NA,other,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81689,both interview and exam,female,18,NA,white,1,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,22500 +81690,both interview and exam,male,1,14,white,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81691,both interview and exam,male,9,NA,white,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +81692,both interview and exam,female,17,NA,black,2,214,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,60000 +81693,both interview and exam,female,7,NA,black,2,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +81694,both interview and exam,female,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +81695,both interview and exam,female,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,unable to ascertain,TRUE,40000 +81696,both interview and exam,female,3,NA,asian,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81697,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +81698,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81699,both interview and exam,female,19,NA,black,2,238,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,60000 +81700,both interview and exam,female,30,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +81701,both interview and exam,male,52,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81702,both interview and exam,male,6,NA,other,1,76,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81703,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81704,both interview and exam,male,45,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81705,both interview and exam,male,9,NA,white,2,112,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +81706,both interview and exam,male,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81707,both interview and exam,male,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +81708,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,2500 +81709,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +81710,both interview and exam,female,3,NA,white,1,38,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,100000 +81711,both interview and exam,female,32,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +81712,both interview and exam,male,66,NA,other hispanic,2,NA,TRUE,TRUE,FALSE,TRUE,55,NA,4,married,NA,TRUE,60000 +81713,both interview and exam,female,16,NA,black,1,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,22500 +81714,both interview and exam,female,58,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81715,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,NA +81716,both interview and exam,female,11,NA,other,2,142,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +81717,both interview and exam,male,35,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +81718,both interview and exam,male,1,18,white,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81719,both interview and exam,male,43,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,40000 +81720,both interview and exam,male,11,NA,mexican american,1,144,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,70000 +81721,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +81722,both interview and exam,female,47,NA,black,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,100000 +81723,both interview and exam,male,1,16,other hispanic,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81724,both interview and exam,male,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +81725,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,no,TRUE,100000 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american,2,150,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +81736,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81737,both interview and exam,male,70,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,60000 +81738,both interview and exam,female,15,NA,mexican american,2,188,NA,NA,FALSE,TRUE,12.5,9,NA,NA,NA,FALSE,40000 +81739,interview only,female,13,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81740,both interview and exam,male,21,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,4,never_married,NA,TRUE,22500 +81741,both interview and exam,male,43,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +81742,both interview and exam,male,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81743,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,FALSE,TRUE,55,NA,2,widowed,NA,TRUE,22500 +81744,both interview and exam,female,5,NA,white,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81745,both interview and exam,male,16,NA,black,1,204,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +81746,both interview and exam,female,8,NA,black,1,98,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81747,both interview and exam,male,1,15,black,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81748,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +81749,both interview and exam,male,0,1,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81750,both interview and exam,female,22,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,22500 +81751,both interview and exam,female,17,NA,mexican american,1,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +81752,both interview and exam,male,41,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +81753,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81754,both interview and exam,female,16,NA,black,1,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81755,both interview and exam,male,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81756,both interview and exam,male,2,NA,white,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81757,both interview and exam,male,10,NA,black,2,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,17500 +81758,both interview and exam,male,14,NA,black,1,172,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +81759,both interview and exam,male,9,NA,black,2,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +81760,both interview and exam,female,36,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,no,FALSE,22500 +81761,both interview and exam,female,1,14,black,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81762,both interview and exam,female,22,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,no,TRUE,NA +81763,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,30000 +81764,both interview and exam,male,74,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +81765,both interview and exam,male,17,NA,other hispanic,1,211,FALSE,NA,FALSE,FALSE,0.5,9,NA,NA,NA,FALSE,50000 +81766,both interview and exam,male,32,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81767,interview only,female,57,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,60000 +81768,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +81769,both interview and exam,male,4,NA,asian,1,51,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,87500 +81770,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,2,married,NA,FALSE,NA +81771,both interview and exam,male,18,NA,white,2,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +81772,both interview and exam,male,49,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,FALSE,30000 +81773,both interview and exam,male,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +81774,both interview and exam,male,0,3,other,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81775,both interview and exam,male,17,NA,white,2,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +81776,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,no,TRUE,7500 +81777,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,70000 +81778,both interview and exam,male,18,NA,black,1,221,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81779,both interview and exam,female,63,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,7500 +81780,both interview and exam,male,22,NA,mexican american,2,NA,TRUE,TRUE,FALSE,TRUE,17.5,NA,3,never_married,NA,TRUE,40000 +81781,both interview and exam,male,50,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81782,both interview and exam,male,17,NA,asian,1,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +81783,both interview and exam,male,44,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +81784,both interview and exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +81785,both interview and exam,female,70,NA,other hispanic,2,NA,FALSE,NA,FALSE,NA,55,NA,1,widowed,NA,TRUE,12500 +81786,both interview and exam,female,1,20,other hispanic,2,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81787,both interview and exam,male,34,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,40000 +81788,both interview and exam,male,0,6,white,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81789,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +81790,both interview and exam,female,8,NA,asian,1,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +81791,both interview and exam,male,1,21,white,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81792,interview only,male,49,NA,white,NA,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +81793,both interview and exam,male,4,NA,mexican american,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81794,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +81795,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,TRUE,70000 +81796,both interview and exam,female,8,NA,black,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +81797,both interview and exam,female,74,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,40000 +81798,both interview and exam,male,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,22500 +81799,both interview and exam,male,10,NA,other,2,130,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +81800,both interview and exam,male,7,NA,black,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,2500 +81801,both interview and exam,male,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,100000 +81802,both interview and exam,male,30,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,never_married,NA,TRUE,100000 +81803,both interview and exam,male,18,NA,asian,1,225,FALSE,NA,FALSE,FALSE,3,13,NA,NA,NA,TRUE,2500 +81804,both interview and exam,female,14,NA,black,1,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81805,both interview and exam,female,21,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,yes,TRUE,22500 +81806,both interview and exam,female,32,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,no,TRUE,70000 +81807,both interview and exam,male,0,4,black,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81808,both interview and exam,female,18,NA,mexican american,2,218,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +81809,both interview and exam,male,40,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81810,both interview and exam,male,11,NA,other,2,140,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +81811,interview only,female,2,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81812,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +81813,both interview and exam,female,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,60000 +81814,both interview and exam,male,67,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81815,both interview and exam,male,75,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,12500 +81816,both interview and exam,female,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,12500 +81817,both interview and exam,male,6,NA,black,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,50000 +81818,both interview and exam,male,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +81819,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,17500 +81820,both interview and exam,male,65,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +81821,both interview and exam,male,0,9,other hispanic,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81822,both interview and exam,female,51,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +81823,both interview and exam,male,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +81824,both interview and exam,male,78,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +81825,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,22500 +81826,both interview and exam,female,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +81827,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81828,both interview and exam,female,45,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81829,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,separated,no,TRUE,40000 +81830,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +81831,both interview and exam,female,72,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +81832,interview only,male,80,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +81833,both interview and exam,male,72,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81834,both interview and exam,male,33,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,50000 +81835,both interview and exam,female,47,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,NA +81836,both interview and exam,female,36,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +81837,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,unable to ascertain,TRUE,17500 +81838,both interview and exam,male,5,NA,other,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81839,both interview and exam,male,13,NA,other hispanic,1,160,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +81840,both interview and exam,male,6,NA,asian,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81841,both interview and exam,female,11,NA,white,1,133,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +81842,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,40000 +81843,both interview and exam,male,19,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +81844,both interview and exam,male,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,70000 +81845,both interview and exam,male,75,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81846,both interview and exam,female,19,NA,mexican american,1,232,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,7500 +81847,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +81848,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,4,never_married,no,TRUE,100000 +81849,both interview and exam,female,44,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,22500 +81850,both interview and exam,male,67,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81851,both interview and exam,male,73,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81852,both interview and exam,male,1,15,mexican american,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81853,both interview and exam,male,17,NA,asian,1,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +81854,both interview and exam,male,38,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +81855,both interview and exam,female,27,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,17500 +81856,both interview and exam,male,7,NA,other hispanic,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +81857,both interview and exam,male,5,NA,mexican american,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,40000 +81858,both interview and exam,female,22,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +81859,both interview and exam,male,0,8,white,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81860,both interview and exam,male,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +81861,both interview and exam,female,14,NA,white,2,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81862,interview only,female,20,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,7500 +81863,both interview and exam,male,56,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +81864,both interview and exam,male,17,NA,white,2,208,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +81865,both interview and exam,male,42,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81866,both interview and exam,female,53,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,separated,NA,TRUE,12500 +81867,both interview and exam,male,57,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,40000 +81868,both interview and exam,female,2,NA,other hispanic,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81869,both interview and exam,female,9,NA,other hispanic,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +81870,interview only,female,37,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,unable to ascertain,TRUE,100000 +81871,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +81872,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,30000 +81873,interview only,male,62,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,45,NA,5,never_married,NA,TRUE,100000 +81874,both interview and exam,male,3,NA,white,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81875,both interview and exam,female,70,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,17500 +81876,both interview and exam,male,9,NA,black,2,115,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +81877,both interview and exam,female,44,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81878,both interview and exam,male,7,NA,asian,2,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81879,both interview and exam,male,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +81880,both interview and exam,female,8,NA,mexican american,1,99,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +81881,both interview and exam,male,9,NA,mexican american,2,120,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,87500 +81882,both interview and exam,female,36,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,3,living_with_partner,no,FALSE,2500 +81883,both interview and exam,male,19,NA,white,2,237,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,40000 +81884,both interview and exam,male,6,NA,white,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,2500 +81885,both interview and exam,female,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,NA +81886,both interview and exam,male,47,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81887,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,12500 +81888,both interview and exam,male,0,10,asian,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81889,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,yes,TRUE,7500 +81890,both interview and exam,female,67,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +81891,both interview and exam,female,28,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,no,TRUE,100000 +81892,both interview and exam,male,16,NA,white,2,194,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81893,both interview and exam,male,30,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,TRUE,50000 +81894,both interview and exam,female,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,30000 +81895,both interview and exam,female,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +81896,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,22500 +81897,both interview and exam,female,12,NA,other hispanic,2,155,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,17500 +81898,both interview and exam,female,29,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,unable to ascertain,TRUE,30000 +81899,both interview and exam,male,55,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +81900,both interview and exam,female,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +81901,both interview and exam,male,0,6,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +81902,both interview and exam,male,6,NA,white,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +81903,both interview and exam,male,30,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +81904,both interview and exam,female,47,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,never_married,NA,TRUE,70000 +81905,both interview and exam,male,15,NA,black,2,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,60000 +81906,both interview and exam,male,8,NA,mexican american,2,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +81907,both interview and exam,male,13,NA,black,2,157,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +81908,both interview and exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81909,both interview and exam,female,18,NA,black,2,224,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +81910,both interview and exam,male,30,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,60000 +81911,both interview and exam,male,13,NA,black,1,161,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +81912,both interview and exam,male,6,NA,mexican american,2,82,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,NA +81913,both interview and exam,female,18,NA,mexican american,1,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 +81914,both interview and exam,male,15,NA,other,1,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81915,both interview and exam,male,6,NA,asian,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81916,both interview and exam,male,6,NA,white,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +81917,both interview and exam,male,14,NA,black,1,169,NA,NA,FALSE,FALSE,7.5,7,NA,NA,NA,TRUE,22500 +81918,interview only,female,19,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,17.5,14,NA,NA,NA,TRUE,7500 +81919,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +81920,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81921,both interview and exam,female,14,NA,black,2,180,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,7500 +81922,both interview and exam,female,9,NA,white,2,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +81923,both interview and exam,male,35,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +81924,both interview and exam,female,10,NA,mexican american,2,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,30000 +81925,both interview and exam,male,23,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,never_married,NA,TRUE,50000 +81926,both interview and exam,male,12,NA,white,1,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +81927,both interview and exam,female,5,NA,other hispanic,2,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +81928,both interview and exam,male,2,NA,mexican american,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +81929,both interview and exam,female,15,NA,mexican american,2,188,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +81930,both interview and exam,male,18,NA,other hispanic,2,228,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,30000 +81931,both interview and exam,male,6,NA,white,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81932,both interview and exam,female,24,NA,black,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,living_with_partner,yes,TRUE,50000 +81933,both interview and exam,female,80,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,7500 +81934,both interview and exam,female,61,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81935,both interview and exam,female,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,7500 +81936,both interview and exam,female,1,23,other hispanic,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81937,interview only,male,15,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +81938,interview only,female,34,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,unable to ascertain,TRUE,87500 +81939,both interview and exam,female,5,NA,mexican american,2,69,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,FALSE,12500 +81940,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,NA +81941,both interview and exam,male,17,NA,other hispanic,2,209,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +81942,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,30000 +81943,both interview and exam,female,13,NA,other,2,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +81944,both interview and exam,female,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,60000 +81945,both interview and exam,female,53,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,87500 +81946,both interview and exam,female,30,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,no,FALSE,NA +81947,both interview and exam,female,0,1,black,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81948,both interview and exam,male,17,NA,mexican american,1,207,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,NA +81949,both interview and exam,male,47,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,87500 +81950,both interview and exam,male,52,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +81951,both interview and exam,male,14,NA,mexican american,2,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,100000 +81952,both interview and exam,male,56,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +81953,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,40000 +81954,both interview and exam,male,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81955,both interview and exam,male,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +81956,both interview and exam,female,35,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,no,TRUE,87500 +81957,both interview and exam,male,49,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +81958,both interview and exam,female,2,NA,white,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81959,both interview and exam,male,77,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81960,both interview and exam,male,17,NA,asian,2,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +81961,both interview and exam,female,13,NA,white,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +81962,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +81963,both interview and exam,male,3,NA,asian,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +81964,both interview and exam,male,0,8,black,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81965,both interview and exam,male,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +81966,both interview and exam,female,31,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +81967,both interview and exam,female,30,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,2500 +81968,both interview and exam,female,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,7500 +81969,both interview and exam,male,58,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,NA,TRUE,40000 +81970,both interview and exam,female,53,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +81971,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +81972,interview only,female,6,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,30000 +81973,both interview and exam,female,0,9,black,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81974,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81975,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +81976,both interview and exam,female,6,NA,white,2,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +81977,both interview and exam,female,16,NA,mexican american,1,196,NA,NA,FALSE,FALSE,12.5,9,NA,NA,NA,TRUE,22500 +81978,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +81979,both interview and exam,male,53,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +81980,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +81981,both interview and exam,female,3,NA,other hispanic,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81982,both interview and exam,female,55,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +81983,both interview and exam,female,72,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81984,both interview and exam,female,6,NA,asian,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81985,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +81986,both interview and exam,male,6,NA,other hispanic,1,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +81987,both interview and exam,female,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,TRUE,40000 +81988,both interview and exam,male,65,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +81989,both interview and exam,female,46,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,12500 +81990,both interview and exam,female,3,NA,white,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81991,both interview and exam,female,12,NA,black,2,147,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +81992,both interview and exam,female,51,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,NA,TRUE,87500 +81993,both interview and exam,male,43,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,NA,TRUE,100000 +81994,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,60000 +81995,both interview and exam,male,74,NA,asian,2,NA,TRUE,TRUE,FALSE,TRUE,45,NA,4,married,NA,TRUE,NA +81996,both interview and exam,male,48,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,FALSE,NA +81997,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +81998,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,NA +81999,both interview and exam,male,3,NA,black,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82000,both interview and exam,male,6,NA,white,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +82001,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,TRUE,60000 +82002,both interview and exam,female,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +82003,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +82004,both interview and exam,male,1,15,black,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82005,both interview and exam,male,68,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,30000 +82006,both interview and exam,male,46,NA,black,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,TRUE,50000 +82007,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +82008,both interview and exam,female,9,NA,mexican american,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +82009,interview only,female,8,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +82010,interview only,female,36,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,unable to ascertain,TRUE,100000 +82011,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,87500 +82012,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82013,both interview and exam,female,2,NA,black,2,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82014,both interview and exam,male,12,NA,white,2,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +82015,interview only,female,70,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,50000 +82016,both interview and exam,female,3,NA,white,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82017,both interview and exam,female,18,NA,white,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +82018,both interview and exam,male,11,NA,black,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +82019,both interview and exam,male,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +82020,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +82021,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +82022,both interview and exam,female,10,NA,black,1,122,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +82023,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,40000 +82024,both interview and exam,female,7,NA,black,1,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +82025,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +82026,both interview and exam,male,68,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82027,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,30000 +82028,both interview and exam,female,46,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +82029,both interview and exam,female,6,NA,other hispanic,2,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82030,both interview and exam,female,3,NA,asian,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82031,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +82032,both interview and exam,male,8,NA,black,2,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +82033,both interview and exam,male,7,NA,black,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +82034,both interview and exam,male,13,NA,other hispanic,2,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +82035,interview only,female,1,23,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82036,both interview and exam,male,17,NA,other hispanic,2,206,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +82037,both interview and exam,female,43,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,30000 +82038,both interview and exam,male,0,4,white,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82039,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,never_married,no,TRUE,22500 +82040,both interview and exam,male,7,NA,black,2,90,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +82041,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +82042,both interview and exam,male,17,NA,black,2,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +82043,both interview and exam,female,57,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,35,NA,5,married,NA,TRUE,70000 +82044,both interview and exam,female,9,NA,asian,2,112,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +82045,both interview and exam,female,6,NA,mexican american,2,82,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,2500 +82046,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,3,widowed,NA,TRUE,87500 +82047,both interview and exam,male,64,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +82048,both interview and exam,male,6,NA,black,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +82049,both interview and exam,female,15,NA,black,2,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +82050,both interview and exam,female,19,NA,other hispanic,2,228,FALSE,NA,FALSE,FALSE,7.5,13,NA,NA,NA,FALSE,NA +82051,both interview and exam,female,42,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,no,TRUE,100000 +82052,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +82053,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +82054,both interview and exam,male,8,NA,mexican american,2,107,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,7500 +82055,both interview and exam,male,77,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +82056,both interview and exam,male,76,NA,other hispanic,1,NA,TRUE,FALSE,FALSE,TRUE,55,NA,4,married,NA,TRUE,30000 +82057,both interview and exam,female,36,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +82058,both interview and exam,male,34,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,100000 +82059,both interview and exam,female,29,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +82060,both interview and exam,female,25,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +82061,both interview and exam,female,80,NA,black,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,widowed,NA,TRUE,NA +82062,both interview and exam,female,54,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +82063,both interview and exam,male,10,NA,white,1,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,NA +82064,both interview and exam,female,6,NA,other hispanic,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +82065,both interview and exam,male,3,NA,white,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +82066,both interview and exam,female,15,NA,white,2,183,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +82067,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,7500 +82068,both interview and exam,male,44,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,living_with_partner,NA,FALSE,30000 +82069,both interview and exam,male,10,NA,black,2,132,NA,NA,FALSE,FALSE,NA,5,NA,NA,NA,TRUE,50000 +82070,both interview and exam,male,18,NA,white,2,218,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +82071,both interview and exam,female,16,NA,white,1,201,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +82072,both interview and exam,male,14,NA,white,2,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +82073,both interview and exam,male,19,NA,white,1,237,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +82074,both interview and exam,female,1,14,white,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +82075,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82076,both interview and exam,female,5,NA,other,2,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82077,both interview and exam,male,40,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,87500 +82078,both interview and exam,male,8,NA,mexican american,1,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +82079,both interview and 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interview and exam,male,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,7500 +82090,both interview and exam,female,48,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,40000 +82091,both interview and exam,female,69,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,30000 +82092,interview only,female,62,NA,other hispanic,NA,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,divorced,NA,FALSE,12500 +82093,both interview and exam,male,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +82094,interview only,male,27,NA,other hispanic,NA,NA,FALSE,NA,FALSE,FALSE,3,NA,1,never_married,NA,FALSE,40000 +82095,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,70000 +82096,both interview and exam,male,16,NA,black,2,199,NA,NA,FALSE,FALSE,3,11,NA,NA,NA,TRUE,40000 +82097,both interview and exam,male,6,NA,asian,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +82098,both interview and exam,male,64,NA,mexican 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exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82108,both interview and exam,male,61,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,NA,FALSE,50000 +82109,both interview and exam,male,19,NA,white,2,235,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,22500 +82110,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,7500 +82111,both interview and exam,male,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82112,both interview and exam,female,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +82113,both interview and exam,male,69,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +82114,both interview and exam,female,14,NA,black,1,174,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +82115,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,17500 +82116,both interview and exam,female,18,NA,mexican 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exam,male,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82136,both interview and exam,male,0,7,asian,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82137,both interview and exam,male,17,NA,mexican american,2,210,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +82138,both interview and exam,male,61,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82139,both interview and exam,female,39,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,NA +82140,both interview and exam,male,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +82141,both interview and exam,female,12,NA,asian,1,151,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +82142,both interview and exam,male,10,NA,white,1,122,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +82143,both interview and exam,male,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82144,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,7500 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exam,female,12,NA,white,2,146,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +82155,both interview and exam,female,3,NA,white,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +82156,interview only,female,10,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +82157,both interview and exam,male,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +82158,both interview and exam,male,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82159,both interview and exam,female,7,NA,black,2,90,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +82160,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,30000 +82161,both interview and exam,female,39,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +82162,both interview and exam,male,68,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82163,both interview and exam,female,51,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +82164,both interview and exam,male,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,7500 +82165,both interview and exam,male,44,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +82166,both interview and exam,male,6,NA,black,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,2500 +82167,both interview and exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82168,interview only,male,17,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +82169,both interview and exam,female,58,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,never_married,NA,FALSE,NA +82170,both interview and exam,female,62,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,25,NA,5,married,NA,TRUE,100000 +82171,both interview and exam,male,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +82172,both interview and exam,male,29,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +82173,both interview and exam,female,63,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82174,both interview and exam,male,10,NA,other,2,124,NA,NA,FALSE,FALSE,0.5,3,NA,NA,NA,TRUE,2500 +82175,both interview and exam,male,9,NA,white,1,115,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +82176,both interview and exam,male,57,NA,black,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,TRUE,70000 +82177,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +82178,both interview and exam,male,0,7,mexican american,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +82179,both interview and exam,female,16,NA,asian,1,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +82180,both interview and exam,male,4,NA,mexican american,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82181,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,70000 +82182,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 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exam,female,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +82212,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +82213,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82214,both interview and exam,female,9,NA,mexican american,2,115,NA,NA,FALSE,FALSE,3,3,NA,NA,NA,FALSE,30000 +82215,both interview and exam,female,9,NA,other,2,112,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +82216,both interview and exam,male,52,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +82217,interview only,male,23,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +82218,both interview and exam,female,15,NA,white,2,182,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,60000 +82219,both interview and exam,male,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,NA +82220,both interview and exam,female,9,NA,white,2,109,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,2500 +82221,both interview and exam,male,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82222,both interview and exam,male,3,NA,other hispanic,2,45,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,50000 +82223,both interview and exam,male,27,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,87500 +82224,both interview and exam,female,20,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,50000 +82225,both interview and exam,male,55,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +82226,both interview and exam,male,80,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +82227,both interview and exam,female,79,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82228,both interview and exam,male,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,60000 +82229,both interview and exam,male,16,NA,white,2,194,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +82230,both interview and exam,male,60,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,30000 +82231,both interview and exam,male,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +82232,both interview and exam,male,15,NA,mexican american,1,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,70000 +82233,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,17500 +82234,both interview and exam,male,1,13,other,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82235,both interview and exam,female,73,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +82236,both interview and exam,male,79,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +82237,both interview and exam,female,4,NA,black,1,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +82238,both interview and exam,female,66,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +82239,both interview and exam,male,10,NA,other hispanic,1,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 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exam,female,17,NA,black,2,208,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,70000 +82250,both interview and exam,male,19,NA,mexican american,2,230,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,60000 +82251,both interview and exam,male,10,NA,mexican american,2,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +82252,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,unable to ascertain,TRUE,30000 +82253,both interview and exam,female,19,NA,black,1,234,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,40000 +82254,both interview and exam,male,77,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +82255,both interview and exam,male,0,1,white,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +82256,both interview and exam,male,6,NA,white,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +82257,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,40000 +82258,both interview and exam,female,50,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,50000 +82259,both interview and exam,male,20,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,7500 +82260,both interview and exam,male,9,NA,white,2,120,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +82261,both interview and exam,male,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +82262,both interview and exam,female,1,13,mexican american,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +82263,both interview and exam,female,9,NA,black,1,117,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +82264,both interview and exam,male,5,NA,other hispanic,1,72,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +82265,both interview and exam,male,8,NA,white,2,98,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +82266,interview only,female,0,10,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82267,both interview and exam,female,6,NA,white,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +82268,both interview and exam,female,4,NA,white,1,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82269,both interview and exam,female,23,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,never_married,no,FALSE,NA +82270,both interview and exam,male,49,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,40000 +82271,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,30000 +82272,both interview and exam,female,0,2,mexican american,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82273,both interview and exam,female,1,23,white,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82274,both interview and exam,male,5,NA,other hispanic,2,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82275,both interview and exam,female,42,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,unable to ascertain,TRUE,30000 +82276,interview only,female,51,NA,other,NA,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +82277,both interview and exam,female,71,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +82278,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +82279,both interview and exam,female,13,NA,black,2,164,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,NA +82280,both interview and exam,male,6,NA,white,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82281,both interview and exam,female,41,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +82282,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,30000 +82283,both interview and exam,male,48,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,FALSE,NA +82284,both interview and exam,female,8,NA,white,2,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +82285,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +82286,both interview and exam,female,14,NA,white,1,178,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +82287,both interview and exam,female,19,NA,other hispanic,1,233,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,12500 +82288,both interview and exam,male,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +82289,both interview and exam,female,0,11,mexican american,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82290,both interview and exam,male,43,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,2,married,NA,TRUE,40000 +82291,both interview and exam,female,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82292,interview only,female,3,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82293,both interview and exam,female,4,NA,asian,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82294,both interview and exam,male,8,NA,asian,1,103,NA,NA,FALSE,FALSE,3,3,NA,NA,NA,TRUE,7500 +82295,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 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interview and exam,male,43,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,NA +82307,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +82308,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +82309,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,7500 +82310,both interview and exam,female,19,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +82311,both interview and exam,male,17,NA,black,1,209,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +82312,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,22500 +82313,both interview and exam,female,15,NA,black,1,192,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +82314,both interview and exam,male,13,NA,other hispanic,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,17500 +82315,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82316,both interview and exam,male,73,NA,mexican american,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +82317,both interview and exam,male,7,NA,mexican american,2,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,30000 +82318,both interview and exam,male,27,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,never_married,NA,TRUE,2500 +82319,both interview and exam,female,35,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +82320,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +82321,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82322,interview only,male,41,NA,other,NA,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +82323,both interview and exam,male,2,NA,black,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82324,both interview and exam,male,6,NA,other hispanic,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +82325,both interview and exam,male,39,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +82326,both interview and exam,male,10,NA,white,2,133,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +82327,both interview and exam,female,2,NA,black,1,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +82328,both interview and exam,male,2,NA,black,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +82329,both interview and exam,male,45,NA,white,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,NA,TRUE,100000 +82330,both interview and exam,female,51,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82331,both interview and exam,male,16,NA,asian,2,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,NA +82332,both interview and exam,male,0,1,asian,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82333,both interview and exam,female,10,NA,other hispanic,2,127,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,NA +82334,both interview and exam,female,50,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,7500 +82335,both interview and exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +82336,both interview and exam,male,28,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,NA +82337,both interview and exam,female,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,30000 +82338,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,30000 +82339,both interview and exam,male,0,10,mexican american,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +82340,both interview and exam,female,19,NA,asian,1,229,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +82341,both interview and exam,male,16,NA,black,2,199,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +82342,both interview and exam,female,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,50000 +82343,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82344,both interview and exam,male,70,NA,black,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,divorced,NA,TRUE,30000 +82345,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +82346,both interview and exam,female,51,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,separated,NA,TRUE,40000 +82347,both interview and exam,male,2,NA,mexican american,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82348,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,yes,TRUE,87500 +82349,both interview and exam,female,11,NA,white,2,137,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +82350,both interview and exam,female,7,NA,other hispanic,1,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +82351,both interview and exam,male,65,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,30000 +82352,both interview and exam,male,0,11,mexican american,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +82353,both interview and exam,male,53,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +82354,both interview and exam,female,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82355,both interview and exam,female,70,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +82356,both interview and exam,female,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82357,both interview and exam,female,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,30000 +82358,both interview and exam,male,13,NA,other,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,17500 +82359,both interview and exam,male,48,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +82360,both interview and exam,female,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +82361,both interview and exam,male,17,NA,mexican american,2,206,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +82362,both interview and exam,male,7,NA,other hispanic,1,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,17500 +82363,both interview and exam,male,38,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +82364,both interview and exam,female,0,9,white,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82365,both interview and exam,female,17,NA,black,1,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +82366,both interview and exam,female,6,NA,mexican american,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +82367,both interview and exam,male,35,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,NA,FALSE,2500 +82368,both interview and exam,female,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +82369,both interview and exam,female,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,no,TRUE,30000 +82370,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,2500 +82371,both interview and exam,male,6,NA,white,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82372,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,30000 +82373,both interview and exam,female,16,NA,white,2,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +82374,both interview and exam,male,9,NA,other hispanic,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,60000 +82375,both interview and exam,male,49,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,50000 +82376,both interview and exam,male,41,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +82377,both interview and exam,male,19,NA,black,1,236,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +82378,both interview and exam,male,17,NA,asian,1,208,FALSE,NA,FALSE,FALSE,0.5,10,NA,NA,NA,TRUE,17500 +82379,interview only,male,30,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +82380,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82381,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,45,NA,2,widowed,NA,TRUE,NA +82382,both interview and exam,male,3,NA,black,2,37,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82383,both interview and exam,male,62,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,30000 +82384,both interview and exam,female,65,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82385,both interview and exam,male,2,NA,white,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82386,both interview and exam,female,2,NA,black,1,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82387,both interview and exam,female,0,4,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82388,both interview and exam,male,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +82389,both interview and exam,female,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,40000 +82390,both interview and exam,male,0,6,asian,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82391,both interview and exam,male,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +82392,both interview and exam,male,6,NA,black,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +82393,both interview and exam,male,20,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +82394,both interview and exam,male,18,NA,mexican american,2,216,FALSE,NA,FALSE,FALSE,12.5,14,NA,NA,NA,TRUE,NA +82395,both interview and exam,female,25,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,50000 +82396,both interview and exam,male,19,NA,white,1,237,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,50000 +82397,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +82398,both interview and exam,male,31,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +82399,both interview and exam,male,2,NA,other,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82400,both interview and exam,male,16,NA,black,2,197,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +82401,both interview and exam,female,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +82402,both interview and exam,male,65,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,87500 +82403,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82404,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,22500 +82405,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +82406,both interview and exam,male,73,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,NA,never_married,NA,TRUE,12500 +82407,both interview and exam,male,44,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +82408,both interview and exam,male,18,NA,white,2,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 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exam,male,16,NA,white,2,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,50000 +82419,both interview and exam,female,1,23,asian,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82420,both interview and exam,male,35,NA,black,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,TRUE,40000 +82421,both interview and exam,female,13,NA,asian,1,164,NA,NA,FALSE,TRUE,12.5,7,NA,NA,NA,TRUE,100000 +82422,both interview and exam,female,10,NA,asian,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +82423,both interview and exam,male,56,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82424,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,7500 +82425,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,50000 +82426,both interview and exam,male,24,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +82427,both interview and exam,male,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,70000 +82428,both interview and exam,female,26,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,40000 +82429,both interview and exam,male,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82430,both interview and exam,female,24,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,40000 +82431,interview only,female,0,8,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +82432,both interview and exam,male,60,NA,black,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,TRUE,NA +82433,both interview and exam,male,1,16,black,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82434,both interview and exam,female,70,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,NA +82435,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +82436,both interview and exam,male,61,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,married,NA,FALSE,87500 +82437,both interview and exam,female,1,12,other hispanic,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +82438,both interview and exam,male,7,NA,black,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +82439,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82440,both interview and exam,female,63,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82441,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,87500 +82442,both interview and exam,female,0,7,mexican american,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82443,both interview and exam,male,11,NA,black,1,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,7500 +82444,both interview and exam,male,2,NA,black,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82445,both interview and exam,female,52,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82446,both interview and exam,male,66,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +82447,both interview and exam,female,15,NA,other,1,192,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +82448,both interview and exam,male,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +82449,both interview and exam,male,42,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,12500 +82450,both interview and exam,female,34,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,no,FALSE,7500 +82451,both interview and exam,female,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,17500 +82452,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,87500 +82453,both interview and exam,female,0,4,other,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82454,both interview and exam,female,37,NA,other,1,NA,FALSE,NA,FALSE,FALSE,3,NA,4,married,no,TRUE,30000 +82455,both interview and exam,female,25,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,NA +82456,both interview and exam,female,0,6,black,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82457,both interview and exam,male,10,NA,mexican american,1,130,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,17500 +82458,both interview and exam,female,3,NA,other,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82459,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +82460,both interview and exam,female,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,NA +82461,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +82462,both interview and exam,male,36,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,30000 +82463,both interview and exam,female,48,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +82464,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,50000 +82465,both interview and exam,female,44,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,living_with_partner,no,TRUE,12500 +82466,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,70000 +82467,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,30000 +82468,both interview and exam,male,11,NA,other,2,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,70000 +82469,both interview and exam,male,1,18,asian,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82470,both interview and exam,male,13,NA,black,1,158,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +82471,interview only,female,22,NA,other hispanic,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,unable to ascertain,TRUE,12500 +82472,both interview and exam,male,13,NA,white,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +82473,interview only,female,8,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 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exam,male,32,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,60000 +82484,both interview and exam,male,14,NA,black,1,174,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +82485,both interview and exam,female,33,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,TRUE,40000 +82486,both interview and exam,male,40,NA,other,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,TRUE,30000 +82487,both interview and exam,male,21,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +82488,both interview and exam,male,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82489,both interview and exam,male,41,NA,asian,2,NA,TRUE,TRUE,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +82490,interview only,male,0,1,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82491,both interview and exam,male,14,NA,black,1,171,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +82492,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +82493,both interview and exam,female,9,NA,white,2,120,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +82494,both interview and exam,female,19,NA,mexican american,1,236,FALSE,NA,FALSE,FALSE,NA,13,NA,NA,NA,TRUE,NA +82495,both interview and exam,female,51,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +82496,both interview and exam,male,8,NA,mexican american,1,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +82497,both interview and exam,female,11,NA,mexican american,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +82498,both interview and exam,male,18,NA,mexican american,1,227,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,FALSE,NA +82499,both interview and exam,male,12,NA,black,2,152,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +82500,both interview and exam,male,38,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +82501,both interview and exam,female,38,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,married,no,TRUE,100000 +82502,both interview and exam,female,16,NA,white,2,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +82503,both interview and exam,female,16,NA,black,1,193,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +82504,both interview and exam,male,73,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,3,separated,NA,FALSE,7500 +82505,both interview and exam,male,8,NA,white,1,103,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +82506,both interview and exam,female,1,17,mexican american,1,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82507,both interview and exam,male,72,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +82508,both interview and exam,male,5,NA,black,1,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82509,both interview and exam,male,63,NA,mexican american,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +82510,both interview and exam,male,0,11,white,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82511,both interview and exam,female,9,NA,other,1,109,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +82512,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +82513,both interview and exam,male,47,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +82514,both interview and exam,female,4,NA,asian,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82515,both interview and exam,male,11,NA,asian,2,144,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +82516,both interview and exam,male,11,NA,mexican american,1,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,2500 +82517,both interview and exam,male,59,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,50000 +82518,both interview and exam,male,13,NA,mexican american,1,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,70000 +82519,both interview and exam,female,25,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,30000 +82520,both interview and exam,female,16,NA,mexican american,1,201,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,70000 +82521,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +82522,both interview and exam,male,15,NA,other hispanic,2,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,50000 +82523,both interview and exam,female,7,NA,other hispanic,2,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +82524,both interview and exam,female,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +82525,both interview and exam,male,6,NA,other,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +82526,both interview and exam,female,2,NA,mexican american,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82527,both interview and exam,female,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +82528,both interview and exam,male,15,NA,other hispanic,2,191,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +82529,both interview and exam,female,35,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,separated,no,TRUE,60000 +82530,both interview and exam,female,4,NA,asian,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82531,both interview and exam,female,36,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,no,FALSE,NA +82532,both interview and exam,male,16,NA,asian,1,194,NA,NA,FALSE,FALSE,0.5,9,NA,NA,NA,TRUE,17500 +82533,both interview and exam,female,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,NA +82534,both interview and exam,male,18,NA,mexican american,1,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,40000 +82535,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +82536,both interview and exam,female,49,NA,other,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +82537,interview only,female,25,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,unable to ascertain,TRUE,12500 +82538,both interview and exam,female,26,NA,mexican 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exam,male,78,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +82652,both interview and exam,male,73,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,87500 +82653,both interview and exam,male,7,NA,white,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +82654,both interview and exam,female,18,NA,other hispanic,1,219,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +82655,both interview and exam,female,75,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,widowed,NA,TRUE,50000 +82656,both interview and exam,male,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +82657,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +82658,both interview and exam,male,6,NA,black,1,80,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,17500 +82659,both interview and exam,female,0,6,black,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82660,both interview and exam,female,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +82661,both 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interview and exam,male,6,NA,white,1,72,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82691,both interview and exam,male,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,NA +82692,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,7500 +82693,both interview and exam,male,6,NA,mexican american,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +82694,both interview and exam,female,8,NA,mexican american,2,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +82695,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +82696,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,12500 +82697,both interview and exam,female,18,NA,asian,1,227,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +82698,both interview and exam,male,74,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +82699,both interview and 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exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +82719,both interview and exam,female,35,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +82720,both interview and exam,male,58,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,50000 +82721,both interview and exam,male,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82722,both interview and exam,male,6,NA,mexican american,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +82723,both interview and exam,female,74,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +82724,both interview and exam,female,28,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +82725,both interview and exam,female,17,NA,asian,1,208,FALSE,NA,FALSE,TRUE,3,11,NA,NA,NA,TRUE,7500 +82726,both interview and exam,female,16,NA,black,1,197,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +82727,both interview and exam,male,77,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82728,both interview and exam,female,18,NA,mexican american,2,218,FALSE,NA,FALSE,FALSE,17.5,11,NA,NA,NA,TRUE,NA +82729,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,17500 +82730,both interview and exam,female,14,NA,asian,1,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +82731,both interview and exam,female,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,40000 +82732,both interview and exam,male,9,NA,white,2,116,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +82733,both interview and exam,female,40,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +82734,interview only,male,29,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +82735,both interview and exam,female,23,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,living_with_partner,no,TRUE,40000 +82736,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +82737,both interview and exam,female,66,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +82738,both interview and exam,male,3,NA,black,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +82739,both interview and exam,female,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +82740,both interview and exam,male,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,40000 +82741,both interview and exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,7500 +82742,both interview and exam,female,52,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,divorced,NA,TRUE,100000 +82743,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,NA +82744,both interview and exam,male,0,0,black,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82745,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,60000 +82746,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,50000 +82747,both interview and exam,female,0,10,white,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +82748,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +82749,both interview and exam,male,64,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82750,both interview and exam,female,27,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,living_with_partner,no,TRUE,50000 +82751,both interview and exam,female,0,5,white,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +82752,interview only,male,34,NA,black,NA,NA,FALSE,NA,FALSE,FALSE,3,NA,4,married,NA,TRUE,30000 +82753,both interview and exam,female,2,NA,other hispanic,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82754,both interview and exam,female,0,1,white,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82755,both interview and exam,female,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,40000 +82756,both interview and exam,male,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +82757,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +82758,both interview and exam,male,52,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +82759,both interview and exam,male,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +82760,both interview and exam,female,2,NA,other,1,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82761,both interview and exam,female,0,11,white,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82762,both interview and exam,female,26,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,17500 +82763,both interview and exam,female,12,NA,white,2,150,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,60000 +82764,interview only,male,6,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +82765,interview only,male,80,NA,white,NA,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +82766,both interview and exam,female,48,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,NA,FALSE,30000 +82767,both interview and exam,male,7,NA,black,2,85,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +82768,both interview and exam,female,9,NA,black,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +82769,both interview and exam,female,55,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,TRUE,100000 +82770,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +82771,both interview and exam,male,41,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +82772,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +82773,both interview and exam,male,67,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,FALSE,22500 +82774,both interview and exam,female,19,NA,black,2,235,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,2500 +82775,both interview and exam,male,57,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,NA,FALSE,NA +82776,both interview and exam,male,37,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,TRUE,30000 +82777,both interview and exam,female,2,NA,mexican american,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +82778,both interview and exam,male,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +82779,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82780,both interview and exam,female,28,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,no,FALSE,NA +82781,both interview and exam,female,17,NA,mexican american,2,210,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +82782,both interview and exam,male,53,NA,other 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exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,87500 +82812,both interview and exam,male,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +82813,both interview and exam,female,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,50000 +82814,both interview and exam,male,44,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,NA +82815,interview only,female,80,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,35,NA,5,widowed,NA,TRUE,7500 +82816,both interview and exam,male,66,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82817,both interview and exam,female,16,NA,other,2,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +82818,both interview and exam,male,11,NA,black,1,136,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +82819,both interview and exam,male,2,NA,black,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82820,both interview and exam,male,78,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 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exam,male,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,87500 +82841,both interview and exam,male,45,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +82842,both interview and exam,female,68,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +82843,both interview and exam,female,14,NA,black,2,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,70000 +82844,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +82845,both interview and exam,male,64,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +82846,both interview and exam,female,33,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,2,married,no,TRUE,50000 +82847,both interview and exam,female,5,NA,white,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82848,both interview and exam,female,18,NA,other,1,219,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +82849,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 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exam,female,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,widowed,NA,TRUE,50000 +82860,both interview and exam,male,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82861,both interview and exam,female,6,NA,black,1,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82862,both interview and exam,female,39,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,no,TRUE,100000 +82863,interview only,female,69,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +82864,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +82865,both interview and exam,female,14,NA,other hispanic,1,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,17500 +82866,interview only,female,5,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82867,both interview and exam,female,41,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,no,TRUE,100000 +82868,both interview and exam,male,78,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,12500 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interview and exam,female,76,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +82880,both interview and exam,female,6,NA,other hispanic,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +82881,both interview and exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82882,both interview and exam,female,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,widowed,NA,TRUE,NA +82883,both interview and exam,female,1,17,asian,2,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82884,both interview and exam,male,18,NA,white,1,228,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +82885,both interview and exam,male,10,NA,black,1,131,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +82886,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +82887,both interview and exam,female,7,NA,black,1,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +82888,both interview and exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +82889,both interview and exam,male,66,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +82890,both interview and exam,female,2,NA,mexican american,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82891,both interview and exam,male,11,NA,other hispanic,1,137,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +82892,both interview and exam,male,0,9,mexican american,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82893,both interview and exam,female,15,NA,white,2,189,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +82894,both interview and exam,male,49,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,NA +82895,both interview and exam,female,57,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,100000 +82896,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +82897,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,17500 +82898,both interview and exam,male,66,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,TRUE,30000 +82899,both interview and exam,male,66,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,3,married,NA,TRUE,NA +82900,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82901,both interview and exam,male,68,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,living_with_partner,NA,FALSE,12500 +82902,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,FALSE,TRUE,0.5,NA,5,married,no,TRUE,100000 +82903,both interview and exam,female,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,50000 +82904,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82905,both interview and exam,male,7,NA,mexican american,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +82906,both interview and exam,male,72,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,30000 +82907,both interview and exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +82908,both interview and exam,male,6,NA,black,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +82909,both interview and exam,male,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,50000 +82910,both interview and exam,male,7,NA,white,1,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +82911,both interview and exam,female,5,NA,other,1,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +82912,both interview and exam,female,10,NA,white,1,131,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +82913,both interview and exam,male,28,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,60000 +82914,both interview and exam,male,5,NA,white,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82915,both interview and exam,male,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +82916,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +82917,both interview and exam,male,42,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,100000 +82918,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,22500 +82919,both interview and exam,male,6,NA,white,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +82920,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +82921,both interview and exam,male,9,NA,other hispanic,1,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,30000 +82922,both interview and exam,male,1,16,other,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82923,both interview and exam,male,6,NA,white,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +82924,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +82925,both interview and exam,male,38,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 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exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +82946,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +82947,both interview and exam,female,0,4,white,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82948,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +82949,both interview and exam,male,67,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +82950,interview only,female,2,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82951,both interview and exam,female,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +82952,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82953,both interview and exam,male,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82954,interview only,male,4,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82955,interview 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exam,male,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +82965,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,no,FALSE,50000 +82966,both interview and exam,male,1,20,black,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +82967,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +82968,both interview and exam,female,79,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,17500 +82969,both interview and exam,male,54,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +82970,both interview and exam,male,60,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,2500 +82971,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,70000 +82972,both interview and exam,female,1,16,asian,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82973,both interview and exam,male,1,15,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82974,both interview and exam,male,54,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,NA +82975,both interview and exam,female,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +82976,both interview and exam,male,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +82977,both interview and exam,female,10,NA,other,2,122,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +82978,both interview and exam,female,41,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,never_married,no,TRUE,87500 +82979,both interview and exam,male,12,NA,other hispanic,1,148,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +82980,both interview and exam,female,12,NA,black,1,150,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +82981,both interview and exam,female,0,1,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82982,both interview and exam,female,74,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,widowed,NA,FALSE,60000 +82983,both interview and exam,female,10,NA,asian,1,133,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +82984,both interview and exam,female,12,NA,mexican american,1,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,30000 +82985,both interview and exam,female,6,NA,black,1,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +82986,both interview and exam,male,15,NA,asian,1,185,NA,NA,FALSE,FALSE,3,10,NA,NA,NA,TRUE,7500 +82987,both interview and exam,male,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +82988,both interview and exam,female,6,NA,mexican american,2,78,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +82989,both interview and exam,male,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,12500 +82990,both interview and exam,male,66,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,FALSE,17500 +82991,both interview and exam,female,16,NA,black,2,203,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +82992,both interview and exam,female,17,NA,white,1,216,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +82993,both interview and exam,female,8,NA,black,1,99,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +82994,interview only,female,6,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,50000 +82995,both interview and exam,male,72,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82996,both interview and exam,female,37,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,married,no,FALSE,30000 +82997,both interview and exam,female,53,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82998,both interview and exam,male,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +82999,both interview and exam,male,35,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,4,married,NA,FALSE,70000 +83000,both interview and exam,male,7,NA,mexican american,2,89,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +83001,both interview and exam,female,43,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,no,TRUE,100000 +83002,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +83003,both interview and exam,female,32,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +83004,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,30000 +83005,both interview and exam,male,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,60000 +83006,both interview and exam,female,71,NA,other hispanic,1,NA,TRUE,FALSE,FALSE,TRUE,55,NA,4,divorced,NA,TRUE,17500 +83007,both interview and exam,male,66,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,22500 +83008,both interview and exam,female,10,NA,black,2,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +83009,both interview and exam,male,24,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,never_married,NA,FALSE,NA +83010,both interview and 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interview and exam,male,4,NA,white,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +83347,both interview and exam,female,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +83348,both interview and exam,male,15,NA,other hispanic,2,183,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,40000 +83349,both interview and exam,female,18,NA,black,1,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,40000 +83350,both interview and exam,male,15,NA,mexican american,1,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +83351,both interview and exam,male,63,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +83352,both interview and exam,male,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +83353,both interview and exam,female,0,9,other,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +83354,both interview and exam,female,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +83355,both interview and exam,male,15,NA,black,1,184,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,87500 +83356,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,17500 +83357,both interview and exam,male,10,NA,black,1,133,NA,NA,FALSE,FALSE,3,3,NA,NA,NA,TRUE,30000 +83358,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +83359,both interview and exam,female,60,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,NA +83360,both interview and exam,male,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +83361,interview only,male,31,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +83362,both interview and exam,female,31,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,no,TRUE,50000 +83363,both interview and exam,male,28,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +83364,both interview and exam,male,46,NA,mexican 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exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +83383,both interview and exam,female,12,NA,white,1,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +83384,both interview and exam,male,9,NA,white,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +83385,both interview and exam,female,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,7500 +83386,interview only,male,34,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +83387,interview only,male,48,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,NA,never_married,NA,TRUE,17500 +83388,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +83389,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,70000 +83390,both interview and exam,male,71,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +83391,both interview and exam,female,56,NA,mexican 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exam,male,2,NA,black,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +83420,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,70000 +83421,both interview and exam,female,2,NA,white,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +83422,both interview and exam,male,1,13,black,2,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +83423,both interview and exam,male,66,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,FALSE,100000 +83424,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +83425,both interview and exam,female,34,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,yes,TRUE,100000 +83426,both interview and exam,female,56,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +83427,both interview and exam,female,27,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +83428,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,30000 +83429,both interview and exam,female,61,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,married,NA,FALSE,30000 +83430,both interview and exam,female,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +83431,both interview and exam,female,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +83432,both interview and exam,male,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +83433,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +83434,both interview and exam,female,1,23,other hispanic,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +83435,both interview and exam,female,8,NA,black,2,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,7500 +83436,both interview and exam,male,76,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,60000 +83437,both interview and 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+83731,ur_albumin_mg_l,5.3 +83731,ur_creatinine_mg_dl,114 +83731,ur_creatinine_umol_l,10077.6 +83731,ur_albumin_creatinine_ratio,4.65 diff --git a/content/complete/detailed/01_custom_functions.qmd b/content/complete/detailed/01_custom_functions.qmd new file mode 100644 index 0000000..b49353b --- /dev/null +++ b/content/complete/detailed/01_custom_functions.qmd @@ -0,0 +1,667 @@ +--- +title: "Custom functions" +format: html +editor_options: + chunk_output_type: console +--- + +## A simple custom function + +In this notebook, you will learn how to define your own functions. + +We will start with a very simple function, that we will call `add_one()`, which will add 1 to any value it is given. + +The simplest way to define `add_one()` is + +```{r} +add_one <- function(x) { + x + 1 +} +``` + +The code that is run when you "call" your function is shown inside the curly parentheses. To "call" a function is to write the name of the function, followed by some parentheses inside which you provide a value for your argument, such as: + +```{r} +add_one(5) +``` + +What is happening when you call `add_one(5)` is that `x` is temporarily being assigned the value `5`, and then the code inside the curly parentheses `x + 1` is run, with the result being returned as the output of the function. + + +Note that by default, any custom R function you create will automatically return the final result that is computed. So for example, if your function contains multiple computations that would have output, such as the version below, when you call `add_one(5)`, you will only see the final computed result (i.e., you will see the output of `x + 1` but not `x - 1`. + + +```{r} +add_one <- function(x) { + x - 1 + x + 1 +} +``` + +```{r} +add_one(5) +``` + + + +For this reason, it is common to explicitly provide a "return statement", which specifies what you want the output of your function to be. In the example below, we explicitly specify that we want the output of `add_one()` to be the output of the first computation `x - 1`, rather than the second one, `x + 1`. + +```{r} +add_one <- function(x) { + return(x - 1) + x + 1 +} +``` + +```{r} +add_one(5) +``` + + +## The general syntax of a custom function + +The general syntax of a custom function is shown below: + +```{r} +#| eval: false +fn_name <- function(arg) { + # code involve arg + return(object) +} +``` + + + + +## Exercise + +Write a function called "cube" that returns the cubic of the argument + + +```{r} +cube <- function(value) { + cubed_value = value^3 + return(cubed_value) +} +``` + +```{r} +cube(value = 3) +``` + + + +## Multiple arguments + +To create a function with multiple arguments, you need to provide two arguments inside the function definition, separated by a comma. The function below has two arguments: `x` and `y`: + +```{r} +add_xy <- function(x, y) { + x + 2*y +} +``` + +When you call this `add_xy()`, you can then specify a value for each argument, separated by a comma: + +```{r} +add_xy(2, 5) +``` + +When you have multiple arguments, funny things can start to happen when you don't name your arguments. + +What do you think will happen if you *first* provide a named argument for the *second* argument `y` by specifying `y = 2`, and then provide an unnamed argument afterwards? + +```{r} +add_xy(y = 2, 5) +``` + +R will be clever and it will first apply the named arguments by assigning `y` to the value 2, and then it will start at the beginning of the argument list and fill in the remaining argument, so `x` will be assigned to the value `5`. + +However, so that your code is easy to read and you don't have to remember which arguments appear in which order, it is good practice to always name your arguments. + +```{r} +add_xy(x = 2, y = 5) +``` + +Note that when you provide named arguments, it technically doesn't matter which order you provide them in (but this is *not* true when you don't provide named arguments!) + + +```{r} +add_xy(y = 5, x = 2) +``` + + +Again, note that even when you provide named arguments in a function call (e.g., in `add_xy(y = 5, x = 2)`), you are *not* defining a global version of the arguments, i.e., there is no `y` defined: + +```{r} +#| error: true +y +``` + +Before we move on, what do you think will happen when you call `add_xy()` without any arguments inside the parentheses? + + +```{r} +#| error: true +add_xy() +``` + +You get an error, because we haven't specified any *default values* for the arguments which the function will use when an argument is not provided. + +### Default values + + +To provide *default* values for your arguments, you can assign the argument inside the function definition. In the example below, both `x` and `y` are given the default values of 1. + +```{r} +add_xy <- function(x = 1, y = 1) { + x + 2*y +} +``` + +Now if we run `add_xy()` without any arguments, we don't get an error! We get the same thing that we would have got if we had run `add_xy(x = 1, y = 1)`. + +```{r} +add_xy() +``` + +What do you think will happen if we run `add_xy(4)`? + +```{r} +add_xy(4) +``` + +What happens is that the value `4` is assigned to the *first* argument, `x`, and the argument `y` is assigned it's default value of `1`. + + +Similarly, if you provide a value for the argument `y`, the default value for `x` will be used: + +```{r} +add_xy(y = 3) +``` + + + +### Exercise + + +Without using the `mean()` function, write a function called `my_mean()` that takes four values as its arguments and computes their mean. Ensure that each argument has a default of 0. Use your function to compute the mean of the values 4, 5, 2, 1. + + +#### Solution + +```{r} +my_mean <- function(a = 0, b = 0, c = 0, d = 0) { + return((a + b + c + d) / 4) +} +``` + +Note that when we run this function it is taking four separate arguments (rather than a vector, as the original mean function does): + +```{r} +my_mean(4, 5, 2, 1) +``` + +You can define a function that instead takes a single vector as its argument: + +```{r} +my_mean_vec <- function(vec) { + return(sum(vec) / length(vec)) +} +``` + +and then to run this function, you provide a vector by wrapping the four values inside `c()`: + +```{r} +my_mean_vec(c(4, 5, 2, 1)) +``` + +What happens if you apply your original `my_mean()` function to this vector? + +```{r} +my_mean(c(4, 5, 2, 1)) +``` + +This is equivalent to assigning the argument `a = c(4, 5, 2, 1)`, and then not providing any values for the `b`, `c`, and `d` arguments (so their default values are used). So the above code is equivalent to: + +```{r} +# (a + b + c + d) / 4 + +(c(4, 5, 2, 1) + 0 + 0 + 0) / 4 +``` + +The fact that we haven't told any of our functions what type of object the arguments should be means that the function will simply take whatever object it is given and try and run the code. In the next lesson, you will learn how to specify options for arguments using if/else statements and by providing several argument defaults. + + + +## If/else statements + +First, let's explain what an if statement and an if/else statement is. + +### If statements + +Let's start with a stand-alone "if" statement. + +The following code defines a variable `a`, and then runs some *conditional* code that is only run if the condition `a == 1` is `TRUE`. In this case, since `a` contains the value `5`, the condition `a == 1` is `FALSE`, and so the code `"a is 1"` is not run. + +```{r} +a <- 5 + +if (a == 1) { + "a is 1" +} + +``` + + +If instead, we assign `a` to `1`, then the code `"a is 1"` will be run: + + +```{r} +a <- 1 + +if (a == 1) { + "a is 1" +} +``` + +There is nothing special about the string value provided, it is just a simple piece of code. We could instead just run code containing a numeric value: + +```{r} +a <- 1 + +if (a == 1) { + 3 +} +``` + + +Or even define a variable inside our "if" statement: + + +```{r} +a <- 1 + +if (a == 1) { + y <- 3 +} +``` + +Note that unlike for a function, this variable will have been defined in our "global" environment. + +```{r} +y +``` + + +### Else statemenets + +While you can use a stand-alone "if" statement, you can also provide an "else" statement. The "else" part of the "if/else" statement provides some code that will be run if the "if" condition is *not* `TRUE`. For example, the following code will first ask if `a` equals 1, and if so, will assign `y <- 3`. If not, the statement will not run the `y <- 3` code and will instead assign `y <- 9`: + +```{r} +a <- 3 +if (a == 1) { + # if condition is true, run the following: + y <- 3 +} else { + # if condition is not true, run the following: + y <- 9 +} +``` + +```{r} +# check what y was assigned to +y +``` + + + +### Using "if" statements to provide custom errors when inappropriate arguments are provided + +The following uses an "if" statement to add a "stop condition" that throws an error when the argument `a` is either non-numeric or does not have a length of 1: + +```{r} +my_mean <- function(a = 0, b = 0, c = 0, d = 0) { + if (!is.numeric(a) | (length(a) != 1)) { + stop("'a' must be a numeric value of length 1") + } + + return((a + b + c + d) / 4) +} +``` + + + +### Exercise + + +1. Use an if/else statement that checks whether the value in a variable called `age` is at least 18. If so, your statement should return the character value of "You are eligible to vote" and if not, your statement should return "You are not eligible to vote" + + +```{r} +age <- 21 +if (age >= 18) { + "You are eligible to vote" +} else { + "You are not eligible to vote" +} +``` + + +2. Write a function that computes the area of a circle (`area = pi * radius^2`) given the radius as its argument and throws an error if a non-numeric or a negative radius value is given. + +```{r} +circle_area <- function(radius) { + if (!is.numeric(radius) | radius < 0) { + stop("'radius' must be a non-negative numeric value") + } + area <- pi * radius^2 + return(area) +} +``` + +```{r} +#| error: true +# the following should throw an error: +circle_area("4") +circle_area(-4) +``` + + + +## Default argument options + +```{r} +add_xy <- function(x = 1, y = 1, output_type = c("numeric", "character")) { + # this line will set the default value of output_type to be "numeric" + # and will only allow options provided in the default vector + output_type <- match.arg(output_type) + + # stop condition if x or y are not numeric + if (!is.numeric(x) | !is.numeric(y)) { + stop("'x' and 'y' must be numeric") + } + + # computing my result + result <- x + 2 * y + + # returning result in the format specified by output_type + if (output_type == "numeric") { + return(result) + } else if (output_type == "character") { + return(as.character(result)) + } + +} +``` + +```{r} +add_xy(x = 2, y = 3, output_type = "character") +``` + +```{r} +add_xy(2, 3) +``` + +```{r} +#| error: true +add_xy(2, 3, output_type = "charcter") +``` + + +### Exercise + +Write a function called `calculate_area()` that will calculate the area of the shape specified in the argument `shape`, which has options "circle", "square", and "triangle". Your function will need to have the following additional arguments: + +- `radius` for computing the area of a circle (pi * radius^2), + +- `side` for computing the area of a square (side^2), + +- `base` and `height` for computing the area of a triangle (height * base / 2). + +Recall that arguments that are not *always* required should have a default value. Your function should throw an error when you fail to provide the arguments that are needed for the value specified in the `shape` argument. + + +```{r} +calculate_area <- function(shape = c("circle", "square", "triangle"), + radius = NA, + side = NA, + base = NA, + height = NA) { + shape = match.arg(shape) + # error statements + if (shape == "circle" & is.na(radius)) { + stop("'radius' required for 'circle' shape") + } + if (shape == "square" & is.na(side)) { + stop("'side' required for 'square' shape") + } + if (shape == "triangle" & (is.na(base) | is.na(height))) { + stop("'base' and 'height' required for 'triangle' shape") + } + + # compute the area + if (shape == "circle") { + area <- pi * radius^2 + } else if (shape == "square") { + area <- side^2 + } else if (shape == "triangle") { + area <- base * height / 2 + } + + return(area) + +} +``` + + + +## Tidy evaluation for writing tidyverse-style functions + +Sometimes you want to write a function whose argument is a column of a data frame without quotes (i.e., in the tidyverse style) so that you can use it in a tidyverse function. Unfortunately this is more complicated than it should be, but in this lesson, you'll learn how to implement "tidy evaluation" so that your function can take tidyverse-style column-name arguments to use in tidyverse functions. + +First, we have to load in the tidyverse. And we will also load in the demographics data file from the NHANES study. You will need to make sure that your data/ folder and demographics.csv file are saved in the same location as this quarto document, and that your working directory is appropriate (if not, you can choose Session > Set Working Directory > To Source File Location). If you're using a project, then your working directory should already be set to the correct location. + +```{r} +library(tidyverse) +demographics <- read_csv("data/demographics.csv") +``` + +```{r} +head(demographics) +``` + +So a reminder of the kinds of things we will often do within the tidyverse is creating figures, such as boxplots, using ggplot2 based on a data frame. Notice that when we refer to the variables from our data frame in the context of the tidyverse (including ggplot2), we do *not* use quotes around the column names: + + +```{r} +demographics |> ggplot() + + geom_boxplot(aes(x = served_active_duty_us, + y = age_years)) +``` + +Here is another example using a different variable from the data (`language_english`), where we also add a "classic" theme, and some custom axis labels. + +```{r} +demographics |> ggplot() + + geom_boxplot(aes(x = language_english, + y = age_years)) + + theme_classic() + + labs(x = "English language", + y = "Age (years)") +``` + +Let's try and turn this into a function so we can create boxplots comparing the age distribution across all of the levels of any categorical varaible in our data that we like without having to copy-and-paste the code over and over again. + +In this first attempt, we use `variable_name` as the argument: + +```{r} +createBoxplots <- function(variable_name) { + demographics |> ggplot() + + geom_boxplot(aes(x = variable_name, + y = age_years)) +} +``` + +But this yields an error where R claims that it doesn't know what `language_english` is. Which to be fair, since it isn't the name of a variable in our space, it doesn't! + +```{r} +#| error: true +createBoxplots(language_english) +``` + +We can try and run it with a character/string verion of the column name by wrapping it in quotes, but then we just get one boxplot for the string value `"language_english"`, which ggplot doesn't know is supposed to be a column from our data. + +```{r} +createBoxplots("language_english") +``` + +The issue is that ggplot wants us to refer to the column names without strings, but our custom function doesn't know how to find our column name variable that we provide. + +Fortunately, there is an easy fix, which involves something called "tidy evaluation", which involves wrapping the argument inside two sets of curly parentheses inside the body of our function, which indicates to R that this argument should be used in the tidyverse style, without quotes: + +```{r} +createBoxplots <- function(variable_name) { + demographics |> ggplot() + + geom_boxplot(aes(x = {{ variable_name }}, + y = age_years)) +} +``` + +And now it works: + +```{r} +createBoxplots(language_english) +``` + + +Let's use our function on a few different columns to make sure: + +```{r} +createBoxplots(marital_status) +``` + +Notice that in the marital status plot, the x-axis tick labels are all smooshed into eachother. We deal with this by adding a theme layer to our plot which modifies the properties of the `axis.text.x` theme element. We can add this either to output of `createBoxplots()` (which outputs a ggplot2 object itself): + +```{r} +createBoxplots(marital_status) + + theme(axis.text.x = element_text(angle = 90, + hjust = 1, + vjust = 0.5)) +``` + +Or we can apply it to all plots created with our `createBoxplot()` function by including it in the function body: + +```{r} +createBoxplots <- function(variable_name) { + demographics |> ggplot() + + geom_boxplot(aes(x = {{ variable_name }}, + y = age_years)) + + theme_classic() + + theme(axis.text.x = element_text(angle = 90, + hjust = 1, + vjust = 0.5)) +} +``` + + +```{r} +# now this version will have the 90-degree axis text +createBoxplots(marital_status) +``` + + +#### Adding labels using column variable names + +Sometimes you want to take the name of the column name that you are providing in the argument and use the actual text from the column name to create a nice label. The last line in the version of our function below converts the `variable_name` to a text-based object and uses the `str_replace` function from the tidyverse to replace the underscore with a space: + +```{r} +createBoxplots <- function(variable_name) { + demographics |> ggplot() + + geom_boxplot(aes(x = {{ variable_name }}, + y = age_years)) + + theme_classic() + + theme(axis.text.x = element_text(angle = 90, + hjust = 1, + vjust = 0.5)) + + labs(x = str_replace(as_label(enquo(variable_name)), "_", " "), + y = "Age (years)") +} +``` + + +```{r} +createBoxplots(marital_status) +``` + +#### Tip: Using patchwork to patch together plots + +The patchwork library can be used to create custom grids of ggplot objects (be sure to expand your plot window if the plots aren't showing up properly): + +```{r} +library(patchwork) +createBoxplots(language_english) + createBoxplots(marital_status) +``` + +```{r} +(createBoxplots(language_english) + createBoxplots(marital_status)) / createBoxplots(pregnant) +``` + + +### Exercise + +Create a function called createOrderedBars() that takes a categorical column from `demographics` as its argument and creates a bar chart for the average age for each level of the variable. + +Challenge mode: Arrange the bars in ascending order, and provide an argument called `ascending` that allows the user to specify whether or not the bars will be arranged in ascending order. + + + +#### Solution + +Note that you'll want to use `geom_col()` instead of `geom_bar()` to create bar charts where the bars have the specific height provided in the y-variable. + +```{r} +createOrderedBars <- function(variable_name) { + demographics |> + # group by the column provided + group_by({{ variable_name }}) |> + # compute the mean age + summarize(mean_age = mean(age_years)) |> + # create the bar plot + ggplot() + + geom_col(aes(x = {{ variable_name }}, + y = mean_age)) +} +``` + +```{r} +createOrderedBars(marital_status) +``` + +#### Challenge solution + +To arrange the bars in ascending order of `mean_age`, you first need to convert the categorical variable itself to a factor whose levels are in the order that you want the bars to appear. You can do this by arranging the rows of your data frame in order of `mean_age` and then using `fct_inorder()` to convert your variable to a factor with levels match the increasing order of `mean_age`. + +```{r} +createOrderedBars <- function(variable_name) { + demographics |> + # group by the column provided + group_by({{ variable_name }}) |> + # compute the mean age + summarize(mean_age = mean(age_years)) |> + + # OPTIONAL CODE FOR CHALLENGE MODE: + # arrange in increasing order of mean_age + arrange(mean_age) |> + # modify selected_variable so that it is a factor whose levels are in + # increasing order of mean_age + mutate(selected_variable = fct_inorder({{ variable_name }})) |> + + # create the bar plot + ggplot() + + geom_col(aes(x = selected_variable, + y = mean_age)) +} +``` + + diff --git a/content/complete/detailed/02_iteration_purrr.qmd b/content/complete/detailed/02_iteration_purrr.qmd new file mode 100644 index 0000000..37403a2 --- /dev/null +++ b/content/complete/detailed/02_iteration_purrr.qmd @@ -0,0 +1,289 @@ +--- +title: "Iteration with purrr" +format: html +editor_options: + chunk_output_type: console +--- + +The purpose of this lesson is to learn how to iteratively apply functions to all elements contained within an object, such as all columns in a data frame, or all entries in a vector. + + +Since we will be continuing with the demographics NHANES data we were using previously, we will first need to load in that dataset. To do that, we will also need to load the tidyverse library. + +Note that the "purrr" R package that we will be using in this lesson is *included* in the tidyverse package, so that it it not necessary to also load the purrr package separately. + +```{r} +library(tidyverse) +#library(purrr) +demographics <- read_csv("data/demographics.csv") +``` + + +To start with, the function that we want to iterate first is the `n_distinct()` function from the tidyverse. + +Recall that to pull up the help page for a function, you can use the following syntax: + +```{r} +?n_distinct +``` + +`n_distinct()` counts the number of unique values in a vector. For example, if we want to apply `n_distinct()` to count the number of unique values in the `gender` column from the `demographics` data frame, we can first extract it as a vector using `demographics$gender` and then apply `n_distinct()` to it: + +```{r} +n_distinct(demographics$gender) +``` + +What if we want to do this simultaneously to all columns. Rather than repeating our code above over and over again, we can instead use the `map()` function. + +The `map()` function takes two arguments. The first is the object whose elements that we want to iterate over and the second is the function that we want to apply to each element in our object. + +When our object is a data frame, the elements being iterated over are the *columns* of the data frame. + +The code below uses the `map()` function to apply `n_distinct()` to every column of the `demographics` data frame simultanesouly: + +```{r} +map(demographics, n_distinct) +``` + + +The output of the `map()` function is a list (more on that in a moment). + +The following code shows another example, this time applying the `exp()` function to all entries/elements in a simple numeric vector: + +```{r} +map(c(4, 5, 6), exp) +``` + + +Again, the output of the `map()` function is a list. + +### Lists + + +Let's talk about lists. Lists, like vectors, correspond to a collection of values contained in a single object. + +You can use the `list()` function to define a list, for example: + +```{r} +my_list <- list(1, 4, 7) +``` + +You can extract elements from a list just as you would from a vector, using the square bracket notation. The code below extracts the third element from `my_list`: + +```{r} +my_list[3] +``` + +However, note that the output above is also a list itself. + +If you want to extract the actual object/value contained within the third element of the list, then you need to use double square parentheses: + +```{r} +my_list[[3]] +``` + +Note that unlike vectors, lists are not vectorized. This means that you cannot conduct operations like adding 1 to a list. For a vector, this would add 1 to each element of the vector. But for a list, you just get an error: + +```{r} +#| error: true +my_list + 1 +``` + +Why would we ever prefer lists to vectors? The reason is that lists are infinitely more flexible than vectors. While all entries in a vector must be a *single value* of the *same type*, entries of a list can be anything. + +For example, the code below creates a list that contains three entries: the head of the `demographics` data frame, the value 2, and a vector of the character values "a" and "b": + +```{r} +my_complex_list <- list(head(demographics), 2, c("a", "b")) +my_complex_list +``` + +You can also create a *named* list when defining it as if you are defining argument names: + +```{r} +my_complex_list <- list(data = head(demographics), value = 2, vector = c("a", "b")) +my_complex_list +``` + + +### Exercise + +Use `map()` and `class()` to identify the type/class of each column in the demographics dataset, and extract the class of the `household_income` column. + +#### Solution + +```{r} +demographics_class <- map(demographics, class) +``` + +The `household_income` is the last column in the `demographics` data frame. There are several ways to extract it's class from the `demographics_class` list object. + +First is using numeric positional indexing inside square parentheses. Tip: You can use `ncol(demographics)` to extract the final column without having to actually know what integer position the final column corresponds to: + +```{r} +demographics_class[ncol(demographics)] +demographics_class[19] +``` + +You can also use named indexing, by providing the list element name as a *character* inside one or two square parentheses (depending if you want the output to be a list of length 1 or just the value contained in the list element): + +```{r} +demographics_class[["household_income"]] +``` + +And you can also use the `$` syntax with the list element name (without quotes). + +```{r} +demographics_class$household_income +``` + + +Note that these are the same techniques that you can use for extracting a column from a data frame. This is because a data frame is actually a special case of a list, where each element of the list is a vector corresponding to each column, and each of the vectors have the same length. + + + + + +## Using custom functions in purrr + + +To iterate using your own custom functions in a purrr `map()` function, you can define your function and provide it in the second argument of `map()`. For example, below, we define the `exp_plus_one()` function, and we then apply this function iteratively to each of the values in the vector `c(1, 4, 5)` using `map()`: + +```{r} + +exp_plus_one <- function(x) { + return(exp(x) + 1) +} + +map(c(1, 4, 5), exp_plus_one) +``` + +However, for simple functions like this one (e.g., functions that only involve a single line of code which is also the return statement), there is a shortcut that we can use which involves defining the function "on the fly" in the function argument of the `map()` function itself. + +The code below does the same thing as the code in the previous chunk, but it doesn't give the function a name. A temporary function defined inside an argument this way is called an *"anonymous function"*: + +```{r} +map(c(1, 4, 5), function(x) exp(x) + 1) +``` + +However, we can go one step further and forego the `function(x)` part entirely using what I call the "tilde-dot" shorthand syntax. Here, we use the tilde `~` symbol to "start" an anonymous function and we use a `.` to represent the argument of our anonymous function. The code below uses the tilde-dot shorthand syntax which is equivalent to the code in each of the chunks above, but is significantly more succinct. + +```{r} +# tilde-dot syntax +map(c(1, 4, 5), ~{exp(.) + 1}) +``` + +As another example of this shorthand syntax, we can use it to count the number of missing values in each column of the demographics data (which is defined/loaded in the first code chunk of this document). + +To decide what should go inside the `~{}`, I typically use a representative value to test out my code first. For example, below, I take a single column `demographics$pregnant`, and I write out the code that I want to apply to it: + +```{r} +sum(is.na(demographics$pregnant)) +``` + +Then I take this code and place it inside the body of `~{}` and replace the test column `demographics$pregnant` with a `.` to apply this code to *every* column: + +```{r} +map(demographics, ~{sum(is.na(.))}) +``` + +### Exercise + +Use the tilde-dot short-hand syntax to compute the number of values in each column that is equal to 1. Recall that if a vector has missing values, and you want to use `sum()`, you will want to provide an argument `na.rm = TRUE` to ignore missing values. + +#### Solution + +First, the code below does the long-form version which defines a function and then provides that function in the second argument of the `map()` function: + +```{r} +add_ones <- function(x) { + sum(x == 1, na.rm = TRUE) +} + +map(demographics, add_ones) +``` + +Then I make this more concise by taking the body of my `add_ones()` function above, and placing it inside `~{}`, and replace the `x` argument with a `.`: + +```{r} +map(demographics, ~{sum(. == 1, na.rm = TRUE)}) +``` + + + + + +## Alternative map functions for outputting doubles, characters and data frames + +Let's explore some alternative map functions that have different output types (i.e., they do not output a list). + +Recall our `map()` function previously that we used to count the number of missing values in each column of the demographics data. + +```{r} +map(demographics, ~sum(is.na(.))) +``` + +It turns out that a list may not be the most useful format for this information. For instance, perhaps it would be more helpful to create a numeric vector instead. + +### Outputting numeric vectors + +The `map_dbl()` function will output a "double" vector, where a double is a type of numeric value. Below, is the same code from above, but using `map_dbl()` outputs a *named* numeric/double vector, instead of a list (where the name of each element is inherited from the column names of the original data frame). + +```{r} +map_dbl(demographics, ~sum(is.na(.))) +``` + + +### Outputting character vectors + +If you are applying a function whose output is a character value (not a numeric value), such as `class()`, then you can use the `map_chr()` function to output a named *character* vector instead. + +```{r} +map_chr(demographics, class) +``` + + +### Outputting data frames + +One of the most versatile functions is the `map_df()` function, which outputs a data frame. The code below outputs the class of each column in a "wide" single-row data frame, where each column in the original data frame has its own column in the output here. + + + +```{r} +map_df(demographics, class) +``` + +Note that if you want your output to be in a "long" format, where you have one column for the output of your function, you need to have the function you are applying output a single-column tibble/data frame, and these values will then be stacked vertically as you iterate. + +```{r} +map_df(demographics, ~tibble(col_class = class(.))) +``` + + +You can provide an `.id` argument to include the original column names as a variable in the output data frame too: + +```{r} +map_df(demographics, ~tibble(col_class = class(.)), .id = "variable_name") +``` + +### Example + +This long-format is very useful if you want to create a plot, such as a bar chart for the number of missing values (recall that you will need to convert the `variable_name` column to a factor whose levels are in the order you want them to appear in your plot and you can add theme layers to customize the output of your plot). + +```{r} +map_df(demographics, + ~tibble(n_missing = sum(is.na(.))), + .id = "variable_name") |> + arrange(n_missing) |> + mutate(variable_name = fct_inorder(variable_name)) |> + ggplot() + + geom_col(aes(x = variable_name, y = n_missing)) + + scale_y_continuous(expand = c(0, 0)) + + theme_classic() + + theme(axis.text.x = element_text(angle = 90, + hjust = 1, + vjust = 0.5)) +``` + + + diff --git a/content/complete/detailed/03_across.qmd b/content/complete/detailed/03_across.qmd new file mode 100644 index 0000000..3027611 --- /dev/null +++ b/content/complete/detailed/03_across.qmd @@ -0,0 +1,198 @@ +--- +title: "Across" +format: html +editor_options: + chunk_output_type: console +--- + +In this lesson, we will introduce the `across()` function, which can be used to apply dplyr functions like mutate, summarize, select, etc to subsets of columns that satisfy certain criteria, such as to all numeric columns, or all columns that start with `age_`. + +We will continue working with the demographics data, so let's first load the tidyverse and load the demographics data object. + + +```{r} +library(tidyverse) +demographics <- read_csv("data/demographics.csv") +head(demographics) +``` + + +Let's suppose that our task is to convert all character columns of the demographics data to upper-case. The function that we are trying to apply is the `toupper()` function. + +```{r} +toupper("abc") +``` + + +Before introducing across, let's first see one way that we could do this using the `map()` functions that we have just learned (there are often multiple ways of doing the same thing): + +```{r} +# one way to convert all character columns to uppercase +# creating a boolean/logical vector for identifying character columns +character_cols <- map_chr(demographics, class) == "character" +# re-assinging the character columns to an upper-case version of themselves +demographics[character_cols] <- map_df(demographics[character_cols], toupper) +demographics +``` + +While this works, it is fairly convoluted, is hard to read, and involves defining an intermediate variable (`character_cols`) -- in the tidyverse style, it is generally recommended to *avoid* defining intermediate variables whenever possible. + + +Since the code above modified our demographics data, let's load it in again to revert `demographics` to the original unmodified version: + +```{r} +demographics <- read_csv("data/demographics.csv") +demographics +``` + +## Introducing across() + +We could instead do this kind of operation using a `mutate()` operation in conjunction with `across()`. + +First, if we were to conduct our uppercase operation for just one character column, say, `interview_examination`, then we could do this using a mutate function as follows: + +```{r} +# just for the interview_examination column +demographics |> mutate(interview_examination = toupper(interview_examination)) +``` + +To do this for *all* character columns, you need to provide `across()` to the argument of your mutate function. The `across()` function has two arguments: + +- The first argument is a "select statement" that specifies which columns you want to apply your function to. Since we want to apply our `toupper` function to all character columns, we use the `where()` function to provide a logical function, which, when applied to all columns, will only output `TRUE` for the character columns, resulting in them being selected for computation. + +- The second argument is the function name, `toupper`, that we want to apply to all columns that are selected as a result of the first argument. + +The result is that `toupper()` is applied to all columns where `is.character()` would result in `TRUE`: + +```{r} +demographics |> mutate(across(where(is.character), toupper)) +``` + +## More across examples + +### Add 100 to all `age_` columns + +Let's first look at another `mutate()` example, where this time, we want to add 100 to all columns whose name starts with `age_`. + +If we were to do this to just the `age_years` column, our code would look like: + + +```{r} +demographics |> mutate(age_years = age_years + 100) +``` + +To generalize this to all columns that start with `age_` using `across()`, we can use the `starts_with()` select helper, and apply the anonymous function `~{. + 100}`: + +```{r} +demographics |> mutate(across(starts_with("age_"), ~{. + 100})) +``` + +### Convert `born_usa` and `citizen_usa` to numeric (binary) columns using `ends_with()` + +The next example involves convert `born_usa` and `citizen_usa` to numeric (binary) columns. + + +```{r} +demographics |> select(born_usa, citizen_usa) +``` + + +Since both `born_usa` and `citizen_usa` end with `_usa` (and they are the only columns to do so), we can use the `ends_with()` select helper. In this case, to convert the logical `TRUE/FALSE` values to numeric `0/1` values, the function we are applying is `as.numeric()`. The code below uses `across()` to do this: + +```{r} +demographics |> mutate(across(ends_with("_usa"), as.numeric)) |> + print(width = Inf) +``` + +### Convert `born_usa` and `citizen_usa` to numeric (binary) columns using a vector of column names + +Suppose we had a vector of column names that we wanted to modify using `mutate()`: + +```{r} +selected_cols <- c("born_usa", "citizen_usa") +``` + +Then we could use `all_of(selected_cols)` in `across()` to apply the function to all columns listed in the `selected_cols` vector as follows: + +```{r} +demographics |> mutate(across(all_of(selected_cols), as.numeric)) |> + print(width = Inf) +``` + +We could also use `any_of(selected_cols)`: + +```{r} +demographics |> mutate(across(any_of(selected_cols), as.numeric)) |> + print(width = Inf) +``` + +The difference between the two, is that when using `all_of()` all columns in `selected_cols` must be included in the data, whereas this is not necessary for `any_of()`. For example, if one of our columns in `selected_cols` did not exist, then `all_of()` would throw an error, whereas `any_of()` would not: + + +```{r} +#| error: true +selected_cols <- c("born_usa", "citizen_usa", "abc") +demographics |> mutate(across(all_of(selected_cols), as.numeric)) +``` + +We could also use `any_of(selected_cols)`: + +```{r} +demographics |> mutate(across(any_of(selected_cols), as.numeric)) +``` + +## Select helpers summary + +So far we have seen the following "select helpers" that can be used to specify the columns inside `across()`: + +- `where()` -- across to all columns that satisfy a logical condition (`is.character`) + +- `starts_with()` and `ends_with()` -- across all columns that start or ends with a specified string + +- `all_of()` and `any_of()` -- across all columns whose names are contained in a character vector, where `all_of()` requires all columns in the vector be present. + +Another common select helper is `contains()` which can be used to select all columns that *contain* a specified string. + + +### Exercise + +a. For all columns that contain the word "education" (`education_youth` and `education`), add the number 5 to each value + +b. For all numeric columns, standardize the values by subtracting the mean and dividing by the standard deviation + +c. Compute the average age across all columns that start with `age_` + +d. Compute the total number of `TRUE` values in the `born_usa`, `citizen_usa`, and `language_english` columns + + +#### Solution + +a. + +```{r} +demographics |> mutate(across(contains("education"), ~. + 5)) |> + print(width = Inf) +``` + +b. + +```{r} +# standardize all numeric columns +demographics |> mutate(across(where(is.numeric), ~{(. - mean(., na.rm = TRUE)) / sd(., na.rm = TRUE)})) +``` + +c. + +```{r} +# compute average age across all age columns +demographics |> summarize(across(starts_with("age"), ~mean(., na.rm = TRUE))) +``` + +d. + +```{r} +# compute the total in the `born_usa`, `citizen_usa`, and `language_english` +demographics |> summarise(across(any_of(c("born_usa", "citizen_usa", "language_english")), + ~sum(., na.rm = TRUE))) +``` + diff --git a/content/complete/detailed/04_recoding_variables.qmd b/content/complete/detailed/04_recoding_variables.qmd new file mode 100644 index 0000000..8c073a2 --- /dev/null +++ b/content/complete/detailed/04_recoding_variables.qmd @@ -0,0 +1,142 @@ +--- +title: "Recoding variables using if_else and case_when" +format: html +editor_options: + chunk_output_type: console +--- + +```{r} +library(tidyverse) +demographics <- read_csv("data/demographics.csv") +demographics +``` + + +In this document, you will learn how to "recode" variables by replacing values in a variable with other values of your choice. The most common use-case is typically converting numerically-encoded variables to categorical/character versions, and vice versa. + +We will introduce two functions for doing this: + +- `if_else()` which can be used to create binary variables (variables with just two distinct values) based on a logical "condition" + +- `case_when()` which can be used to create variables with many different values. + +## if_else + +Consider, for example, the `interview_examination` column. This variable has two distinct values `"both interview and exam"` and `"interview only"`: + +```{r} +demographics |> count(interview_examination) +``` + +If we wanted to do an analysis involving this column, we might need to convert it to a numeric format. We can do that using `if_else()`. The code below uses `if_else()` to create a column called `interview_examination_numeric` that converts all values in `interview_examination` that are equal to `"both interview and exam"` to `2`, and converts all other values to `1`. + +```{r} +demographics |> + mutate(interview_examination_numeric = if_else(interview_examination == "both interview and exam", + true = 2, + false = 1)) |> + select(interview_examination, interview_examination_numeric) +``` + +Note that you can use `if_else()` for columns of any type. The following code again creates the `interview_examination_numeric` column, and then creates a new column called `interview_examination_revert` that takes the numeric encoding and converts the values `2` and `1` to new character values, `"both"` and `"just interview"`, respectively. We also use the select helper `contains()` inside our select function to view all of the resulting columns that contain the word `"interview"`: + +```{r} +demographics |> + mutate(interview_examination_numeric = if_else(interview_examination == "both interview and exam", + true = 2, + false = 1)) |> + mutate(interview_examination_revert = if_else(interview_examination_numeric == 2, + true = "both", + false = "just interview")) |> + select(contains("interview")) +``` + +### Exercise + +Use `if_else()` to create a variable called `completed_high_school`, which has the values `"yes"` if `education` is equal to at least 3, and `"no"` otherwise. + +A link to the documentation for the demographics data can be found [here](https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/P_DEMO.htm#DMDEDUC2). + + +#### Solution + +Our condition is `education >= 3` and we want to replace all values for which this condition is true with `"yes"`, and all other values with `"no"`: + +```{r} +demographics |> + mutate(completed_high_school = if_else(education >= 3, true = "yes", false = "no")) |> + select(education, completed_high_school) |> + sample_n(10) +``` + + +## case_when + +The `case_when()` function is similar to `if_else()`, in that it allows you to recode values in a column of a DataFrames with different values DataFrame based on a condition, but unlike `if_else()` which only lets you provide one condition, and two value options, `case_when()` allows you to have an unlimited number of conditions and corresponding recoded values. + +In this section we will work with the `marital_status` column of the demographics data: + +```{r} +demographics |> count(marital_status) +``` + +To create a new variable based on `marital_status` that replaces `"married"` with `3`, `"living_with_partner"` with `2`, and each of `"divorced"`, `"widowed"`, `"never_married"`, and `"separated"` with `1`, you can use the following code (the `select()` function at the end just allows us to view the original and the new columns side-by-side). + + + +```{r} +demographics |> mutate(marital_status_numeric = case_when(marital_status == "married" ~ 3, + marital_status == "living_with_partner" ~ 2, + marital_status == "divorced" ~ 1, + marital_status == "widowed" ~ 1, + marital_status == "never_married" ~ 1, + marital_status == "separated" ~ 1)) |> + select(marital_status, marital_status_numeric) +``` + +The argument syntax of `case_when()` is `CONDITION ~ new_value`, where for entries in the original column for which `CONDITION` is `TRUE`, the value `new_value` is returned. So in `marital_status == "married" ~ 3`, the `CONDITION` is `marital_status == "married"`, and the `new_value` is `3`. + +Note that if you have multiple values that you want to recode as the same value, you can use the `%in%` vector syntax for asking whether a variable is contained `%in%` a vector of values: + +```{r} +demographics |> + mutate(marital_status_numeric = case_when( + marital_status == "married" ~ 3, + marital_status == "living_with_partner" ~ 2, + # replace the final four conditions with a single %in% condition: + marital_status %in% c("divorced", "widowed", "never_married", "separated") ~ 1) + ) |> + select(marital_status, marital_status_numeric) +``` + + +## Execise + +Use `case_when()` to convert `born_usa` and `citizen_usa` to "yes" and "no". Bonus points: use `across()`. + + +To do this without `across()`, you can write: + +```{r} +demographics |> mutate(born_usa_chr = case_when(born_usa ~ "yes", + !born_usa ~ "no"), + citizen_usa_chr = case_when(citizen_usa ~ "yes", + !citizen_usa ~ "no")) |> + select(born_usa, born_usa_chr, citizen_usa, citizen_usa_chr) |> + sample_n(10) +``` + +Note that `born_usa ~ "yes"` is equivalent to `born_usa == TRUE ~ "yes"`, but the `== TRUE` is redundant because `born_usa` is itself a logical variable. Similarly, `!citizen_usa ~ "no"` is equivalent to `citizen_usa == FALSE ~ "no"`. + +To use `across()`, the relevant select helper is something like `ends_with("_usa")` or `contains("usa")`, and you provide a `~` before `case_when()` to start an anonymous function, and you need to replace the column name with `.` (again, you don't need the `== TRUE` for this particular example in the condition, but that's just because the columns we're applying the `case_when()` function to are logical). + +```{r} +demographics |> mutate(across(ends_with("_usa"), + ~case_when(. == TRUE ~ "yes", + . == FALSE ~ "no"), + .names = "{.col}_chr")) |> + select(contains("_usa")) |> + sample_n(10) +``` + + diff --git a/content/complete/detailed/05_pivoting.qmd b/content/complete/detailed/05_pivoting.qmd new file mode 100644 index 0000000..72984a7 --- /dev/null +++ b/content/complete/detailed/05_pivoting.qmd @@ -0,0 +1,81 @@ +--- +title: "Reshaping (Pivoting) Data" +format: html +editor_options: + chunk_output_type: console +--- + +In this lesson, we will be working with a new NHANES table that contains urine albumin and creatinine *lab* data. + +```{r} +library(tidyverse) +labs_data <- read.csv("data/urine_albumin_creatinine.csv") +``` + +Taking a look at the first 10 rows, it is clear that this data is in a **long format**. This means that each "observational unit" (in this case, each survey respondent) has multiple rows in the data, and the *names* of the variables being measured (the types of labs) are all contained in a single row (called `labs`) and the *values* of each of the variables being measured are all contained in a single row (called `measurements`). Note that each respondent has 5 rows each: + +```{r} +head(labs_data, 10) +``` + +A **wide format**, on the other hand, will only have *one* row for each observational unit (respondent), and each of the individual variables being measured (the labs) will have their own column, each containing the *values* for the corresponding lab. + +You can convert from a long format to a wide format using the `pivor_wider()` function. The main arguments that you need to provide is the name of the columns that you want to pivot, specifically, the column that contains the variable names (you provide this to the `names_from` argument) and the column that contains the variable measurements (you provide this to the `values_from` argument). + +The code below creates a wide-form version of the labs data, and saves it as a new data frame called `labs_data_wide`: + +```{r} +labs_data_wide <- labs_data |> + pivot_wider(names_from = "lab", values_from = "measurement") +labs_data_wide +``` + +If you want to instead convert from a wide format dataset into a longer-format dataset, you can instead use the `pivot_longer()` function. The main argument you need to provide to `pivot_longer()` is `cols` which contains the names of the columns that will be pivoted into a single pair of `name` and `value` columns. You can change the names of the resulting `name` and `value` columns using the `names_to` and `values_to` arguments of `pivot_longer()`. + +The following code takes the wide-format version of the labs data and pivots it back into the original long-format version: + +```{r} +labs_data_wide |> pivot_longer(cols = starts_with("ur_"), names_to = "lab", values_to = "measurement") +``` + +It is *not* necessarily the case that either one of the long-format versus the wide-format is *always* better than the other. Which one makes more sense will depend on what you plan to do with the data. For example, if you plan to join your labs dataset onto the demographics data that we have been working with previously (you will see this in the next lesson), then you will need to have a single row for each observational unit, and therefore, the wide format is better. + +However, if you want to create a visualization that compares the different variables using ggplot2, it is a lot easier if all of the variables appear in a long (name and value column) format. For example, it is much easier to create some boxplots comparing each of the lab measurement distributions using the original long format than the wide format: + +```{r} +# create boxplots using the long format +labs_data |> ggplot() + + geom_boxplot(aes(x = lab, y = measurement)) +``` + + + +### Exercise + +Load the demographics data and use `select()` to select just the `respondent_id`, `gender`, `marital_status` and `race` columns and then use `pivot_longer()` to create the following long-format table (below are just the first 10 rows). + + respondent_id name value + + 1 73557 gender male + 2 73557 marital_status separated + 3 73557 race black + 4 73558 gender male + 5 73558 marital_status married + 6 73558 race white + 7 73559 gender male + 8 73559 marital_status married + 9 73559 race white +10 73560 gender male + +#### Solution + +```{r} +demographics <- read_csv("data/demographics.csv") +demographics +``` + +```{r} +demographics |> + select(respondent_id, gender, marital_status, race) |> + pivot_longer(cols = all_of(c("gender", "marital_status", "race"))) +``` diff --git a/content/complete/detailed/06_joining.qmd b/content/complete/detailed/06_joining.qmd new file mode 100644 index 0000000..695058a --- /dev/null +++ b/content/complete/detailed/06_joining.qmd @@ -0,0 +1,136 @@ +--- +title: "Joining Data Together" +format: html +editor_options: + chunk_output_type: console +--- + +This lesson introduces techniques for "joining" multiple data tables together using a "key" variable that serves to identify the individual "observational units" in the data. In the NHANES data, each observational unit is an individual respondent of the survey. + +A really helpful resource for learning about joins is the [R for Data Science](https://r4ds.had.co.nz/index.html) book (specifically the chapter about ["Relational Data"](https://r4ds.had.co.nz/relational-data.html)). + +At the end of this lesson we will have created a *single* data frame that contains the information from both the `demographics` data and the urine albumin and creatinine `labs` data that we load in below: + + +```{r} +library(tidyverse) +demographics <- read_csv("data/demographics.csv") +labs <- read_csv("data/urine_albumin_creatinine.csv") +``` + +## Determining what kind of join to do + +There are four kinds of joins that you might want to use for combining two tables into a single table: + +- An **inner join**, which will keep only the data for the observational units that appear in both tables + +- A **left join**, which will keep all of the data for the observational units in the first (left) table, and will add missing values when there is no available data in the second table. + +- A **right join**, which will keep all of the data for the observational units in the second (right) table, and will add missing values when there is no available data in the first table. + +- A **full join**, which will keep all of the data for the observational units in both the first (left) table, and will add missing values when there is no available data in the other table. + +The kind of join that you will implement will depend on what you want to use your joined data for. + +If you only want to keep observational units that have *complete* data (i.e., data available in both tables), then you will want to perform an *inner join*, but if you don't want to discard observational that are missing from one of the tables, you will want to perform a *full join*. + +Identifying the overlap between the two tables can help determine which type of join makes sense. + +So let's ask the question of *Are there any observations in the demographics table that do not appear in the labs table?* + +```{r} +# proportion of people in demographics who are also in labs +sum(unique(demographics$respondent_id) %in% unique(labs$respondent_id)) / n_distinct(demographics$respondent_id) +``` + +The calculation above shows that around 81% of observations in the demographics table have available labs data. + +We can also ask the converse question of *Are there any observations in the labs table that do not appear in the demographics table?* + +```{r} +# proportion of people in labs who are also in demographics +sum(unique(labs$respondent_id) %in% unique(demographics$respondent_id)) / n_distinct(labs$respondent_id) +``` + +The calculation above shows that 100% of observations in the labs table have available demographics data. + +This means that all of the people with labs data appear in the demographics data. Which, if our "left" table is demographics, and our "right" table is labs, means that an *inner join will be the same as a full join*. It also means that a *full join will be the same as a left join*. + + +### Checking the uniqueness of the key ID variables + +It is also helpful to determine whether the key ID values are unique in each table. There are lots of ways to do this, one of which is using the `identical()` function to ask whether the `unique()` version of the `respondent_id` column is equal to the non-`unique()` version. + +Below, we see that the `respondent_id` column is indeed unique for `demographics`: + +```{r} +# are the respondent ID values in demographics unique? +identical(unique(demographics$respondent_id), demographics$respondent_id) +``` + +But not for `labs`: + +```{r} +# are the respondent ID values in labs unique? +identical(unique(labs$respondent_id), labs$respondent_id) +``` + +## Joining demographics and labs + + +Our two options for to join demographics (left) and labs (right) are: + +- An inner or right join will only keep the 81% of people in demographics who have available labs data + +- **A left or full join will keep all people in demographics data, and join missing values for those who don't have labs data available** + +Since we don't want to discard any data, we will choose the latter, a left/full join. + +The following two pieces of code, one using `left_join()` and the other using `full_join()` are equivalent for this problem: + +```{r} +print(left_join(demographics, labs, by = "respondent_id"), width = Inf) +print(full_join(demographics, labs, by = "respondent_id"), width = Inf) +``` + +However, notice that the observations in demographics that have labs observations have all been *duplicated* to match the number of rows in the labs data for each respondent. There are now many more rows in our joined data than we had in our demographics data, which is *not* what we want! + +An important lesson is learned here: **if your key ID variable has repeated values, your joined data will too**. + +**A good check after completing a join is to make sure that the number of rows in the resulting joined data matches what you expect** + +Therefore, to ensure that we have just one row per observational unit (i.e., per `respondent_id` value), we need to join the wide-format `labs_wide` data instead of the long-format `labs` data. + +Below, we compute the wide-format labs data: + +```{r} +labs_wide <- labs |> pivot_wider(names_from = "lab", values_from = "measurement") +labs_wide +``` + +Then we can see that joining this wide version of the labs data onto the demographics data with a `left_join()` yields a joined dataset with all of the `demographics` and `labs_wide` columns, and the number of rows matches the original `demographics` data. + +```{r} +print(left_join(demographics, labs_wide, by = "respondent_id"), width = Inf) +``` + + +## Exercise + +How many rows would you expect an inner join of `demographics` and `labs_wide` to have? Check your answer by conducting the join using `inner_join()` + +The number of rows should match the *intersection* of the two datasets. Since all people in `labs_wide` are also in `demographics`, the join will have the same number of rows in `labs_wide`. + +```{r} +nrow(labs_wide) +``` + +The join can be conducted using `inner_join()` and notice that the number of rows matches `labs_wide`. + +```{r} +inner_join(demographics, labs_wide, by = "respondent_id") +``` + + + +Note that if there were observations in `labs_wide` that were not in `demographics`, then the resulting inner join will have fewer rows than both tables. \ No newline at end of file diff --git a/content/complete/detailed/data/demographics.csv b/content/complete/detailed/data/demographics.csv new file mode 100644 index 0000000..bef67f3 --- /dev/null +++ b/content/complete/detailed/data/demographics.csv @@ -0,0 +1,10176 @@ 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exam,male,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +73725,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +73726,both interview and exam,female,67,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,50000 +73727,both interview and exam,female,3,NA,black,1,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +73728,both interview and exam,male,16,NA,white,2,196,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +73729,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +73730,both interview and exam,male,48,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +73731,both interview and exam,male,12,NA,other,1,154,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +73732,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,3,married,NA,TRUE,50000 +73733,both interview and exam,female,23,NA,mexican 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exam,female,8,NA,white,2,107,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +73753,both interview and exam,female,11,NA,white,1,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +73754,both interview and exam,male,15,NA,mexican american,2,190,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,17500 +73755,both interview and exam,male,75,NA,mexican american,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,40000 +73756,both interview and exam,male,56,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +73757,both interview and exam,female,29,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,87500 +73758,both interview and exam,female,15,NA,white,2,188,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +73759,both interview and exam,female,9,NA,mexican american,2,117,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +73760,both interview and exam,male,64,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +73761,both interview and exam,male,17,NA,mexican 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exam,male,78,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +73781,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +73782,both interview and exam,male,68,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +73783,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +73784,interview only,female,7,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +73785,both interview and exam,male,46,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +73786,both interview and exam,female,18,NA,white,2,217,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +73787,both interview and exam,male,71,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,60000 +73788,both interview and exam,female,9,NA,other hispanic,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +73789,both interview and exam,female,2,NA,black,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +73790,both interview and exam,male,59,NA,white,2,NA,TRUE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +73791,interview only,male,8,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +73792,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +73793,both interview and exam,male,10,NA,mexican american,2,131,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +73794,both interview and exam,female,6,NA,other hispanic,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +73795,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +73796,both interview and exam,female,5,NA,mexican american,1,72,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +73797,both interview and exam,female,57,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +73798,both interview and exam,male,11,NA,other 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exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +73808,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +73809,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,30000 +73810,both interview and exam,male,48,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +73811,both interview and exam,male,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,22500 +73812,both interview and exam,male,5,NA,white,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +73813,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +73814,both interview and exam,male,0,4,black,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +73815,both interview and exam,female,72,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +73816,both interview and exam,male,64,NA,other 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interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +73846,both interview and exam,female,24,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +73847,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,40000 +73848,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,12500 +73849,both interview and exam,female,16,NA,white,2,200,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +73850,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +73851,both interview and exam,female,48,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +73852,both interview and exam,female,40,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,no,FALSE,50000 +73853,both interview and exam,male,13,NA,white,2,165,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +73854,both interview and exam,female,1,23,mexican 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exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +74006,both interview and exam,female,34,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,no,TRUE,30000 +74007,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +74008,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +74009,both interview and exam,female,6,NA,white,2,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74010,both interview and exam,male,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +74011,both interview and exam,male,55,NA,black,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +74012,both interview and exam,female,68,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,widowed,NA,FALSE,40000 +74013,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +74014,both interview and exam,male,60,NA,mexican 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exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,70000 +74034,both interview and exam,female,0,6,mexican american,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74035,both interview and exam,female,3,NA,black,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74036,both interview and exam,male,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +74037,both interview and exam,male,20,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,never_married,NA,TRUE,22500 +74038,both interview and exam,female,54,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,2500 +74039,both interview and exam,female,10,NA,black,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +74040,both interview and exam,male,4,NA,other hispanic,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +74041,both interview and exam,male,60,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,NA +74042,both interview and exam,female,41,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,unable to ascertain,TRUE,22500 +74043,both interview and exam,female,14,NA,mexican american,2,177,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,7500 +74044,both interview and exam,male,73,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +74045,both interview and exam,male,38,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,never_married,NA,FALSE,50000 +74046,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,unable to ascertain,TRUE,100000 +74047,both interview and exam,female,40,NA,mexican american,1,NA,FALSE,NA,FALSE,NA,NA,NA,2,living_with_partner,no,FALSE,22500 +74048,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +74049,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,NA,TRUE,40000 +74050,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +74051,both interview and exam,female,20,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +74052,both interview and exam,female,19,NA,black,2,239,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 +74053,both interview and exam,female,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +74054,both interview and exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,70000 +74055,both interview and exam,male,57,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,50000 +74056,both interview and exam,male,38,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,22500 +74057,both interview and exam,female,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +74058,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,30000 +74059,both interview and exam,male,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74060,both interview and exam,female,8,NA,white,2,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +74061,both interview and exam,female,12,NA,black,1,148,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +74062,both interview and exam,female,67,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,45,NA,2,never_married,NA,TRUE,17500 +74063,interview only,male,49,NA,asian,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,100000 +74064,both interview and exam,male,17,NA,asian,2,207,FALSE,NA,FALSE,FALSE,3,9,NA,NA,NA,TRUE,17500 +74065,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,50000 +74066,both interview and exam,male,56,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,FALSE,17500 +74067,both interview and exam,female,2,NA,white,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74068,both interview and exam,female,5,NA,white,2,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74069,both interview and exam,female,0,11,white,1,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74070,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74071,both interview and exam,female,3,NA,white,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74072,both interview and exam,male,63,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,17500 +74073,both interview and exam,male,0,8,black,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74074,both interview and exam,female,4,NA,mexican american,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74075,both interview and exam,male,59,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +74076,both interview and exam,female,4,NA,mexican american,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74077,both interview and exam,male,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,60000 +74078,both interview and exam,male,63,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +74079,both interview and exam,female,2,NA,mexican american,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +74080,both interview and exam,female,5,NA,white,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74081,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +74082,both interview and exam,male,4,NA,other,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74083,both interview and exam,female,67,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +74084,both interview and exam,male,1,15,other,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74085,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +74086,both interview and exam,male,6,NA,black,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74087,both interview and exam,female,59,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,100000 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exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +74098,both interview and exam,male,0,4,mexican american,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74099,both interview and exam,male,44,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,FALSE,22500 +74100,both interview and exam,male,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,17500 +74101,both interview and exam,female,34,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +74102,both interview and exam,female,18,NA,black,2,217,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,40000 +74103,both interview and exam,female,17,NA,other hispanic,1,211,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,22500 +74104,both interview and exam,female,8,NA,other,1,102,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +74105,both interview and exam,female,0,1,black,2,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74106,both interview and exam,female,10,NA,black,2,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +74107,both interview and exam,male,4,NA,white,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74108,both interview and exam,female,1,19,black,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74109,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,FALSE,FALSE,35,NA,3,divorced,NA,TRUE,40000 +74110,both interview and exam,male,60,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,30000 +74111,both interview and exam,female,61,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,widowed,NA,TRUE,100000 +74112,both interview and exam,female,28,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,17500 +74113,both interview and exam,male,17,NA,white,1,212,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +74114,both interview and exam,female,9,NA,black,1,112,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +74115,both interview and exam,male,27,NA,mexican 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exam,female,28,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,separated,no,TRUE,22500 +74125,both interview and exam,female,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,NA +74126,both interview and exam,female,53,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +74127,both interview and exam,female,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +74128,both interview and exam,female,71,NA,black,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,married,NA,TRUE,40000 +74129,both interview and exam,male,56,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,NA,TRUE,50000 +74130,both interview and exam,male,12,NA,black,1,149,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +74131,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,70000 +74132,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,70000 +74133,both interview and exam,female,14,NA,mexican american,2,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,30000 +74134,both interview and exam,female,51,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,NA,TRUE,60000 +74135,both interview and exam,female,6,NA,white,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74136,both interview and exam,male,9,NA,asian,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +74137,both interview and exam,male,17,NA,mexican american,1,212,FALSE,NA,FALSE,FALSE,12.5,12,NA,NA,NA,FALSE,50000 +74138,both interview and exam,male,69,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,FALSE,30000 +74139,both interview and exam,female,63,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,2500 +74140,both interview and exam,female,8,NA,mexican american,1,100,NA,NA,FALSE,FALSE,7.5,2,NA,NA,NA,FALSE,12500 +74141,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,60000 +74142,both interview and exam,male,61,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +74143,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74144,both interview and exam,male,51,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,87500 +74145,both interview and exam,male,6,NA,black,2,79,NA,NA,FALSE,FALSE,7.5,0,NA,NA,NA,TRUE,40000 +74146,both interview and exam,male,50,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,TRUE,7500 +74147,both interview and exam,female,79,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +74148,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,22500 +74149,both interview and exam,female,54,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +74150,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,87500 +74151,interview only,male,1,21,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +74152,both interview and exam,female,74,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,7500 +74153,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +74154,both interview and exam,female,52,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +74155,interview only,female,20,NA,other hispanic,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,unable to ascertain,TRUE,17500 +74156,both interview and exam,female,3,NA,other hispanic,2,37,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74157,both interview and exam,female,7,NA,other,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74158,both interview and exam,female,19,NA,black,1,232,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +74159,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +74160,both interview and exam,female,66,NA,other 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exam,male,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +74347,both interview and exam,male,13,NA,other,2,166,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +74348,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +74349,both interview and exam,female,57,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,100000 +74350,both interview and exam,male,52,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +74351,both interview and exam,female,7,NA,black,1,87,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,50000 +74352,both interview and exam,male,65,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,100000 +74353,interview only,female,20,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,unable to ascertain,TRUE,17500 +74354,both interview and exam,female,0,2,mexican american,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74355,both interview and 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exam,male,26,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,never_married,NA,TRUE,30000 +74394,both interview and exam,female,51,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +74395,both interview and exam,male,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +74396,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +74397,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +74398,both interview and exam,male,27,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +74399,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +74400,both interview and exam,male,23,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +74401,both interview and exam,female,19,NA,white,2,234,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,22500 +74402,both interview and 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exam,male,4,NA,white,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74497,both interview and exam,male,2,NA,other hispanic,1,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +74498,both interview and exam,male,29,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,TRUE,50000 +74499,both interview and exam,male,59,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +74500,both interview and exam,male,6,NA,mexican american,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,12500 +74501,both interview and exam,female,10,NA,white,1,131,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +74502,both interview and exam,male,27,NA,black,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,NA,TRUE,7500 +74503,both interview and exam,female,47,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,30000 +74504,both interview and exam,female,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,22500 +74505,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,100000 +74506,both interview and exam,female,4,NA,mexican american,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +74507,both interview and exam,male,14,NA,mexican american,2,176,NA,NA,FALSE,FALSE,3,8,NA,NA,NA,FALSE,22500 +74508,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74509,both interview and exam,female,48,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +74510,both interview and exam,male,64,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +74511,both interview and exam,male,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74512,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,1,married,NA,TRUE,40000 +74513,both interview and exam,male,15,NA,white,2,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,NA +74514,both interview and exam,female,0,5,other 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interview and exam,male,47,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,FALSE,17500 +74525,both interview and exam,male,11,NA,other,2,137,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +74526,both interview and exam,female,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +74527,both interview and exam,male,0,5,black,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74528,both interview and exam,female,1,15,mexican american,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +74529,both interview and exam,male,51,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,30000 +74530,both interview and exam,female,45,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,3,married,NA,FALSE,22500 +74531,both interview and exam,male,72,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,17500 +74532,both interview and exam,male,25,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,17500 +74533,both interview and exam,female,0,8,white,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74534,both interview and exam,male,65,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +74535,both interview and exam,male,1,22,other hispanic,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +74536,both interview and exam,male,65,NA,other hispanic,1,NA,TRUE,TRUE,FALSE,TRUE,55,NA,4,married,NA,TRUE,30000 +74537,both interview and exam,female,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,12500 +74538,both interview and exam,female,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +74539,both interview and exam,male,55,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +74540,both interview and exam,female,11,NA,other hispanic,2,134,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +74541,both interview and exam,female,5,NA,black,1,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74542,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,2500 +74543,both interview and exam,male,40,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +74544,both interview and exam,male,10,NA,black,1,126,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +74545,both interview and exam,female,8,NA,white,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +74546,both interview and exam,female,27,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,2,never_married,no,FALSE,30000 +74547,both interview and exam,male,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +74548,both interview and exam,female,63,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,4,divorced,NA,FALSE,17500 +74549,both interview and exam,female,55,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,NA,TRUE,70000 +74550,both interview and exam,female,4,NA,black,1,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74551,both interview and exam,female,32,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +74552,both interview and exam,female,44,NA,black,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,never_married,no,TRUE,22500 +74553,both interview and exam,male,6,NA,white,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +74554,both interview and exam,female,35,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +74555,interview only,female,2,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74556,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +74557,both interview and exam,female,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,30000 +74558,both interview and exam,female,1,12,black,2,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74559,both interview and exam,female,19,NA,other hispanic,1,234,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,70000 +74560,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +74561,both interview and exam,male,1,18,mexican american,2,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74562,both interview and exam,male,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +74563,both interview and exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +74564,both interview and exam,female,26,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,unable to ascertain,TRUE,30000 +74565,both interview and exam,male,66,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,NA,FALSE,NA +74566,both interview and exam,female,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,12500 +74567,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +74568,both interview and exam,male,8,NA,other hispanic,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +74569,both interview and exam,male,19,NA,white,1,233,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,40000 +74570,both interview and exam,female,63,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +74571,both interview and exam,male,53,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74572,both interview and exam,female,2,NA,black,1,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74573,both interview and exam,female,4,NA,black,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74574,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +74575,both interview and exam,female,16,NA,other hispanic,2,198,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +74576,both interview and exam,female,73,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +74577,interview only,female,3,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74578,both interview and exam,male,4,NA,other hispanic,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74579,both interview and exam,male,51,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,living_with_partner,NA,TRUE,12500 +74580,both interview and exam,female,13,NA,other hispanic,2,160,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,22500 +74581,both interview and exam,male,75,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +74582,both interview and exam,female,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +74583,both interview and exam,female,60,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +74584,both interview and exam,male,10,NA,black,2,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +74585,interview only,female,0,1,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74586,both interview and exam,male,24,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,30000 +74587,both interview and exam,male,66,NA,mexican american,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +74588,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +74589,both interview and exam,male,67,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,22500 +74590,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +74591,both interview and exam,male,73,NA,black,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,22500 +74592,both interview and exam,male,1,15,black,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74593,both interview and exam,male,0,1,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74594,both interview and exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,50000 +74595,both interview and exam,male,5,NA,mexican american,1,62,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +74596,both interview and exam,female,45,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +74597,both interview and exam,male,0,6,mexican american,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 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exam,female,60,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,divorced,NA,TRUE,100000 +74637,both interview and exam,male,11,NA,white,1,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +74638,both interview and exam,male,34,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,living_with_partner,NA,TRUE,87500 +74639,both interview and exam,male,51,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +74640,both interview and exam,male,14,NA,white,1,181,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +74641,both interview and exam,male,33,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +74642,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +74643,both interview and exam,male,2,NA,black,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74644,both interview and exam,female,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,NA +74645,both interview and exam,female,68,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +74646,both interview and exam,male,49,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +74647,both interview and exam,female,15,NA,white,2,191,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +74648,both interview and exam,female,18,NA,black,2,221,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,17500 +74649,both interview and exam,female,4,NA,black,2,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74650,both interview and exam,male,56,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,4,married,NA,FALSE,30000 +74651,both interview and exam,male,8,NA,white,2,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,7500 +74652,both interview and exam,female,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,no,FALSE,30000 +74653,both interview and exam,female,29,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,17500 +74654,both interview and 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exam,female,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +74805,both interview and exam,male,12,NA,other hispanic,2,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +74806,both interview and exam,male,11,NA,asian,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +74807,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,12500 +74808,both interview and exam,female,0,4,other hispanic,1,4,NA,NA,FALSE,TRUE,0.5,NA,NA,NA,NA,TRUE,7500 +74809,both interview and exam,male,9,NA,black,1,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +74810,interview only,female,3,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +74811,both interview and exam,male,2,NA,asian,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74812,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,7500 +74813,both interview and exam,female,13,NA,other,1,159,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +74814,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,12500 +74815,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +74816,both interview and exam,male,13,NA,mexican american,1,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,7500 +74817,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +74818,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74819,both interview and exam,male,1,17,mexican american,2,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74820,both interview and exam,male,1,18,black,1,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74821,both interview and exam,female,4,NA,black,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74822,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,100000 +74823,both interview and exam,male,67,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +74824,both interview and exam,female,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +74825,both interview and exam,male,16,NA,mexican american,2,203,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +74826,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74827,both interview and exam,female,0,11,white,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74828,both interview and exam,male,8,NA,other,1,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +74829,both interview and exam,female,27,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,yes,TRUE,7500 +74830,both interview and exam,male,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +74831,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74832,both interview and exam,male,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,87500 +74833,both interview and exam,male,16,NA,white,2,196,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +74834,both interview and exam,male,48,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,living_with_partner,NA,FALSE,NA +74835,both interview and exam,male,7,NA,white,1,95,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,70000 +74836,both interview and exam,female,4,NA,black,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74837,both interview and exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +74838,both interview and exam,female,8,NA,other hispanic,1,97,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +74839,both interview and exam,male,47,NA,white,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +74840,both interview and exam,male,10,NA,mexican american,1,121,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +74841,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,widowed,NA,TRUE,NA +74842,both interview and exam,female,2,NA,white,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +74843,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,no,FALSE,7500 +74844,both interview and exam,male,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +74845,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +74846,both interview and exam,female,2,NA,mexican american,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74847,both interview and exam,female,1,20,asian,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74848,both interview and exam,female,5,NA,white,2,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74849,both interview and exam,male,9,NA,other hispanic,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +74850,both interview and exam,female,2,NA,white,2,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74851,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,NA +74852,both interview and exam,female,12,NA,black,1,148,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +74853,interview only,female,80,NA,asian,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +74854,both interview and exam,female,18,NA,other hispanic,2,225,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,22500 +74855,both interview and exam,male,16,NA,black,2,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +74856,both interview and exam,male,5,NA,black,1,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74857,both interview and exam,female,9,NA,other hispanic,2,109,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +74858,both interview and exam,male,2,NA,mexican american,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74859,both interview and exam,female,55,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +74860,both interview and exam,male,40,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,70000 +74861,both interview and exam,male,60,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,7500 +74862,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +74863,both interview and exam,male,1,20,white,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74864,both interview and exam,female,11,NA,mexican american,2,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,30000 +74865,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +74866,both interview and exam,male,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +74867,both interview and exam,female,53,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +74868,both interview and exam,female,9,NA,mexican american,1,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,22500 +74869,both interview and exam,female,66,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,30000 +74870,both interview and exam,female,11,NA,black,1,137,NA,NA,FALSE,FALSE,7.5,5,NA,NA,NA,TRUE,22500 +74871,both interview and exam,male,8,NA,black,1,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,2500 +74872,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +74873,both interview and exam,female,1,17,black,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74874,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74875,both interview and exam,female,5,NA,black,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74876,both interview and exam,male,2,NA,other hispanic,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74877,both interview and exam,female,14,NA,mexican american,1,179,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,NA +74878,both interview and exam,female,69,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,87500 +74879,both interview and exam,female,43,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,no,TRUE,100000 +74880,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +74881,both interview and exam,female,14,NA,white,1,180,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +74882,both interview and exam,male,25,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,married,NA,FALSE,50000 +74883,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +74884,both interview and exam,male,0,7,white,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74885,both interview and exam,female,57,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +74886,both interview and exam,female,18,NA,black,1,223,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,30000 +74887,both interview and exam,male,13,NA,black,1,164,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +74888,interview only,male,21,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +74889,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +74890,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +74891,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,70000 +74892,both interview and exam,female,0,0,other,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74893,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74894,both interview and exam,female,6,NA,asian,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74895,both interview and exam,female,15,NA,white,2,191,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,70000 +74896,both interview and exam,male,6,NA,black,1,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +74897,both interview and exam,female,46,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,FALSE,22500 +74898,both interview and exam,female,2,NA,mexican american,1,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +74899,both interview and exam,female,0,7,other hispanic,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74900,both interview and exam,female,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +74901,both interview and exam,male,55,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +74902,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +74903,both interview and exam,male,11,NA,black,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,NA +74904,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +74905,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74906,both interview and exam,male,0,6,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74907,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +74908,both interview and exam,male,0,4,black,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74909,both interview and exam,male,64,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,FALSE,50000 +74910,both interview and exam,female,19,NA,black,1,231,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,7500 +74911,both interview and exam,female,13,NA,mexican american,2,166,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,NA +74912,both interview and exam,male,12,NA,asian,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,NA +74913,both interview and exam,female,14,NA,black,2,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +74914,both interview and exam,male,9,NA,mexican american,2,118,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +74915,both interview and exam,female,4,NA,asian,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74916,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +74917,both interview and exam,female,11,NA,white,2,137,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +74918,both interview and exam,female,49,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,NA,FALSE,40000 +74919,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +74920,both interview and exam,female,6,NA,black,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +74921,both interview and exam,male,0,10,mexican american,1,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74922,both interview and exam,male,3,NA,black,2,46,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74923,both interview and exam,male,24,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +74924,both interview and exam,male,1,17,white,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74925,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,30000 +74926,both interview and exam,female,6,NA,black,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +74927,both interview and exam,male,17,NA,black,1,209,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +74928,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,60000 +74929,both interview and exam,female,66,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +74930,both interview and exam,female,11,NA,white,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +74931,both interview and exam,male,53,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +74932,both interview and exam,male,32,NA,other,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +74933,both interview and exam,female,57,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +74934,both interview and exam,male,14,NA,black,1,169,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +74935,both interview and exam,male,20,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,never_married,NA,TRUE,NA +74936,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +74937,both interview and exam,male,74,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +74938,both interview and exam,female,52,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +74939,both interview and exam,male,13,NA,asian,1,156,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +74940,both interview and exam,male,80,NA,black,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,TRUE,40000 +74941,both interview and exam,female,59,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +74942,both interview and exam,female,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +74943,both interview and exam,male,19,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,40000 +74944,both interview and exam,female,2,NA,black,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74945,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +74946,both interview and exam,male,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,2500 +74947,both interview and exam,female,3,NA,other,1,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74948,both interview and exam,female,33,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +74949,both interview and exam,male,8,NA,white,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +74950,both interview and exam,female,20,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,never_married,no,TRUE,40000 +74951,both interview and exam,male,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +74952,both interview and exam,female,0,8,white,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74953,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 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exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +74964,both interview and exam,female,2,NA,mexican american,2,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74965,both interview and exam,male,26,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +74966,both interview and exam,male,3,NA,other,1,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74967,both interview and exam,female,0,6,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74968,both interview and exam,female,10,NA,black,1,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +74969,both interview and exam,male,22,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,never_married,NA,TRUE,22500 +74970,both interview and exam,male,1,16,other,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74971,both interview and exam,female,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +74972,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 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exam,male,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +74983,both interview and exam,female,63,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,2,married,NA,TRUE,30000 +74984,both interview and exam,male,64,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,never_married,NA,FALSE,NA +74985,both interview and exam,female,66,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,widowed,NA,FALSE,12500 +74986,both interview and exam,female,17,NA,mexican american,2,214,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,FALSE,22500 +74987,both interview and exam,female,10,NA,black,2,132,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +74988,both interview and exam,female,8,NA,white,1,103,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +74989,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,NA +74990,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +74991,both interview and exam,male,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,17500 +74992,both interview and exam,female,14,NA,white,2,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +74993,both interview and exam,male,5,NA,white,2,62,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74994,interview only,female,7,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +74995,both interview and exam,male,0,6,other hispanic,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74996,both interview and exam,male,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74997,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,50000 +74998,both interview and exam,female,38,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,married,no,TRUE,30000 +74999,both interview and exam,female,7,NA,white,2,88,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +75000,both interview and exam,female,45,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,separated,NA,FALSE,30000 +75001,both interview 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interview and exam,female,69,NA,white,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,60000 +75012,both interview and exam,male,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +75013,both interview and exam,male,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +75014,interview only,male,47,NA,asian,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,TRUE,87500 +75015,both interview and exam,female,2,NA,mexican american,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75016,both interview and exam,male,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +75017,both interview and exam,male,54,NA,black,2,NA,FALSE,NA,FALSE,FALSE,35,NA,2,never_married,NA,TRUE,40000 +75018,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +75019,both interview and exam,female,11,NA,white,2,143,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +75020,both interview and exam,female,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +75021,both interview and exam,female,0,8,asian,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75022,interview only,male,10,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +75023,both interview and exam,male,27,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +75024,both interview and exam,female,3,NA,white,1,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +75025,both interview and exam,female,12,NA,black,2,155,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,70000 +75026,interview only,male,6,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +75027,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,100000 +75028,both interview and exam,female,10,NA,white,1,128,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +75029,both interview and exam,male,23,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,NA +75030,both interview and exam,female,56,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,7500 +75031,interview only,female,80,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +75032,both interview and exam,male,23,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +75033,both interview and exam,female,14,NA,black,1,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +75034,both interview and exam,female,19,NA,mexican american,1,233,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,87500 +75035,both interview and exam,female,3,NA,black,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75036,both interview and exam,male,7,NA,mexican american,1,91,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +75037,both interview and exam,male,3,NA,asian,1,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +75038,both interview and exam,female,2,NA,black,1,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +75039,both interview and exam,male,6,NA,mexican american,2,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +75040,both interview and exam,male,16,NA,black,1,193,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,87500 +75041,both interview and exam,female,15,NA,black,1,185,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +75042,both interview and exam,female,54,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,2500 +75043,both interview and exam,female,17,NA,mexican american,1,209,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,7500 +75044,both interview and exam,female,60,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,3,married,NA,FALSE,87500 +75045,both interview and exam,female,13,NA,mexican american,1,168,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,22500 +75046,both interview and exam,female,2,NA,other hispanic,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +75047,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +75048,both interview and exam,male,15,NA,mexican american,2,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,NA +75049,both interview and 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exam,female,2,NA,other,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +75107,both interview and exam,female,8,NA,white,2,106,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +75108,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +75109,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +75110,both interview and exam,male,5,NA,black,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75111,both interview and exam,male,32,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,NA,TRUE,40000 +75112,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +75113,interview only,male,36,NA,asian,NA,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,TRUE,22500 +75114,both interview and exam,female,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +75115,both interview and exam,female,2,NA,other,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +75116,both 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exam,female,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,12500 +75126,both interview and exam,male,6,NA,other,1,76,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +75127,both interview and exam,male,59,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +75128,both interview and exam,male,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +75129,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,30000 +75130,both interview and exam,male,6,NA,mexican american,1,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,50000 +75131,both interview and exam,female,34,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +75132,both interview and exam,male,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +75133,both interview and exam,male,12,NA,black,2,147,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +75134,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,12500 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exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,60000 +75203,both interview and exam,male,69,NA,mexican american,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +75204,both interview and exam,female,7,NA,black,1,91,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,7500 +75205,both interview and exam,female,32,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,no,TRUE,100000 +75206,both interview and exam,male,9,NA,white,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +75207,both interview and exam,male,65,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +75208,both interview and exam,male,9,NA,black,2,117,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +75209,both interview and exam,female,18,NA,asian,1,222,FALSE,NA,FALSE,TRUE,17.5,13,NA,NA,NA,TRUE,7500 +75210,both interview and exam,female,7,NA,mexican american,2,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,22500 +75211,both interview and exam,male,37,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 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exam,male,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +75222,both interview and exam,female,65,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,NA,TRUE,100000 +75223,both interview and exam,female,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +75224,both interview and exam,female,27,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,50000 +75225,both interview and exam,male,14,NA,mexican american,1,179,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,40000 +75226,both interview and exam,female,8,NA,white,2,98,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,17500 +75227,both interview and exam,female,18,NA,asian,1,219,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,12500 +75228,interview only,female,7,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,NA +75229,both interview and exam,male,0,1,black,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75230,both interview and exam,female,2,NA,other hispanic,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 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exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +75344,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +75345,both interview and exam,female,54,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +75346,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75347,both interview and exam,female,62,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75348,both interview and exam,female,9,NA,black,2,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +75349,both interview and exam,male,54,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,separated,NA,FALSE,30000 +75350,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,22500 +75351,both interview and exam,female,29,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +75352,both interview and exam,male,30,NA,other 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exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +75613,both interview and exam,female,55,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +75614,both interview and exam,female,7,NA,black,2,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +75615,both interview and exam,female,1,23,white,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +75616,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +75617,both interview and exam,male,2,NA,white,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75618,both interview and exam,male,13,NA,mexican american,2,159,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,40000 +75619,both interview and exam,male,36,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,100000 +75620,both interview and exam,female,52,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +75621,both interview and exam,female,59,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +75622,both interview and exam,female,8,NA,white,1,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +75623,both interview and exam,male,9,NA,white,2,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +75624,both interview and exam,female,21,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,never_married,no,TRUE,50000 +75625,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +75626,both interview and exam,female,5,NA,other hispanic,2,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +75627,both interview and exam,male,1,15,black,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75628,both interview and exam,female,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +75629,both interview and exam,female,9,NA,other hispanic,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +75630,both interview and exam,female,59,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +75631,both interview and exam,female,72,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +75632,both interview and exam,female,3,NA,asian,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +75633,both interview and exam,male,10,NA,mexican american,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,NA +75634,both interview and exam,male,13,NA,black,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +75635,both interview and exam,female,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +75636,both interview and exam,female,35,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +75637,both interview and exam,female,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,100000 +75638,both interview and exam,female,16,NA,black,2,197,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +75639,both interview and exam,male,15,NA,black,1,184,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +75640,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +75641,both interview and exam,female,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75642,both interview and exam,male,1,22,mexican american,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +75643,both interview and exam,female,43,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,FALSE,7500 +75644,both interview and exam,male,69,NA,asian,1,NA,TRUE,TRUE,FALSE,TRUE,45,NA,2,married,NA,TRUE,NA +75645,both interview and exam,male,6,NA,black,1,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +75646,both interview and exam,male,20,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +75647,both interview and exam,male,28,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +75648,both interview and exam,female,18,NA,other hispanic,1,219,FALSE,NA,FALSE,FALSE,0.5,9,NA,NA,NA,FALSE,22500 +75649,both interview and exam,male,11,NA,white,1,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +75650,both interview and exam,female,13,NA,mexican american,2,159,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +75651,both interview and exam,male,1,21,asian,2,21,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,100000 +75652,both interview and exam,male,4,NA,mexican american,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +75653,both interview and exam,male,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +75654,both interview and exam,female,49,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +75655,both interview and exam,male,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +75656,both interview and exam,female,1,12,white,2,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +75657,both interview and exam,female,12,NA,white,2,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +75658,both interview and exam,male,8,NA,black,2,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +75659,both interview and exam,male,15,NA,black,2,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +75660,both interview and exam,female,59,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +75661,both interview and exam,male,4,NA,asian,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +75662,both interview and exam,female,44,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +75663,both interview and exam,female,54,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +75664,both interview and exam,female,31,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,7500 +75665,both interview and exam,female,12,NA,other hispanic,2,152,NA,NA,FALSE,FALSE,3,7,NA,NA,NA,FALSE,22500 +75666,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75667,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +75668,both interview and exam,male,10,NA,mexican american,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +75669,both interview and exam,male,64,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,divorced,NA,TRUE,100000 +75670,both interview and exam,female,27,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,50000 +75671,both interview and exam,male,11,NA,asian,1,144,NA,NA,FALSE,FALSE,3,6,NA,NA,NA,TRUE,60000 +75672,interview only,male,1,13,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +75673,interview only,female,6,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +75674,both interview and exam,male,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,17500 +75675,both interview and exam,female,17,NA,black,1,208,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,NA +75676,both interview and exam,female,6,NA,asian,1,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +75677,both interview and exam,female,10,NA,black,2,125,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +75678,both interview and exam,male,10,NA,other hispanic,2,126,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +75679,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +75680,both interview and exam,female,15,NA,white,2,181,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +75681,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,40000 +75682,both interview and exam,male,29,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +75683,both interview and exam,male,23,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,NA +75684,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +75685,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,2500 +75686,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +75687,interview only,female,20,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,100000 +75688,both interview and exam,female,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,2,divorced,NA,FALSE,7500 +75689,both interview and exam,male,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +75690,both interview and exam,male,34,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,40000 +75691,both interview and exam,female,70,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +75692,both interview and exam,male,18,NA,white,2,218,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +75693,both interview and exam,male,0,2,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +75694,both interview and exam,male,9,NA,other hispanic,2,112,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +75695,both interview and exam,female,74,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,widowed,NA,FALSE,30000 +75696,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,widowed,NA,TRUE,12500 +75697,both interview and exam,female,10,NA,white,1,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +75698,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +75699,both interview and exam,female,62,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,1,never_married,NA,FALSE,17500 +75700,both interview and exam,male,68,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,divorced,NA,FALSE,17500 +75701,both interview and exam,female,2,NA,white,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75702,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,divorced,NA,TRUE,50000 +75703,both interview and exam,male,3,NA,black,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75704,both interview and exam,male,24,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +75705,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +75706,both interview and exam,female,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +75707,both interview and exam,female,14,NA,other hispanic,2,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,17500 +75708,both interview and exam,female,5,NA,black,1,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +75709,both interview and exam,female,30,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,no,TRUE,60000 +75710,both interview and exam,male,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75711,both interview and exam,male,12,NA,mexican american,1,150,NA,NA,FALSE,FALSE,3,5,NA,NA,NA,TRUE,87500 +75712,both interview and exam,male,11,NA,white,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +75713,both interview and exam,female,12,NA,asian,1,145,NA,NA,FALSE,FALSE,7.5,6,NA,NA,NA,TRUE,7500 +75714,both interview and exam,male,54,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +75715,both interview and exam,male,12,NA,other hispanic,2,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,NA +75716,both interview and exam,male,2,NA,mexican american,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +75717,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +75718,both interview and exam,male,0,11,other,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75719,both interview and exam,male,2,NA,other,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +75720,both interview and exam,male,6,NA,mexican american,2,72,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,60000 +75721,both interview and exam,male,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +75722,both interview and exam,male,15,NA,black,1,188,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +75723,both interview and exam,female,55,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,never_married,NA,TRUE,17500 +75724,both interview and exam,male,66,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,50000 +75725,both interview and exam,male,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +75726,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +75727,both interview and exam,male,0,0,white,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +75728,both interview and exam,male,10,NA,white,2,131,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +75729,both interview and exam,female,11,NA,mexican american,1,137,NA,NA,FALSE,FALSE,12.5,4,NA,NA,NA,FALSE,50000 +75730,both interview and exam,male,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +75731,both interview and exam,male,8,NA,other hispanic,1,106,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,2500 +75732,both interview and exam,male,15,NA,mexican american,2,190,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +75733,both interview and exam,male,56,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +75734,both interview and exam,male,18,NA,black,1,223,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,87500 +75735,both interview and exam,male,19,NA,asian,2,237,TRUE,FALSE,FALSE,TRUE,17.5,13,NA,NA,NA,TRUE,100000 +75736,both interview and exam,male,0,5,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75737,both interview and exam,female,20,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +75738,both interview and exam,male,47,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,87500 +75739,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +75740,both interview and exam,female,5,NA,black,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +75741,both interview and exam,female,11,NA,white,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +75742,both interview and exam,male,37,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,70000 +75743,both interview and exam,female,36,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,no,TRUE,7500 +75744,both interview and exam,female,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +75745,both interview and exam,female,44,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,no,TRUE,40000 +75746,both interview and exam,female,2,NA,other,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75747,both interview and exam,male,18,NA,asian,2,221,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,87500 +75748,both interview and exam,female,80,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,60000 +75749,both interview and exam,male,69,NA,other hispanic,2,NA,TRUE,FALSE,FALSE,TRUE,45,NA,3,divorced,NA,TRUE,7500 +75750,both interview and exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75751,both interview and exam,male,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75752,both interview and exam,female,11,NA,white,2,141,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +75753,both interview and exam,male,19,NA,mexican american,1,238,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +75754,both interview and exam,male,55,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +75755,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +75756,both interview and exam,female,5,NA,white,2,70,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,NA +75757,both interview and exam,female,7,NA,mexican american,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +75758,both interview and exam,male,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +75759,both interview and exam,male,11,NA,other hispanic,2,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +75760,both interview and exam,female,12,NA,asian,1,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +75761,both interview and exam,female,6,NA,black,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +75762,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,70000 +75763,both interview and exam,male,32,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,30000 +75764,both interview and exam,female,2,NA,other hispanic,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +75765,both interview and exam,female,7,NA,black,1,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +75766,both interview and exam,female,16,NA,white,2,195,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +75767,both interview and exam,female,9,NA,mexican american,2,113,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,40000 +75768,both interview and exam,male,46,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,35,NA,3,married,NA,TRUE,70000 +75769,both interview and exam,male,72,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +75770,both interview and exam,female,10,NA,white,2,127,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +75771,both interview and exam,male,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +75772,both interview and exam,female,15,NA,white,1,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +75773,both interview and exam,female,19,NA,white,1,229,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +75774,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +75775,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,NA,TRUE,NA +75776,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,22500 +75777,both interview and exam,male,9,NA,asian,2,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +75778,interview only,male,62,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,TRUE,30000 +75779,both interview and exam,male,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +75780,both interview and exam,male,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,22500 +75781,both interview and exam,male,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75782,both interview and exam,male,6,NA,mexican american,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +75783,interview only,male,55,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,40000 +75784,both interview and exam,male,57,NA,other hispanic,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +75785,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,70000 +75786,both interview and exam,female,54,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +75787,both interview and exam,male,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +75788,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75789,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +75790,both interview and exam,female,28,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +75791,both interview and exam,female,12,NA,black,1,150,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +75792,both interview and exam,male,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +75793,both interview and exam,female,2,NA,white,1,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +75794,both interview and exam,female,8,NA,black,1,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +75795,both interview and exam,male,79,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,55,NA,1,married,NA,FALSE,22500 +75796,both interview and exam,female,14,NA,black,1,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +75797,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,87500 +75798,both interview and exam,male,9,NA,mexican american,1,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,40000 +75799,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +75800,both interview and exam,male,9,NA,mexican american,1,118,NA,NA,FALSE,FALSE,7.5,3,NA,NA,NA,FALSE,22500 +75801,both interview and exam,male,3,NA,mexican american,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +75802,both interview and exam,male,15,NA,mexican american,1,192,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,NA +75803,both interview and exam,male,40,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +75804,both interview and exam,male,0,8,white,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75805,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,22500 +75806,both interview and exam,male,7,NA,white,2,94,NA,NA,FALSE,FALSE,3,2,NA,NA,NA,TRUE,NA +75807,both interview and exam,female,32,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +75808,both interview and exam,male,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +75809,both interview and exam,male,13,NA,white,2,159,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +75810,both interview and exam,male,7,NA,white,2,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +75811,both interview and exam,female,8,NA,mexican american,2,102,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +75812,interview only,female,1,13,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75813,both interview and exam,female,6,NA,black,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +75814,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,2500 +75815,both interview and exam,male,7,NA,other,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +75816,both interview and exam,female,17,NA,asian,2,214,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,60000 +75817,both interview and exam,female,53,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,1,married,NA,TRUE,50000 +75818,both interview and exam,female,6,NA,black,1,79,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +75819,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +75820,both interview and exam,female,43,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,no,TRUE,100000 +75821,interview only,male,25,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,5,never_married,NA,TRUE,70000 +75822,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,100000 +75823,both interview and exam,female,43,NA,other,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,no,TRUE,100000 +75824,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +75825,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,no,TRUE,40000 +75826,both interview and exam,male,70,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +75827,both interview and exam,female,14,NA,other,2,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,87500 +75828,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +75829,both interview and exam,male,5,NA,mexican american,1,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +75830,both interview and exam,female,18,NA,black,1,218,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +75831,both interview and exam,female,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +75832,both interview and exam,female,14,NA,mexican american,2,169,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +75833,both interview and exam,male,15,NA,black,2,185,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +75834,both interview and exam,male,0,7,other,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +75835,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +75836,both interview and exam,male,16,NA,other,2,195,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +75837,both interview and exam,male,55,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 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exam,female,6,NA,black,1,77,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +75848,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75849,both interview and exam,female,3,NA,other hispanic,2,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75850,both interview and exam,female,37,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,no,TRUE,100000 +75851,both interview and exam,male,11,NA,other hispanic,2,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +75852,both interview and exam,male,7,NA,white,2,85,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +75853,both interview and exam,female,19,NA,mexican american,2,239,FALSE,NA,FALSE,FALSE,3,11,NA,NA,NA,FALSE,12500 +75854,both interview and exam,male,18,NA,white,2,221,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,50000 +75855,both interview and exam,female,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +75856,both interview and exam,female,28,NA,other 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interview and exam,male,12,NA,mexican american,2,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +75867,both interview and exam,male,1,22,asian,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75868,both interview and exam,female,0,7,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +75869,both interview and exam,male,27,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +75870,both interview and exam,female,40,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,60000 +75871,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +75872,both interview and exam,female,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,12500 +75873,both interview and exam,male,9,NA,white,2,109,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +75874,both interview and exam,male,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +75875,both interview and exam,male,14,NA,black,1,169,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +75876,both interview and exam,male,4,NA,white,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75877,both interview and exam,male,1,21,white,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +75878,both interview and exam,female,12,NA,mexican american,1,156,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,30000 +75879,both interview and exam,male,56,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,12500 +75880,both interview and exam,female,13,NA,asian,1,158,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +75881,both interview and exam,female,25,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,never_married,no,FALSE,40000 +75882,both interview and exam,male,54,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +75883,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +75884,both interview and exam,female,3,NA,white,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +75885,both interview and exam,male,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75886,both interview and exam,male,12,NA,mexican american,2,155,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,NA +75887,both interview and exam,female,56,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +75888,both interview and exam,female,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,40000 +75889,interview only,male,4,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +75890,both interview and exam,female,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,50000 +75891,both interview and exam,male,2,NA,white,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +75892,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +75893,both interview and exam,female,49,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,TRUE,87500 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exam,male,28,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,17500 +75904,both interview and exam,female,70,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,widowed,NA,FALSE,30000 +75905,both interview and exam,female,39,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,never_married,no,TRUE,87500 +75906,both interview and exam,male,17,NA,white,1,210,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +75907,both interview and exam,male,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +75908,both interview and exam,female,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +75909,both interview and exam,female,77,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,FALSE,7500 +75910,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +75911,both interview and exam,male,67,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,separated,NA,TRUE,50000 +75912,both interview and exam,male,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +75913,both interview and exam,female,32,NA,white,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,never_married,no,TRUE,NA +75914,both interview and exam,male,1,14,other hispanic,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75915,both interview and exam,female,63,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +75916,both interview and exam,male,7,NA,white,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +75917,interview only,female,13,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +75918,both interview and exam,female,7,NA,white,1,89,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +75919,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,NA +75920,both interview and exam,male,11,NA,mexican american,2,134,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +75921,both interview and exam,male,76,NA,black,1,NA,FALSE,NA,FALSE,TRUE,55,NA,4,married,NA,TRUE,87500 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exam,male,18,NA,asian,2,227,FALSE,NA,FALSE,FALSE,7.5,13,NA,NA,NA,TRUE,40000 +75932,both interview and exam,male,41,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,100000 +75933,both interview and exam,female,53,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +75934,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,7500 +75935,both interview and exam,male,4,NA,mexican american,1,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +75936,both interview and exam,female,35,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,never_married,no,FALSE,12500 +75937,both interview and exam,male,77,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +75938,both interview and exam,female,33,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +75939,both interview and exam,male,13,NA,black,1,163,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +75940,both interview and exam,male,4,NA,white,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75941,both interview and exam,male,8,NA,white,2,98,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +75942,both interview and exam,male,78,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +75943,both interview and exam,male,2,NA,mexican american,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,2500 +75944,both interview and exam,male,16,NA,asian,1,202,NA,NA,FALSE,TRUE,12.5,10,NA,NA,NA,TRUE,100000 +75945,both interview and exam,male,60,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,married,NA,TRUE,60000 +75946,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +75947,both interview and exam,female,13,NA,black,1,159,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +75948,both interview and exam,female,5,NA,mexican american,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75949,both interview and exam,female,40,NA,mexican 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exam,female,29,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,4,married,no,TRUE,100000 +75959,both interview and exam,female,0,11,white,1,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75960,both interview and exam,male,76,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +75961,both interview and exam,male,10,NA,mexican american,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +75962,both interview and exam,male,64,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,40000 +75963,both interview and exam,female,6,NA,mexican american,1,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,50000 +75964,both interview and exam,male,71,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75965,both interview and exam,female,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,12500 +75966,both interview and exam,female,37,NA,white,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,never_married,no,TRUE,70000 +75967,both interview and exam,female,7,NA,black,1,88,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +75968,interview only,male,2,24,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75969,both interview and exam,male,69,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,divorced,NA,TRUE,60000 +75970,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +75971,both interview and exam,male,12,NA,black,1,150,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +75972,both interview and exam,female,5,NA,mexican american,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75973,both interview and exam,male,65,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75974,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +75975,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,30000 +75976,both interview and exam,male,67,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,22500 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interview and exam,male,61,NA,black,2,NA,FALSE,NA,FALSE,FALSE,35,NA,3,living_with_partner,NA,TRUE,NA +75997,both interview and exam,female,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +75998,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +75999,both interview and exam,male,19,NA,asian,2,238,FALSE,NA,FALSE,FALSE,3,14,NA,NA,NA,TRUE,7500 +76000,both interview and exam,female,0,2,other hispanic,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76001,both interview and exam,male,16,NA,black,2,204,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +76002,both interview and exam,female,0,5,mexican american,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76003,both interview and exam,female,10,NA,white,2,129,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +76004,both interview and exam,female,58,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,2500 +76005,both interview and exam,female,14,NA,mexican 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exam,male,67,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76024,both interview and exam,female,40,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +76025,both interview and exam,male,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +76026,both interview and exam,female,9,NA,white,2,114,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +76027,both interview and exam,female,5,NA,asian,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +76028,both interview and exam,female,57,NA,black,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,never_married,NA,TRUE,22500 +76029,both interview and exam,male,3,NA,asian,2,46,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76030,both interview and exam,male,32,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76031,both interview and exam,male,4,NA,white,2,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76032,both interview and exam,male,18,NA,mexican american,1,220,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,50000 +76033,both interview and exam,female,69,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,3,divorced,NA,TRUE,30000 +76034,both interview and exam,female,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +76035,both interview and exam,male,0,7,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76036,both interview and exam,male,64,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,1,never_married,NA,FALSE,2500 +76037,both interview and exam,male,60,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,22500 +76038,both interview and exam,female,15,NA,white,1,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,70000 +76039,both interview and exam,female,26,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +76040,both interview and exam,female,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +76041,both interview and exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +76042,both interview and exam,female,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,40000 +76043,both interview and exam,female,64,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +76044,both interview and exam,male,11,NA,mexican american,1,140,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,17500 +76045,both interview and exam,female,12,NA,mexican american,2,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +76046,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +76047,both interview and exam,male,9,NA,white,2,114,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +76048,both interview and exam,male,49,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +76049,both interview and exam,male,54,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,60000 +76050,both interview and 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exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,70000 +76060,both interview and exam,female,32,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76061,both interview and exam,female,10,NA,black,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +76062,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,40000 +76063,both interview and exam,female,0,3,asian,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +76064,both interview and exam,male,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,70000 +76065,both interview and exam,male,1,21,asian,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76066,both interview and exam,male,17,NA,other hispanic,1,216,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +76067,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +76068,both interview and exam,female,13,NA,black,1,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +76069,both interview and exam,male,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76070,interview only,male,15,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +76071,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76072,both interview and exam,male,73,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,1,married,NA,TRUE,12500 +76073,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +76074,both interview and exam,male,70,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,60000 +76075,both interview and exam,male,35,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +76076,both interview and exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,22500 +76077,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +76078,both interview and exam,male,48,NA,other hispanic,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76079,both interview and exam,female,19,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,22500 +76080,both interview and exam,female,6,NA,mexican american,1,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,22500 +76081,both interview and exam,male,35,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76082,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76083,both interview and exam,male,11,NA,white,2,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +76084,both interview and exam,male,48,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76085,both interview and exam,male,2,NA,other hispanic,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76086,both interview and exam,male,18,NA,white,2,224,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +76087,both interview and exam,male,55,NA,other 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interview and exam,male,39,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +76107,both interview and exam,female,59,NA,other,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,22500 +76108,both interview and exam,male,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,100000 +76109,both interview and exam,male,36,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +76110,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +76111,both interview and exam,male,2,NA,black,1,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76112,both interview and exam,male,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76113,interview only,female,5,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76114,both interview and exam,male,18,NA,white,1,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +76115,both interview and exam,female,15,NA,asian,2,192,NA,NA,FALSE,FALSE,0.5,9,NA,NA,NA,TRUE,40000 +76116,both interview and exam,male,68,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +76117,both interview and exam,female,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +76118,both interview and exam,female,60,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,never_married,NA,TRUE,40000 +76119,both interview and exam,male,49,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +76120,both interview and exam,male,40,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +76121,both interview and exam,male,11,NA,black,1,140,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +76122,both interview and exam,female,0,8,mexican american,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +76123,both interview and exam,male,0,4,other hispanic,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +76124,both interview and exam,male,0,9,white,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 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exam,male,58,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +76135,both interview and exam,male,16,NA,black,1,200,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +76136,both interview and exam,female,53,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,NA,FALSE,50000 +76137,both interview and exam,male,56,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +76138,both interview and exam,female,39,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +76139,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +76140,both interview and exam,female,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,30000 +76141,interview only,female,40,NA,white,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,unable to ascertain,TRUE,NA +76142,interview only,male,2,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76143,both interview and exam,female,1,16,mexican 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exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76153,both interview and exam,male,16,NA,other hispanic,2,201,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,7500 +76154,both interview and exam,female,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,50000 +76155,both interview and exam,male,10,NA,mexican american,1,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +76156,both interview and exam,male,61,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,separated,NA,TRUE,87500 +76157,interview only,female,50,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +76158,both interview and exam,female,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +76159,both interview and exam,male,75,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,30000 +76160,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,yes,TRUE,30000 +76161,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +76162,both interview and exam,female,10,NA,other hispanic,2,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +76163,interview only,female,10,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +76164,both interview and exam,female,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +76165,both interview and exam,female,7,NA,mexican american,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,40000 +76166,interview only,female,8,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +76167,both interview and exam,female,42,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,no,TRUE,NA +76168,both interview and exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,22500 +76169,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,50000 +76170,both interview and exam,female,55,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,divorced,NA,TRUE,100000 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exam,male,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,2500 +76181,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +76182,both interview and exam,male,3,NA,white,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76183,both interview and exam,female,17,NA,white,2,216,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,60000 +76184,both interview and exam,male,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +76185,both interview and exam,female,3,NA,asian,2,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76186,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,married,NA,TRUE,NA +76187,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76188,both interview and exam,female,74,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,divorced,NA,TRUE,12500 +76189,both interview and exam,female,15,NA,mexican 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exam,male,51,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76209,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76210,both interview and exam,female,17,NA,mexican american,2,207,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +76211,both interview and exam,male,17,NA,mexican american,1,212,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +76212,both interview and exam,female,34,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,no,TRUE,60000 +76213,both interview and exam,male,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +76214,both interview and exam,female,18,NA,mexican american,2,218,FALSE,NA,FALSE,FALSE,12.5,11,NA,NA,NA,TRUE,40000 +76215,both interview and exam,female,43,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +76216,both interview and exam,male,13,NA,white,2,167,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +76217,both interview and exam,female,53,NA,mexican 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interview and exam,female,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,17500 +76228,both interview and exam,male,1,21,black,1,21,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76229,both interview and exam,male,17,NA,other hispanic,2,208,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +76230,both interview and exam,male,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,NA +76231,both interview and exam,male,25,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +76232,both interview and exam,male,29,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,living_with_partner,NA,FALSE,17500 +76233,both interview and exam,female,54,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,NA +76234,both interview and exam,female,17,NA,mexican american,1,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,12500 +76235,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +76236,both interview 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exam,female,68,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +76491,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,yes,TRUE,40000 +76492,interview only,female,55,NA,white,NA,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,100000 +76493,both interview and exam,male,38,NA,black,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,living_with_partner,NA,TRUE,NA +76494,both interview and exam,male,29,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,divorced,NA,TRUE,22500 +76495,both interview and exam,male,3,NA,asian,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76496,both interview and exam,female,23,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,separated,no,FALSE,7500 +76497,both interview and exam,female,7,NA,mexican american,1,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +76498,both interview and exam,male,6,NA,asian,2,81,NA,NA,FALSE,FALSE,7.5,1,NA,NA,NA,TRUE,40000 +76499,both interview and 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exam,female,7,NA,black,2,95,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +76547,both interview and exam,male,16,NA,asian,2,197,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +76548,both interview and exam,male,62,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +76549,both interview and exam,male,74,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,7500 +76550,both interview and exam,male,70,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,30000 +76551,both interview and exam,female,56,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,100000 +76552,both interview and exam,female,31,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,yes,TRUE,17500 +76553,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +76554,both interview and exam,female,10,NA,other,2,123,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +76555,both interview and 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hispanic,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +76565,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,87500 +76566,both interview and exam,female,4,NA,mexican american,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +76567,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +76568,both interview and exam,female,64,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,70000 +76569,both interview and exam,male,45,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,17500 +76570,both interview and exam,male,3,NA,black,2,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76571,both interview and exam,male,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,87500 +76572,both interview and exam,female,6,NA,white,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,70000 +76573,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,87500 +76574,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +76575,both interview and exam,female,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76576,both interview and exam,female,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,87500 +76577,both interview and exam,female,23,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,30000 +76578,both interview and exam,male,43,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,living_with_partner,NA,FALSE,50000 +76579,both interview and exam,female,16,NA,mexican american,2,193,NA,NA,FALSE,FALSE,12.5,8,NA,NA,NA,FALSE,12500 +76580,both interview and exam,female,71,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,40000 +76581,both interview and exam,female,13,NA,white,1,161,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,70000 +76582,both interview and exam,male,3,NA,black,2,46,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +76583,both interview and exam,male,15,NA,black,1,192,NA,NA,FALSE,FALSE,7.5,9,NA,NA,NA,TRUE,22500 +76584,both interview and exam,female,49,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76585,both interview and exam,female,6,NA,black,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,60000 +76586,both interview and exam,female,45,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,7500 +76587,both interview and exam,male,62,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,100000 +76588,both interview and exam,female,13,NA,mexican american,2,165,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,22500 +76589,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +76590,both interview and exam,female,67,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,50000 +76591,both interview and exam,female,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +76592,both interview and exam,male,5,NA,mexican american,1,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76593,both interview and exam,male,76,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,widowed,NA,TRUE,7500 +76594,both interview and exam,male,10,NA,white,2,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +76595,both interview and exam,female,11,NA,asian,1,143,NA,NA,FALSE,FALSE,3,6,NA,NA,NA,TRUE,7500 +76596,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +76597,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +76598,both interview and exam,male,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,4,divorced,NA,TRUE,60000 +76599,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +76600,both interview and exam,female,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,yes,TRUE,2500 +76601,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +76602,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +76603,both interview and exam,male,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,2500 +76604,both interview and exam,male,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,22500 +76605,both interview and exam,male,12,NA,other hispanic,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,17500 +76606,both interview and exam,female,57,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,NA,TRUE,100000 +76607,both interview and exam,male,2,NA,other hispanic,1,31,NA,NA,FALSE,TRUE,0.5,NA,NA,NA,NA,TRUE,7500 +76608,both interview and exam,female,38,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,12500 +76609,both interview and exam,female,21,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,never_married,no,TRUE,17500 +76610,both interview and exam,male,7,NA,black,2,90,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +76611,both interview and exam,male,16,NA,mexican american,1,201,NA,NA,FALSE,FALSE,12.5,10,NA,NA,NA,TRUE,22500 +76612,both interview and exam,male,62,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,FALSE,100000 +76613,both interview and exam,male,32,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,100000 +76614,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +76615,both interview and exam,male,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +76616,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +76617,both interview and exam,male,18,NA,black,1,219,FALSE,NA,FALSE,FALSE,12.5,12,NA,NA,NA,TRUE,22500 +76618,both interview and exam,male,9,NA,black,1,121,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +76619,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,12500 +76620,both interview and exam,female,3,NA,asian,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76621,both interview and exam,female,1,21,other,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76622,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +76623,both interview and exam,male,41,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +76624,both interview and exam,male,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +76625,both interview and exam,male,10,NA,black,1,128,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +76626,both interview and exam,female,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76627,both interview and exam,female,76,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +76628,both interview and exam,male,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76629,both interview and exam,male,25,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +76630,both interview and exam,female,39,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,divorced,no,TRUE,7500 +76631,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,17500 +76632,both interview and exam,male,49,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,TRUE,70000 +76633,both interview and exam,male,48,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +76634,both interview and exam,female,43,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,no,TRUE,40000 +76635,both interview and exam,male,59,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +76636,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,yes,TRUE,30000 +76637,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +76638,both interview and exam,female,63,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +76639,both interview and exam,male,43,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,2500 +76640,both interview and exam,female,6,NA,white,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +76641,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,22500 +76642,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,no,TRUE,60000 +76643,both interview and exam,female,41,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,87500 +76644,both interview and exam,male,10,NA,mexican american,1,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +76645,both interview and exam,male,52,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +76646,both interview and exam,female,1,23,mexican american,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +76647,both interview and exam,female,8,NA,white,2,107,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +76648,both interview and exam,female,74,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,NA +76649,both interview and exam,male,59,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,NA,TRUE,12500 +76650,both interview and exam,female,8,NA,white,1,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +76651,both interview and exam,female,0,8,asian,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76652,both interview and exam,male,3,NA,other hispanic,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76653,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +76654,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +76655,both interview and exam,female,64,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,divorced,NA,FALSE,7500 +76656,both interview and exam,female,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,40000 +76657,both interview and exam,female,49,NA,black,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,never_married,NA,TRUE,NA +76658,both interview and exam,female,9,NA,white,2,111,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +76659,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,NA +76660,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,FALSE,FALSE,45,NA,3,widowed,NA,TRUE,12500 +76661,both interview and exam,female,9,NA,black,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +76662,both interview and exam,male,12,NA,mexican american,2,156,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +76663,both interview and exam,male,71,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,NA +76664,both interview and exam,female,0,6,white,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76665,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76666,both interview and exam,female,65,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,widowed,NA,TRUE,12500 +76667,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76668,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76669,both interview and exam,male,63,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,never_married,NA,FALSE,60000 +76670,both interview and exam,male,49,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,70000 +76671,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76672,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +76673,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76674,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,living_with_partner,no,TRUE,22500 +76675,both interview and exam,male,48,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +76676,both interview and exam,male,41,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,50000 +76677,both interview and exam,female,18,NA,mexican american,1,220,FALSE,NA,FALSE,FALSE,12.5,14,NA,NA,NA,TRUE,30000 +76678,both interview and exam,male,10,NA,white,1,123,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +76679,both interview and exam,female,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +76680,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76681,both interview and exam,male,1,16,black,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76682,both interview and exam,female,13,NA,black,1,167,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +76683,both interview and exam,male,15,NA,other hispanic,1,192,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +76684,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +76685,both interview and exam,female,4,NA,mexican american,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76686,both interview and exam,male,34,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,married,NA,FALSE,NA +76687,both interview and exam,male,79,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,22500 +76688,both interview and exam,male,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,40000 +76689,interview only,female,69,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +76690,both interview and exam,female,14,NA,black,2,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,NA +76691,both interview and exam,male,38,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,4,never_married,NA,TRUE,NA +76692,both interview and exam,female,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +76693,both interview and exam,male,7,NA,black,1,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +76694,both interview and exam,male,8,NA,white,2,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +76695,interview only,female,80,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +76696,both interview and exam,female,7,NA,other,1,92,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,2500 +76697,both interview and exam,male,24,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,30000 +76698,both interview and exam,female,66,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,50000 +76699,both interview and exam,female,16,NA,black,1,201,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +76700,both interview and exam,male,53,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,FALSE,17500 +76701,both interview and exam,female,3,NA,black,2,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76702,both interview and exam,male,62,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +76703,both interview and exam,male,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +76704,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +76705,both interview and exam,female,50,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +76706,both interview and exam,male,60,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +76707,both interview and exam,female,46,NA,black,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,never_married,NA,TRUE,22500 +76708,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,2500 +76709,both interview and exam,male,74,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +76710,both interview and exam,male,1,13,asian,2,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76711,both interview and exam,male,11,NA,black,2,134,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,60000 +76712,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76713,both interview and exam,female,2,NA,other,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76714,both interview and exam,female,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +76715,both interview and exam,male,74,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +76716,both interview and exam,female,18,NA,white,2,221,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +76717,both interview and exam,female,0,5,black,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76718,both interview and exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +76719,both interview and exam,female,39,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,50000 +76720,both interview and exam,female,15,NA,mexican american,2,191,NA,NA,FALSE,FALSE,3,10,NA,NA,NA,FALSE,30000 +76721,both interview and exam,female,9,NA,white,2,117,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +76722,both interview and exam,male,73,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76723,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +76724,both interview and exam,female,13,NA,asian,2,165,NA,NA,FALSE,FALSE,7.5,8,NA,NA,NA,TRUE,30000 +76725,both interview and exam,male,14,NA,white,2,170,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +76726,both interview and exam,female,0,0,asian,1,0,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76727,both interview and exam,female,7,NA,mexican american,1,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,60000 +76728,both interview and exam,male,8,NA,black,1,104,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +76729,both interview and exam,female,0,7,asian,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76730,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +76731,both interview and exam,male,41,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,FALSE,70000 +76732,both interview and exam,female,19,NA,mexican american,2,231,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,87500 +76733,both interview and exam,male,77,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +76734,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +76735,both interview and exam,female,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +76736,both interview and exam,female,30,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,yes,TRUE,100000 +76737,both interview and exam,female,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +76738,both interview and exam,female,63,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,divorced,NA,TRUE,100000 +76739,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,17500 +76740,both interview and exam,female,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76741,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +76742,both interview and exam,male,40,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +76743,both interview and exam,male,2,NA,white,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76744,both interview and exam,female,5,NA,asian,1,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +76745,both interview and exam,male,70,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,widowed,NA,FALSE,87500 +76746,both interview and exam,male,55,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,25,NA,5,never_married,NA,TRUE,NA +76747,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +76748,both interview and exam,male,1,13,white,1,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76749,both interview and exam,male,7,NA,mexican american,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,30000 +76750,both interview and exam,female,9,NA,mexican american,1,116,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,17500 +76751,both interview and exam,female,36,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,unable to ascertain,FALSE,70000 +76752,both interview and exam,male,4,NA,other hispanic,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76753,both interview and exam,male,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,70000 +76754,both interview and exam,male,76,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76755,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +76756,both interview and exam,male,44,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,TRUE,17500 +76757,both interview and exam,male,79,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,separated,NA,TRUE,40000 +76758,both interview and exam,male,15,NA,other,2,187,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +76759,both interview and exam,male,0,1,black,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76760,both interview and exam,female,16,NA,mexican american,1,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +76761,both interview and exam,female,0,10,mexican american,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +76762,both interview and exam,female,3,NA,mexican american,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76763,both interview and exam,female,12,NA,mexican american,1,146,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,60000 +76764,both interview and exam,female,61,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +76765,both interview and exam,female,13,NA,black,2,166,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +76766,both interview and exam,female,11,NA,black,1,135,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 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exam,male,5,NA,asian,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76777,both interview and exam,male,29,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +76778,both interview and exam,male,18,NA,mexican american,2,218,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +76779,both interview and exam,female,71,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,widowed,NA,FALSE,22500 +76780,both interview and exam,female,7,NA,white,2,92,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +76781,both interview and exam,male,1,22,white,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76782,interview only,female,2,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +76783,both interview and exam,female,9,NA,black,1,113,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +76784,both interview and exam,female,11,NA,white,2,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +76785,both interview and exam,male,22,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +76786,both interview and exam,female,9,NA,white,1,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +76787,both interview and exam,male,11,NA,mexican american,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +76788,both interview and exam,male,4,NA,mexican american,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +76789,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76790,both interview and exam,female,6,NA,black,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +76791,both interview and exam,female,15,NA,mexican american,1,189,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +76792,both interview and exam,female,38,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,40000 +76793,both interview and exam,female,45,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +76794,both interview and exam,female,12,NA,black,2,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +76795,both interview and exam,male,11,NA,black,1,144,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +76796,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +76797,both interview and exam,female,60,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,12500 +76798,both interview and exam,female,5,NA,other hispanic,2,62,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +76799,both interview and exam,male,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +76800,both interview and exam,male,18,NA,white,2,225,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,12500 +76801,both interview and exam,male,0,4,other hispanic,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76802,both interview and exam,male,57,NA,black,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,TRUE,17500 +76803,both interview and exam,male,12,NA,mexican american,2,146,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +76804,both interview and exam,male,10,NA,white,1,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +76805,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +76806,both interview and exam,female,14,NA,white,1,178,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +76807,both interview and exam,female,72,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +76808,interview only,female,4,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76809,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +76810,both interview and exam,female,54,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,2,married,NA,FALSE,NA +76811,both interview and exam,female,27,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,never_married,no,TRUE,50000 +76812,both interview and exam,female,4,NA,asian,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76813,interview only,female,31,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,unable to ascertain,TRUE,22500 +76814,both interview and exam,male,62,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76815,both interview and exam,male,44,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,NA +76816,interview only,female,30,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,unable to ascertain,TRUE,7500 +76817,both interview and exam,male,54,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +76818,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +76819,both interview and exam,female,54,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,35,NA,5,married,NA,TRUE,100000 +76820,both interview and exam,male,46,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +76821,both interview and exam,male,18,NA,mexican american,1,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +76822,both interview and exam,female,16,NA,mexican american,2,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,30000 +76823,both interview and exam,female,6,NA,other,2,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +76824,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +76825,both interview and exam,male,28,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,30000 +76826,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +76827,both interview and exam,female,72,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,widowed,NA,FALSE,12500 +76828,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,no,TRUE,22500 +76829,both interview and exam,male,12,NA,black,2,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,22500 +76830,both interview and exam,male,10,NA,white,2,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +76831,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,40000 +76832,both interview and exam,female,5,NA,white,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76833,both interview and exam,female,7,NA,mexican american,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,70000 +76834,both interview and exam,female,16,NA,mexican american,2,194,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,30000 +76835,both interview and exam,female,40,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,12500 +76836,interview only,female,3,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +76837,both interview and exam,male,40,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,TRUE,100000 +76838,both interview and exam,female,2,NA,asian,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76839,both interview and exam,female,6,NA,mexican american,2,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,22500 +76840,both interview and exam,female,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +76841,both interview and exam,male,6,NA,white,1,79,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +76842,both interview and exam,male,62,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,3,married,NA,FALSE,87500 +76843,both interview and exam,male,59,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,17500 +76844,both interview and exam,female,4,NA,black,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76845,both interview and exam,male,17,NA,white,2,215,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +76846,both interview and exam,female,26,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,50000 +76847,both interview and exam,female,35,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +76848,interview only,female,31,NA,other,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,17500 +76849,both interview and exam,male,79,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +76850,both interview and exam,female,7,NA,mexican american,2,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +76851,both interview and exam,female,73,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,1,living_with_partner,NA,FALSE,NA +76852,both interview and exam,male,0,2,white,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +76853,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76854,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76855,both interview and exam,female,0,8,mexican american,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +76856,both interview and exam,male,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +76857,both interview and exam,male,13,NA,white,2,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,70000 +76858,both interview and exam,female,8,NA,other,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +76859,both interview and exam,male,32,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,100000 +76860,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,40000 +76861,both interview and exam,female,3,NA,mexican american,1,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +76862,interview only,female,9,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +76863,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +76864,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,22500 +76865,both interview and exam,male,18,NA,black,1,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +76866,both interview and exam,male,11,NA,black,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +76867,both interview and exam,male,51,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +76868,both interview and exam,male,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +76869,both interview and exam,female,16,NA,mexican american,2,205,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,12500 +76870,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +76871,both interview and exam,female,70,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +76872,both interview and exam,male,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +76873,both interview and exam,female,5,NA,black,1,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76874,both interview and exam,male,10,NA,asian,1,121,NA,NA,FALSE,FALSE,7.5,3,NA,NA,NA,TRUE,7500 +76875,both interview and exam,male,4,NA,white,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76876,both interview and exam,male,1,18,mexican american,1,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76877,both interview and exam,female,52,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +76878,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +76879,both interview and 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exam,male,39,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +76964,both interview and exam,male,16,NA,white,1,194,NA,NA,FALSE,TRUE,7.5,9,NA,NA,NA,TRUE,100000 +76965,both interview and exam,male,35,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +76966,both interview and exam,female,48,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76967,both interview and exam,female,3,NA,white,1,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +76968,both interview and exam,male,34,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,30000 +76969,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +76970,both interview and exam,female,19,NA,asian,2,229,FALSE,NA,FALSE,TRUE,17.5,13,NA,NA,NA,TRUE,60000 +76971,both interview and exam,male,6,NA,asian,1,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +76972,both interview and exam,male,57,NA,mexican 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exam,female,6,NA,black,1,72,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +76982,both interview and exam,female,8,NA,asian,2,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +76983,both interview and exam,male,11,NA,other,1,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +76984,both interview and exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +76985,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76986,both interview and exam,male,2,NA,mexican american,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76987,both interview and exam,female,33,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,3,living_with_partner,no,FALSE,17500 +76988,both interview and exam,male,67,NA,asian,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76989,both interview and exam,female,9,NA,black,1,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +76990,both interview and 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exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +77018,interview only,female,4,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77019,both interview and exam,female,28,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +77020,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +77021,both interview and exam,male,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77022,both interview and exam,male,54,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +77023,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,60000 +77024,both interview and exam,male,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +77025,both interview and exam,male,55,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,TRUE,60000 +77026,both interview and exam,female,14,NA,mexican 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interview and exam,male,12,NA,mexican american,2,153,NA,NA,FALSE,FALSE,3,6,NA,NA,NA,FALSE,22500 +77037,both interview and exam,female,9,NA,mexican american,1,113,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +77038,both interview and exam,male,9,NA,other,2,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +77039,both interview and exam,female,16,NA,mexican american,2,199,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +77040,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +77041,both interview and exam,male,73,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +77042,both interview and exam,male,6,NA,mexican american,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +77043,both interview and exam,female,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +77044,both interview and exam,male,2,NA,black,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +77045,both interview and exam,male,30,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +77046,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +77047,both interview and exam,male,28,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +77048,both interview and exam,female,1,19,white,2,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77049,both interview and exam,female,66,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,widowed,NA,TRUE,50000 +77050,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +77051,both interview and exam,female,21,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,living_with_partner,no,TRUE,12500 +77052,both interview and exam,female,12,NA,other,2,146,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,17500 +77053,both interview and exam,male,8,NA,white,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +77054,both interview and exam,male,54,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,100000 +77055,both interview and exam,female,45,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +77056,interview only,male,16,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +77057,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +77058,both interview and exam,female,17,NA,mexican american,2,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +77059,both interview and exam,female,6,NA,black,1,83,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +77060,both interview and exam,female,72,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +77061,both interview and exam,female,3,NA,mexican american,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +77062,both interview and exam,male,1,15,white,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77063,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +77064,both interview and exam,male,2,NA,white,2,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +77065,both interview and exam,male,6,NA,white,2,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,22500 +77066,both interview and exam,female,62,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,separated,NA,FALSE,NA +77067,both interview and exam,female,67,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +77068,both interview and exam,male,15,NA,mexican american,1,185,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,40000 +77069,interview only,female,0,2,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77070,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +77071,both interview and exam,male,14,NA,asian,2,181,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,70000 +77072,both interview and exam,male,70,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +77073,both interview and exam,female,67,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 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exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,50000 +77084,both interview and exam,female,3,NA,mexican american,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +77085,both interview and exam,female,0,2,asian,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77086,both interview and exam,female,12,NA,mexican american,2,156,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,7500 +77087,both interview and exam,male,10,NA,black,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +77088,both interview and exam,female,7,NA,mexican american,2,95,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +77089,both interview and exam,male,4,NA,black,1,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77090,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,unable to ascertain,TRUE,50000 +77091,both interview and exam,female,31,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,NA +77092,both interview and exam,male,3,NA,white,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77093,both interview and exam,female,2,NA,white,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77094,both interview and exam,female,57,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,60000 +77095,both interview and exam,male,46,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77096,both interview and exam,female,75,NA,white,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,widowed,NA,TRUE,12500 +77097,both interview and exam,male,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +77098,both interview and exam,male,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +77099,both interview and exam,male,14,NA,mexican american,1,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,17500 +77100,both interview and exam,male,63,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,2,married,NA,FALSE,70000 +77101,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77102,both interview and exam,male,12,NA,black,1,150,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +77103,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,FALSE,50000 +77104,both interview and exam,female,13,NA,black,2,162,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +77105,both interview and exam,male,76,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +77106,both interview and exam,male,6,NA,black,1,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +77107,both interview and exam,female,7,NA,white,1,93,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +77108,both interview and exam,male,19,NA,black,1,231,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,30000 +77109,both interview and exam,male,38,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,FALSE,40000 +77110,both interview and exam,male,3,NA,mexican american,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 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exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +77121,both interview and exam,female,42,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,87500 +77122,both interview and exam,female,14,NA,other hispanic,2,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,40000 +77123,both interview and exam,female,50,NA,other,1,NA,FALSE,NA,FALSE,TRUE,55,NA,4,divorced,NA,TRUE,50000 +77124,both interview and exam,female,9,NA,other hispanic,2,111,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +77125,both interview and exam,male,6,NA,mexican american,1,81,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,22500 +77126,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +77127,both interview and exam,female,41,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,2500 +77128,both interview and exam,male,19,NA,white,1,236,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +77129,both interview and exam,female,10,NA,black,1,132,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +77130,both interview and exam,male,16,NA,other hispanic,1,199,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +77131,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,100000 +77132,both interview and exam,male,25,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77133,both interview and exam,female,2,NA,black,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77134,both interview and exam,male,7,NA,black,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,17500 +77135,both interview and exam,male,10,NA,white,1,124,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +77136,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +77137,both interview and exam,female,5,NA,other,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77138,both interview and exam,female,15,NA,black,1,181,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +77139,both interview and exam,female,71,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,2,widowed,NA,TRUE,12500 +77140,both interview and exam,male,58,NA,mexican american,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +77141,both interview and exam,female,42,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,separated,no,FALSE,30000 +77142,both interview and exam,male,68,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +77143,both interview and exam,female,2,NA,black,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77144,both interview and exam,female,27,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +77145,interview only,male,43,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +77146,both interview and exam,male,2,NA,white,2,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77147,both interview and exam,male,45,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,married,NA,TRUE,60000 +77148,both interview and exam,male,4,NA,other hispanic,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77149,both interview and exam,male,11,NA,black,2,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +77150,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77151,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +77152,both interview and exam,male,10,NA,black,1,131,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +77153,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +77154,both interview and exam,female,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +77155,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +77156,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +77157,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77158,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +77159,both interview and exam,female,38,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,no,TRUE,50000 +77160,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +77161,interview only,female,28,NA,other hispanic,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,unable to ascertain,TRUE,87500 +77162,both interview and exam,female,72,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +77163,both interview and exam,female,66,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,widowed,NA,FALSE,40000 +77164,both interview and exam,female,56,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,TRUE,22500 +77165,both interview and exam,male,10,NA,other hispanic,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77166,both interview and exam,female,2,NA,white,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77167,both interview and exam,female,40,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,no,TRUE,7500 +77168,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +77169,both interview and exam,male,10,NA,black,2,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,17500 +77170,both interview and exam,female,58,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,FALSE,87500 +77171,both interview and exam,female,69,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,widowed,NA,TRUE,30000 +77172,both interview and exam,male,42,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,NA +77173,both interview and exam,female,16,NA,asian,2,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +77174,both interview and exam,male,22,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +77175,both interview and exam,female,4,NA,other hispanic,2,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +77176,both interview and exam,female,41,NA,mexican 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exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +77280,both interview and exam,male,42,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +77281,both interview and exam,female,13,NA,white,1,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,2500 +77282,both interview and exam,male,20,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,3,NA,2,never_married,NA,TRUE,NA +77283,interview only,female,46,NA,asian,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77284,both interview and exam,male,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +77285,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,12500 +77286,both interview and exam,female,4,NA,mexican american,1,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,2500 +77287,both interview and exam,female,53,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77288,both interview and 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interview and exam,male,2,NA,mexican american,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +77335,both interview and exam,female,10,NA,white,2,123,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,2500 +77336,both interview and exam,male,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +77337,both interview and exam,female,23,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,never_married,no,FALSE,40000 +77338,both interview and exam,male,6,NA,mexican american,1,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,22500 +77339,both interview and exam,female,41,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +77340,both interview and exam,female,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +77341,both interview and exam,female,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,40000 +77342,both interview and exam,male,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +77343,both interview and exam,male,2,NA,mexican 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interview and exam,female,8,NA,white,1,98,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +77364,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +77365,both interview and exam,male,23,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77366,both interview and exam,male,6,NA,other,1,80,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +77367,both interview and exam,female,48,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +77368,both interview and exam,female,43,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,no,FALSE,40000 +77369,both interview and exam,female,21,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +77370,both interview and exam,male,14,NA,black,1,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,2500 +77371,both interview and exam,female,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77372,both interview and exam,female,7,NA,white,2,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +77373,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +77374,both interview and exam,female,46,NA,black,1,NA,TRUE,FALSE,FALSE,TRUE,25,NA,5,divorced,NA,TRUE,40000 +77375,interview only,female,1,23,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +77376,both interview and exam,male,60,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,40000 +77377,both interview and exam,male,36,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +77378,both interview and exam,male,2,NA,mexican american,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77379,both interview and exam,male,12,NA,black,1,148,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +77380,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77381,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,30000 +77382,both interview and exam,male,1,13,mexican american,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +77383,both interview and exam,male,80,NA,black,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,60000 +77384,both interview and exam,female,14,NA,black,2,179,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,60000 +77385,both interview and exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +77386,both interview and exam,female,31,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,no,TRUE,70000 +77387,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +77388,both interview and exam,male,46,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +77389,both interview and exam,male,4,NA,white,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +77390,both interview and exam,male,3,NA,other,2,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 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exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +77401,both interview and exam,female,0,4,black,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77402,both interview and exam,female,5,NA,other hispanic,2,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77403,both interview and exam,male,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +77404,both interview and exam,female,8,NA,black,2,107,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,50000 +77405,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,70000 +77406,interview only,male,8,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +77407,both interview and exam,female,44,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,separated,no,TRUE,17500 +77408,both interview and exam,female,79,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,widowed,NA,TRUE,12500 +77409,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,no,TRUE,NA +77410,interview only,male,6,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +77411,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,22500 +77412,both interview and exam,female,9,NA,white,1,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +77413,both interview and exam,female,2,NA,white,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77414,both interview and exam,male,32,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,married,NA,FALSE,30000 +77415,both interview and exam,female,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +77416,interview only,female,14,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +77417,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +77418,both interview and exam,female,8,NA,black,2,103,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +77419,both interview and exam,male,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77420,both interview and exam,female,18,NA,mexican american,1,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +77421,interview only,female,5,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77422,both interview and exam,male,80,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77423,both interview and exam,male,74,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +77424,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,no,TRUE,30000 +77425,both interview and exam,male,66,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,NA +77426,both interview and exam,male,14,NA,other hispanic,1,176,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +77427,both interview and exam,female,0,4,white,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77428,both interview and exam,female,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,30000 +77429,both interview and exam,female,76,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +77430,both interview and exam,female,1,19,white,2,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77431,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,12500 +77432,both interview and exam,male,4,NA,other hispanic,2,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +77433,both interview and exam,female,58,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,widowed,NA,TRUE,70000 +77434,both interview and exam,male,5,NA,asian,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77435,both interview and exam,female,10,NA,other hispanic,2,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,22500 +77436,both interview and exam,female,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77437,both interview and exam,male,6,NA,black,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,70000 +77438,both interview and exam,female,41,NA,mexican 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exam,male,12,NA,white,1,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +77458,both interview and exam,male,50,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +77459,both interview and exam,male,29,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,never_married,NA,TRUE,40000 +77460,both interview and exam,male,45,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,divorced,NA,FALSE,40000 +77461,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,2500 +77462,both interview and exam,male,6,NA,black,2,75,NA,NA,FALSE,FALSE,3,1,NA,NA,NA,TRUE,22500 +77463,both interview and exam,female,50,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,60000 +77464,both interview and exam,female,36,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,22500 +77465,both interview and exam,female,21,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,100000 +77466,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,60000 +77467,both interview and exam,female,4,NA,mexican american,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +77468,both interview and exam,male,54,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +77469,both interview and exam,female,67,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +77470,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,87500 +77471,both interview and exam,male,62,NA,white,1,NA,TRUE,TRUE,FALSE,TRUE,25,NA,5,married,NA,TRUE,50000 +77472,both interview and exam,female,0,6,other hispanic,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77473,both interview and exam,female,31,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +77474,both interview and exam,female,14,NA,white,2,180,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,87500 +77475,both interview and exam,male,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77476,both interview and exam,male,9,NA,black,2,112,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +77477,both interview and exam,male,59,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,NA,TRUE,100000 +77478,both interview and exam,male,4,NA,other hispanic,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +77479,both interview and exam,male,4,NA,black,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +77480,both interview and exam,male,11,NA,black,1,139,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +77481,both interview and exam,female,54,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,22500 +77482,both interview and exam,female,5,NA,mexican american,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77483,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +77484,both interview and exam,male,40,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,7500 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exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +77495,both interview and exam,male,10,NA,other,2,131,NA,NA,FALSE,TRUE,7.5,5,NA,NA,NA,TRUE,17500 +77496,both interview and exam,male,1,22,other hispanic,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +77497,both interview and exam,male,9,NA,black,2,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +77498,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77499,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77500,both interview and exam,female,3,NA,mexican american,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77501,both interview and exam,male,5,NA,other,2,73,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77502,both interview and exam,female,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77503,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,2500 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hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,separated,NA,TRUE,100000 +77514,both interview and exam,male,1,16,other,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77515,both interview and exam,female,66,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +77516,both interview and exam,male,16,NA,black,2,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,50000 +77517,both interview and exam,female,15,NA,white,1,187,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +77518,both interview and exam,male,16,NA,white,1,204,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,50000 +77519,both interview and exam,female,16,NA,mexican american,2,197,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,7500 +77520,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +77521,both interview and exam,male,41,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77522,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,40000 +77523,interview only,female,72,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +77524,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +77525,interview only,male,1,18,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77526,both interview and exam,female,0,5,mexican american,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77527,both interview and exam,male,47,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,NA,FALSE,NA +77528,both interview and exam,male,40,NA,asian,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77529,both interview and exam,male,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77530,both interview and exam,female,2,NA,black,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77531,both interview and exam,male,5,NA,black,1,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77532,both interview and exam,male,15,NA,other,2,187,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +77533,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +77534,both interview and exam,female,15,NA,white,1,186,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +77535,both interview and exam,male,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,40000 +77536,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,divorced,NA,TRUE,40000 +77537,both interview and exam,male,8,NA,black,1,103,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +77538,both interview and exam,male,23,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +77539,both interview and exam,female,38,NA,black,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,no,TRUE,100000 +77540,both interview and exam,male,43,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +77541,both interview and exam,male,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77542,both interview and exam,male,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,22500 +77543,both interview and exam,male,43,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +77544,both interview and exam,male,0,8,mexican american,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +77545,both interview and exam,male,1,17,other hispanic,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77546,both interview and exam,male,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +77547,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +77548,both interview and exam,male,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +77549,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +77550,both interview and exam,male,26,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +77551,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +77552,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +77553,both interview and exam,female,2,NA,other hispanic,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +77554,both interview and exam,female,5,NA,mexican american,1,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77555,both interview and exam,male,9,NA,mexican american,2,120,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +77556,both interview and exam,male,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +77557,both interview and exam,female,8,NA,other hispanic,1,106,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +77558,both interview and exam,female,2,NA,white,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77559,both interview and exam,female,0,5,mexican american,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +77560,both interview and exam,female,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,87500 +77561,both interview and exam,female,7,NA,mexican american,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,40000 +77562,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,40000 +77563,both interview and exam,male,36,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +77564,both interview and exam,male,1,23,mexican american,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77565,both interview and exam,female,2,NA,black,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77566,both interview and exam,female,0,2,mexican american,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +77567,interview only,female,1,19,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +77568,both interview and exam,male,3,NA,black,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77569,both interview and exam,female,48,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,FALSE,7500 +77570,both interview and exam,female,9,NA,mexican american,2,116,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,2500 +77571,both interview and exam,female,18,NA,other,2,220,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +77572,both interview and exam,male,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77573,both interview and exam,male,9,NA,mexican american,2,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,30000 +77574,both interview and exam,male,10,NA,other hispanic,2,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +77575,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +77576,both interview and exam,female,0,4,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77577,both interview and exam,female,33,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +77578,both interview and exam,male,45,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,married,NA,FALSE,40000 +77579,both interview and exam,male,15,NA,other hispanic,1,190,NA,NA,FALSE,TRUE,12.5,9,NA,NA,NA,TRUE,22500 +77580,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +77581,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +77582,both interview and exam,male,10,NA,asian,1,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77583,both interview and exam,female,7,NA,mexican american,1,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,17500 +77584,both interview and exam,female,35,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,50000 +77585,both interview and exam,male,36,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,living_with_partner,NA,FALSE,40000 +77586,both interview and exam,male,65,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77587,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +77588,both interview and exam,female,6,NA,other,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +77589,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +77590,both interview and exam,male,9,NA,other hispanic,1,109,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,17500 +77591,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77592,both interview and exam,female,52,NA,black,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,divorced,NA,TRUE,40000 +77593,both interview and exam,female,3,NA,other,2,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +77594,both interview and exam,male,3,NA,other hispanic,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +77595,both interview and exam,female,13,NA,black,1,168,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +77596,both interview and exam,male,49,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,FALSE,NA +77597,both interview and exam,male,58,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,2,married,NA,FALSE,30000 +77598,both interview and exam,male,79,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,17500 +77599,both interview and exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +77600,both interview and exam,female,58,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,divorced,NA,TRUE,40000 +77601,both interview and exam,male,42,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77602,both interview and exam,male,14,NA,white,2,171,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +77603,both interview and exam,female,56,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,70000 +77604,both interview and exam,male,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +77605,both interview and exam,male,55,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,50000 +77606,both interview and exam,male,14,NA,white,1,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +77607,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,no,TRUE,40000 +77608,both interview and exam,male,7,NA,mexican american,2,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +77609,both interview and exam,female,61,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,60000 +77610,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +77611,both interview and exam,female,35,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,never_married,no,TRUE,100000 +77612,both interview and exam,male,22,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77613,both interview and exam,male,19,NA,other hispanic,2,234,FALSE,NA,FALSE,FALSE,3,9,NA,NA,NA,FALSE,22500 +77614,both interview and exam,female,9,NA,other,2,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +77615,both interview and exam,female,19,NA,other hispanic,2,230,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +77616,both interview and exam,female,35,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +77617,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,2500 +77618,both interview and exam,female,25,NA,other,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,never_married,no,TRUE,12500 +77619,both interview and exam,male,0,9,asian,1,9,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,70000 +77620,both interview and exam,female,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +77621,both interview and exam,female,68,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +77622,both interview and exam,female,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +77623,both interview and exam,female,79,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,60000 +77624,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +77625,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,30000 +77626,both interview and exam,female,18,NA,mexican american,2,224,FALSE,NA,FALSE,FALSE,7.5,12,NA,NA,NA,FALSE,30000 +77627,both interview and exam,female,3,NA,black,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77628,both interview and exam,male,7,NA,mexican american,2,95,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +77629,both interview and exam,male,17,NA,black,2,204,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +77630,both interview and exam,male,45,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77631,both interview and exam,female,59,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,divorced,NA,TRUE,30000 +77632,both interview and exam,male,39,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +77633,interview only,female,11,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +77634,both interview and exam,female,67,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,5,divorced,NA,FALSE,7500 +77635,both interview and exam,male,6,NA,other,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +77636,both interview and exam,male,6,NA,other hispanic,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +77637,both interview and exam,female,6,NA,other,1,76,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +77638,both interview and exam,female,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +77639,both interview and exam,female,28,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,never_married,no,FALSE,40000 +77640,both interview and exam,male,46,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +77641,both interview and exam,male,16,NA,asian,2,200,NA,NA,FALSE,FALSE,7.5,10,NA,NA,NA,TRUE,NA +77642,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,17500 +77643,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,no,FALSE,30000 +77644,both interview and exam,male,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77645,both interview and exam,female,52,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,TRUE,87500 +77646,both interview and exam,male,18,NA,mexican american,1,221,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,100000 +77647,both interview and exam,male,68,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,55,NA,4,married,NA,TRUE,100000 +77648,both interview and exam,male,0,7,other hispanic,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77649,both interview and exam,male,7,NA,white,1,90,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +77650,both interview and exam,female,0,3,mexican 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interview and exam,male,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +77809,both interview and exam,male,2,NA,asian,1,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77810,both interview and exam,male,8,NA,asian,1,98,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +77811,both interview and exam,male,55,NA,asian,1,NA,FALSE,NA,FALSE,NA,17.5,NA,5,married,NA,TRUE,60000 +77812,both interview and exam,male,10,NA,white,2,124,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +77813,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77814,both interview and exam,male,5,NA,black,1,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77815,both interview and exam,male,66,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +77816,both interview and exam,male,18,NA,white,2,218,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,60000 +77817,both interview and exam,female,8,NA,black,1,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +77818,both interview 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hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,17500 +77828,both interview and exam,female,18,NA,asian,1,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 +77829,both interview and exam,male,18,NA,black,1,220,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +77830,both interview and exam,female,43,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,no,TRUE,12500 +77831,both interview and exam,male,61,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,NA +77832,both interview and exam,female,67,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,2,married,NA,TRUE,30000 +77833,both interview and exam,male,10,NA,asian,2,122,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77834,both interview and exam,male,5,NA,white,1,62,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77835,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +77836,both interview and exam,male,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 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exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,2500 +77847,both interview and exam,male,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +77848,interview only,male,58,NA,black,NA,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,NA +77849,both interview and exam,male,9,NA,black,2,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +77850,interview only,male,45,NA,asian,NA,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +77851,both interview and exam,male,45,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,60000 +77852,both interview and exam,male,72,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,12500 +77853,both interview and exam,male,67,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,TRUE,70000 +77854,both interview and exam,female,1,17,other hispanic,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +77855,both interview and exam,male,23,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,2500 +77856,both interview and exam,male,33,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,87500 +77857,both interview and exam,male,10,NA,mexican american,1,126,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +77858,both interview and exam,female,37,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,12500 +77859,both interview and exam,female,0,6,mexican american,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +77860,both interview and exam,male,13,NA,black,1,164,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,17500 +77861,both interview and exam,female,68,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,NA,TRUE,22500 +77862,both interview and exam,male,18,NA,white,2,227,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,87500 +77863,both interview and exam,male,0,4,asian,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77864,both interview and exam,male,40,NA,black,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,NA,TRUE,40000 +77865,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,22500 +77866,both interview and exam,male,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +77867,both interview and exam,male,68,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,7500 +77868,both interview and exam,male,16,NA,mexican american,2,195,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +77869,both interview and exam,female,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,NA,FALSE,NA +77870,both interview and exam,male,76,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,17500 +77871,both interview and exam,male,16,NA,white,2,193,NA,NA,FALSE,FALSE,0.5,9,NA,NA,NA,TRUE,100000 +77872,both interview and exam,female,42,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,no,FALSE,40000 +77873,both interview and exam,female,0,1,mexican american,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +77874,both interview and exam,male,52,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,7500 +77875,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +77876,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +77877,both interview and exam,female,6,NA,white,2,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +77878,both interview and exam,female,47,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,2500 +77879,both interview and exam,male,1,14,white,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77880,both interview and exam,male,63,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +77881,both interview and exam,female,19,NA,mexican american,2,238,FALSE,NA,FALSE,FALSE,NA,11,NA,NA,NA,TRUE,17500 +77882,both interview and exam,male,3,NA,black,1,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77883,both interview and exam,male,5,NA,white,2,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77884,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,no,TRUE,NA +77885,both interview and exam,female,9,NA,asian,1,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +77886,both interview and exam,female,14,NA,white,2,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +77887,both interview and exam,female,27,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,2,married,yes,TRUE,22500 +77888,both interview and exam,male,75,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,40000 +77889,both interview and exam,male,38,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +77890,both interview and exam,male,9,NA,black,1,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,2500 +77891,both interview and exam,female,55,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,NA,TRUE,60000 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interview and exam,male,6,NA,other hispanic,2,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +77902,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,NA +77903,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +77904,both interview and exam,male,6,NA,other hispanic,2,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,50000 +77905,both interview and exam,female,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,7500 +77906,both interview and exam,male,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,7500 +77907,both interview and exam,female,26,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,60000 +77908,both interview and exam,female,17,NA,mexican american,1,211,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +77909,both interview and exam,female,78,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +77910,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +77911,both interview and exam,male,8,NA,white,2,102,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +77912,both interview and exam,female,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,no,TRUE,22500 +77913,both interview and exam,female,11,NA,white,2,134,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,22500 +77914,both interview and exam,male,13,NA,asian,2,157,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +77915,both interview and exam,female,57,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,40000 +77916,both interview and exam,female,2,NA,mexican american,2,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +77917,both interview and exam,female,68,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,widowed,NA,FALSE,NA +77918,both interview and exam,male,6,NA,other hispanic,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +77919,both interview and exam,female,17,NA,other hispanic,1,209,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +77920,both interview and exam,male,18,NA,black,2,222,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,60000 +77921,both interview and exam,female,7,NA,white,2,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +77922,both interview and exam,male,68,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +77923,both interview and exam,female,10,NA,white,2,131,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +77924,both interview and exam,male,13,NA,mexican american,2,157,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +77925,both interview and exam,male,0,10,black,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77926,both interview and exam,male,6,NA,white,2,75,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,70000 +77927,both interview and exam,female,42,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,3,married,no,TRUE,40000 +77928,both interview and exam,female,0,1,mexican american,2,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +77929,both interview and exam,male,15,NA,other hispanic,1,186,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +77930,both interview and exam,male,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +77931,both interview and exam,male,36,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,3,married,NA,TRUE,12500 +77932,both interview and exam,male,28,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +77933,both interview and exam,female,18,NA,white,2,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +77934,both interview and exam,male,12,NA,white,1,152,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +77935,both interview and exam,female,48,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +77936,both interview and exam,female,43,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,NA +77937,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,12500 +77938,both interview and exam,male,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,50000 +77939,both interview and exam,female,55,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +77940,both interview and exam,male,16,NA,mexican american,1,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +77941,both interview and exam,male,50,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,12500 +77942,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,87500 +77943,both interview and exam,male,38,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +77944,both interview and exam,male,4,NA,other hispanic,2,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +77945,interview only,female,69,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,2500 +77946,interview only,female,9,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,60000 +77947,both interview and exam,male,12,NA,black,1,150,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,2500 +77948,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +77949,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +77950,both interview and exam,male,80,NA,mexican american,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77951,both interview and exam,male,1,17,mexican american,1,18,NA,NA,FALSE,TRUE,0.5,NA,NA,NA,NA,FALSE,70000 +77952,both interview and exam,male,27,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,87500 +77953,both interview and exam,female,33,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,no,TRUE,NA +77954,both interview and exam,female,44,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,no,TRUE,87500 +77955,both interview and exam,male,4,NA,black,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77956,both interview and exam,male,5,NA,black,2,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77957,both interview and exam,female,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,70000 +77958,both interview and exam,male,1,23,black,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77959,both interview and exam,male,44,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77960,both interview and exam,female,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,60000 +77961,both interview and exam,female,11,NA,white,2,134,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77962,both interview and exam,female,8,NA,black,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +77963,both interview and exam,male,32,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77964,both interview and exam,female,3,NA,black,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +77965,both interview and exam,male,47,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 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exam,male,11,NA,asian,1,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77976,both interview and exam,male,73,NA,other,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,12500 +77977,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +77978,both interview and exam,female,3,NA,other hispanic,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +77979,both interview and exam,female,69,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,35,NA,4,married,NA,TRUE,2500 +77980,both interview and exam,male,1,17,other hispanic,2,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77981,both interview and exam,male,1,13,other hispanic,2,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77982,both interview and exam,female,16,NA,black,1,204,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +77983,both interview and exam,male,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +77984,both interview and exam,male,10,NA,white,1,121,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +77985,both interview and exam,female,24,NA,black,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,never_married,no,TRUE,30000 +77986,both interview and exam,male,2,NA,black,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77987,both interview and exam,female,17,NA,other hispanic,2,214,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +77988,both interview and exam,male,17,NA,other hispanic,1,205,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,60000 +77989,both interview and exam,male,53,NA,other hispanic,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +77990,both interview and exam,male,66,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,22500 +77991,both interview and exam,female,30,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,no,TRUE,40000 +77992,both interview and exam,male,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +77993,both interview and exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +77994,both interview and exam,male,64,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +77995,both interview and exam,male,20,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77996,both interview and exam,male,1,16,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77997,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +77998,both interview and exam,male,8,NA,white,2,106,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +77999,both interview and exam,male,51,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +78000,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +78001,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,60000 +78002,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,unable to ascertain,TRUE,100000 +78003,both interview and exam,female,14,NA,other hispanic,2,168,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,NA +78004,both interview and exam,male,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +78005,both interview and exam,female,15,NA,mexican american,1,181,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,17500 +78006,both interview and exam,male,2,NA,black,1,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78007,both interview and exam,female,80,NA,black,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,17500 +78008,both interview and exam,female,33,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,NA +78009,both interview and exam,male,80,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +78010,both interview and exam,male,73,NA,other,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +78011,both interview and exam,male,0,2,black,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78012,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +78013,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,60000 +78014,both interview and exam,female,6,NA,other hispanic,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +78015,both interview and exam,male,47,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,separated,NA,FALSE,7500 +78016,both interview and exam,male,12,NA,white,2,152,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +78017,both interview and exam,male,7,NA,mexican american,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,22500 +78018,both interview and exam,female,47,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,separated,NA,FALSE,22500 +78019,both interview and exam,male,65,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,40000 +78020,both interview and exam,female,42,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,4,married,no,TRUE,40000 +78021,both interview and exam,female,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +78022,both interview and exam,female,2,NA,asian,2,31,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,TRUE,12500 +78023,both interview and exam,male,0,0,mexican american,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78024,both interview and exam,male,33,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +78025,both interview and exam,male,15,NA,white,1,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +78026,both interview and exam,male,4,NA,black,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78027,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +78028,both interview and exam,male,64,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +78029,both interview and exam,male,1,12,other 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exam,male,43,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,100000 +78049,both interview and exam,female,7,NA,asian,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +78050,both interview and exam,male,17,NA,mexican american,2,211,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +78051,both interview and exam,male,40,NA,other,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +78052,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78053,both interview and exam,male,4,NA,black,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78054,both interview and exam,female,23,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,living_with_partner,no,FALSE,NA +78055,both interview and exam,male,9,NA,white,2,120,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +78056,both interview and exam,male,75,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +78057,both interview and exam,male,14,NA,black,1,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +78058,interview only,male,50,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +78059,both interview and exam,male,4,NA,black,1,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78060,both interview and exam,female,2,NA,white,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78061,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78062,both interview and exam,female,0,4,black,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +78063,both interview and exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,22500 +78064,both interview and exam,female,12,NA,black,1,154,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,22500 +78065,both interview and exam,female,13,NA,mexican american,1,164,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,22500 +78066,both interview and exam,male,2,NA,mexican american,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +78067,both interview and exam,female,10,NA,white,2,129,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +78068,both interview and exam,male,19,NA,white,2,235,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +78069,both interview and exam,female,3,NA,black,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78070,both interview and exam,male,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +78071,both interview and exam,female,6,NA,mexican american,2,85,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,17500 +78072,both interview and exam,male,77,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,22500 +78073,both interview and exam,male,14,NA,white,2,176,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +78074,both interview and exam,male,51,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,divorced,NA,FALSE,NA +78075,both interview and exam,male,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +78076,both interview and exam,female,56,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +78077,both interview and exam,male,10,NA,mexican american,1,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,30000 +78078,both interview and exam,male,19,NA,mexican american,1,231,FALSE,NA,FALSE,FALSE,0.5,13,NA,NA,NA,FALSE,22500 +78079,both interview and exam,female,40,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,50000 +78080,both interview and exam,male,58,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,never_married,NA,TRUE,87500 +78081,both interview and exam,female,63,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,87500 +78082,both interview and exam,male,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +78083,both interview and exam,male,53,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +78084,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,12500 +78085,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,never_married,NA,TRUE,100000 +78086,both interview and exam,male,80,NA,black,1,NA,FALSE,NA,FALSE,TRUE,55,NA,1,married,NA,TRUE,17500 +78087,both interview and exam,male,16,NA,black,2,201,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +78088,both interview and exam,male,66,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +78089,both interview and exam,male,62,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,never_married,NA,FALSE,50000 +78090,both interview and exam,female,15,NA,white,1,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +78091,both interview and exam,female,18,NA,other,1,225,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,7500 +78092,both interview and exam,female,6,NA,asian,1,72,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +78093,both interview and exam,male,29,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +78094,both interview and exam,female,39,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +78095,both interview and exam,female,51,NA,other 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american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,22500 +78105,both interview and exam,female,36,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,no,TRUE,7500 +78106,both interview and exam,male,12,NA,black,1,151,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +78107,both interview and exam,female,54,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +78108,both interview and exam,male,49,NA,black,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,TRUE,17500 +78109,both interview and exam,male,16,NA,white,1,202,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +78110,both interview and exam,female,8,NA,white,1,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +78111,both interview and exam,male,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +78112,both interview and exam,female,8,NA,other,2,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +78113,both interview and exam,female,12,NA,white,1,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +78114,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,2500 +78115,both interview and exam,male,11,NA,white,2,143,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +78116,both interview and exam,female,7,NA,other hispanic,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,50000 +78117,both interview and exam,male,8,NA,other hispanic,1,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +78118,both interview and exam,female,11,NA,other hispanic,1,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +78119,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,87500 +78120,both interview and exam,male,9,NA,asian,2,119,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +78121,both interview and exam,male,22,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +78122,both interview and exam,female,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +78123,both interview and exam,male,0,8,black,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78124,both interview and exam,male,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +78125,both interview and exam,male,0,9,asian,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78126,both interview and exam,female,17,NA,mexican american,1,208,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +78127,both interview and exam,male,67,NA,asian,1,NA,TRUE,TRUE,FALSE,TRUE,45,NA,3,married,NA,TRUE,60000 +78128,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,FALSE,12500 +78129,both interview and exam,female,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,NA +78130,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,TRUE,40000 +78131,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,40000 +78132,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,17500 +78133,both interview and exam,male,0,6,other hispanic,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +78134,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +78135,interview only,male,10,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +78136,both interview and exam,male,5,NA,white,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78137,both interview and exam,female,7,NA,mexican american,2,87,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,17500 +78138,both interview and exam,male,66,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78139,both interview and exam,male,60,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +78140,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78141,both interview and exam,male,9,NA,white,2,116,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +78142,both interview and exam,female,13,NA,other hispanic,1,161,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,60000 +78143,both interview 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exam,male,0,3,white,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78153,both interview and exam,female,18,NA,black,1,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,70000 +78154,both interview and exam,female,2,NA,white,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +78155,both interview and exam,male,9,NA,white,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +78156,interview only,male,32,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +78157,both interview and exam,male,3,NA,black,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78158,both interview and exam,female,41,NA,black,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,no,TRUE,22500 +78159,both interview and exam,female,4,NA,other,2,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +78160,both interview and exam,male,9,NA,black,2,111,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,2500 +78161,both interview and exam,female,34,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,no,TRUE,17500 +78162,both interview and exam,male,3,NA,white,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +78163,both interview and exam,male,13,NA,mexican american,1,159,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,17500 +78164,both interview and exam,female,18,NA,white,1,224,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +78165,both interview and exam,female,43,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,12500 +78166,both interview and exam,male,35,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,married,NA,FALSE,17500 +78167,both interview and exam,male,76,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +78168,both interview and exam,female,19,NA,white,2,232,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,22500 +78169,both interview and exam,female,10,NA,mexican american,1,130,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,30000 +78170,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,60000 +78171,both interview and exam,female,12,NA,black,1,146,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +78172,both interview and exam,male,5,NA,mexican american,1,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78173,interview only,female,11,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +78174,both interview and exam,male,67,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,divorced,NA,FALSE,60000 +78175,both interview and exam,female,60,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,living_with_partner,NA,FALSE,NA +78176,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78177,both interview and exam,male,14,NA,mexican american,2,173,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,30000 +78178,interview only,female,14,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +78179,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78180,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +78181,interview only,male,6,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +78182,both interview and exam,male,5,NA,other,2,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78183,both interview and exam,male,63,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78184,both interview and exam,female,9,NA,white,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +78185,both interview and exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,50000 +78186,both interview and exam,female,67,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,3,married,NA,TRUE,100000 +78187,both interview and exam,female,41,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,no,FALSE,17500 +78188,both interview and exam,male,29,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +78189,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,yes,TRUE,2500 +78190,both interview and exam,male,9,NA,mexican american,1,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,60000 +78191,both interview and exam,male,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,7500 +78192,both interview and exam,male,66,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +78193,both interview and exam,male,33,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,FALSE,60000 +78194,both interview and exam,female,9,NA,mexican american,2,111,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,50000 +78195,both interview and exam,female,79,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,12500 +78196,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78197,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +78198,both interview and exam,female,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78199,both interview and exam,female,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,50000 +78200,both interview and exam,female,66,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +78201,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +78202,both interview and exam,female,5,NA,white,1,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +78203,both interview and exam,female,44,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +78204,both interview and exam,female,6,NA,other hispanic,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +78205,both interview and exam,male,10,NA,mexican american,1,125,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +78206,both interview and exam,female,13,NA,white,1,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +78207,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,7500 +78208,both interview and exam,male,52,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,12500 +78209,both interview and exam,male,13,NA,black,1,161,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +78210,both interview and exam,female,1,12,asian,1,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +78211,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +78212,both interview and exam,female,16,NA,other hispanic,2,204,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +78213,both interview and exam,male,38,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +78214,both interview and exam,male,16,NA,white,2,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +78215,both interview and exam,female,32,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,separated,no,FALSE,NA +78216,both interview and exam,male,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +78217,both interview and exam,male,66,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,widowed,NA,TRUE,100000 +78218,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,30000 +78219,both interview and exam,female,2,NA,white,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78220,both interview and exam,male,30,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,never_married,NA,TRUE,100000 +78221,both interview and exam,male,30,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,12500 +78222,both interview and exam,male,15,NA,other,1,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +78223,both interview and exam,female,23,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,unable to ascertain,TRUE,22500 +78224,both interview and exam,female,10,NA,black,2,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +78225,both interview and exam,female,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,no,FALSE,22500 +78226,both interview and exam,female,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +78227,both interview and exam,female,76,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +78228,both interview and exam,female,0,9,mexican american,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78229,both interview and exam,male,22,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +78230,both interview and exam,female,16,NA,black,1,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,70000 +78231,both interview and exam,female,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,30000 +78232,both interview and exam,female,8,NA,asian,1,106,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +78233,both interview and exam,male,18,NA,other,2,224,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +78234,both interview and exam,male,15,NA,white,2,188,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +78235,both interview and exam,male,64,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,12500 +78236,both interview and exam,male,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78237,both interview and exam,male,39,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,FALSE,30000 +78238,both interview and exam,female,80,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,1,widowed,NA,FALSE,NA +78239,both interview and exam,female,47,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78240,both interview and exam,female,15,NA,black,1,192,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +78241,both interview and exam,male,3,NA,black,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78242,both interview and exam,male,78,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78243,both interview and exam,male,4,NA,black,2,58,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,TRUE,40000 +78244,both interview and exam,male,28,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,FALSE,7500 +78245,both interview and exam,female,72,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +78246,both interview and exam,female,9,NA,white,1,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +78247,both interview and exam,female,24,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,FALSE,50000 +78248,both interview and exam,male,12,NA,black,2,146,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +78249,both interview and exam,female,4,NA,mexican american,1,55,NA,NA,FALSE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78250,both interview and exam,male,8,NA,mexican american,2,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +78251,both interview and exam,male,40,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,2,married,NA,FALSE,22500 +78252,both interview and exam,male,18,NA,other,2,218,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,17500 +78253,both interview and exam,female,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +78254,both interview and exam,female,4,NA,black,1,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78255,both interview and exam,male,17,NA,white,1,215,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +78256,both interview and exam,female,28,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,50000 +78257,both interview and exam,male,0,6,other hispanic,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78258,both interview and exam,female,6,NA,white,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +78259,interview only,female,5,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78260,both interview and exam,female,6,NA,other hispanic,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +78261,both interview and exam,female,3,NA,other,2,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78262,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +78263,both interview and exam,female,41,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,no,FALSE,30000 +78264,both interview and exam,male,5,NA,white,1,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78265,both interview and exam,male,0,8,other hispanic,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +78266,both interview and exam,male,11,NA,mexican american,1,143,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,70000 +78267,both interview and exam,male,32,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +78268,both interview and exam,female,57,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,22500 +78269,both interview and exam,male,40,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78270,both interview and exam,male,55,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,100000 +78271,both interview and exam,female,11,NA,white,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +78272,both interview and exam,female,19,NA,black,1,232,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,12500 +78273,both interview and exam,female,7,NA,white,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +78274,both interview and exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +78275,both interview and exam,female,24,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,yes,TRUE,22500 +78276,both interview and exam,male,6,NA,white,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +78277,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,22500 +78278,both interview and exam,male,6,NA,white,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +78279,both interview and exam,female,14,NA,white,2,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,17500 +78280,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +78281,both interview and exam,male,6,NA,black,1,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +78282,both interview and exam,male,32,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,87500 +78283,both interview and exam,male,12,NA,white,1,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +78284,both interview and exam,male,1,13,other,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78285,both interview and exam,male,7,NA,mexican american,1,90,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,17500 +78286,both interview and exam,male,10,NA,black,1,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,2500 +78287,both interview and exam,female,44,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,no,FALSE,30000 +78288,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +78289,both interview and exam,male,77,NA,white,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,12500 +78290,interview only,male,15,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,17500 +78291,both interview and exam,female,38,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,no,TRUE,30000 +78292,both interview and exam,female,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,60000 +78293,interview only,male,8,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +78294,both interview and exam,male,30,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,87500 +78295,both interview and exam,male,12,NA,black,1,155,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +78296,both interview and exam,male,59,NA,other hispanic,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,separated,NA,TRUE,60000 +78297,both interview and exam,female,65,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,FALSE,30000 +78298,both interview and exam,male,12,NA,white,1,152,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +78299,both interview and exam,male,38,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +78300,both interview and exam,male,0,6,black,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +78301,both interview and exam,male,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +78302,both interview and exam,female,15,NA,asian,2,192,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +78303,both interview and exam,female,3,NA,mexican american,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78304,both interview and exam,male,60,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,7500 +78305,both interview and exam,female,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,no,TRUE,70000 +78306,both interview and exam,female,63,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,55,NA,4,married,NA,TRUE,17500 +78307,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +78308,both interview and exam,female,2,NA,white,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78309,both interview and exam,female,36,NA,mexican 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exam,male,66,NA,other,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +78329,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +78330,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +78331,both interview and exam,male,7,NA,white,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +78332,both interview and exam,male,12,NA,asian,1,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +78333,both interview and exam,male,6,NA,mexican american,1,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,22500 +78334,both interview and exam,female,28,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,2500 +78335,both interview and exam,female,27,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,17500 +78336,both interview and exam,female,19,NA,white,2,231,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +78337,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +78338,both interview and exam,female,35,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +78339,both interview and exam,male,8,NA,other,2,98,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +78340,both interview and exam,male,14,NA,white,2,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,2500 +78341,both interview and exam,female,35,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,NA +78342,both interview and exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,100000 +78343,both interview and exam,female,3,NA,black,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +78344,both interview and exam,male,0,6,white,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +78345,both interview and exam,female,19,NA,other hispanic,1,229,FALSE,NA,FALSE,FALSE,3,12,NA,NA,NA,FALSE,50000 +78346,both interview and exam,male,32,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,FALSE,40000 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exam,female,45,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +78357,both interview and exam,male,9,NA,asian,1,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +78358,both interview and exam,male,9,NA,other,1,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +78359,both interview and exam,female,35,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,100000 +78360,both interview and exam,female,38,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,50000 +78361,both interview and exam,male,4,NA,mexican american,1,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +78362,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +78363,both interview and exam,male,0,3,other hispanic,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +78364,both interview and exam,male,18,NA,asian,1,222,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,12500 +78365,both interview and exam,male,9,NA,other hispanic,1,113,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 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exam,male,5,NA,white,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78385,both interview and exam,male,13,NA,mexican american,2,169,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +78386,both interview and exam,male,44,NA,asian,2,NA,TRUE,FALSE,FALSE,TRUE,25,NA,5,married,NA,TRUE,70000 +78387,both interview and exam,male,10,NA,asian,1,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +78388,both interview and exam,female,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,17500 +78389,both interview and exam,male,16,NA,asian,1,192,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,12500 +78390,both interview and exam,male,4,NA,asian,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +78391,both interview and exam,male,55,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,TRUE,87500 +78392,both interview and exam,female,67,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +78393,both interview and exam,male,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,17500 +78394,both interview and exam,female,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +78395,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,50000 +78396,both interview and exam,female,0,4,white,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +78397,both interview and exam,male,11,NA,black,2,142,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +78398,both interview and exam,male,17,NA,other hispanic,1,211,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +78399,both interview and exam,female,5,NA,asian,2,62,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78400,both interview and exam,female,49,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78401,both interview and exam,male,9,NA,black,1,112,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +78402,both interview and exam,male,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,30000 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exam,female,30,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +78440,both interview and exam,male,57,NA,white,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,4,never_married,NA,TRUE,2500 +78441,both interview and exam,male,27,NA,other,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +78442,both interview and exam,female,59,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,17500 +78443,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78444,both interview and exam,female,52,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +78445,both interview and exam,male,63,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +78446,both interview and exam,female,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,yes,TRUE,100000 +78447,both interview and exam,female,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,40000 +78448,both interview and exam,male,3,NA,other 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exam,male,15,NA,mexican american,1,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,2500 +78459,interview only,male,25,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +78460,both interview and exam,male,32,NA,black,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,TRUE,87500 +78461,both interview and exam,female,16,NA,other hispanic,2,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +78462,both interview and exam,male,58,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,17500 +78463,interview only,male,51,NA,black,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,TRUE,NA +78464,both interview and exam,female,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +78465,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,2500 +78466,both interview and exam,female,5,NA,other,2,70,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,2500 +78467,both interview and exam,female,69,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +78468,both interview and exam,female,30,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,no,TRUE,30000 +78469,both interview and exam,male,2,24,other hispanic,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78470,both interview and exam,female,12,NA,mexican american,1,155,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +78471,both interview and exam,male,6,NA,white,2,84,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +78472,both interview and exam,male,11,NA,mexican american,1,137,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +78473,both interview and exam,male,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +78474,both interview and exam,male,45,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,never_married,NA,FALSE,40000 +78475,both interview and exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +78476,both interview and exam,male,9,NA,asian,1,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +78477,both interview and exam,female,14,NA,white,2,171,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +78478,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78479,both interview and exam,male,28,NA,white,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,70000 +78480,both interview and exam,female,47,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,60000 +78481,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +78482,both interview and exam,male,5,NA,other hispanic,2,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +78483,both interview and exam,female,15,NA,mexican american,1,188,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,22500 +78484,both interview and exam,female,79,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +78485,both interview and exam,female,8,NA,white,2,102,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +78486,both interview and exam,female,60,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78487,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +78488,both interview and exam,female,0,2,other,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +78489,both interview and exam,female,31,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,no,TRUE,87500 +78490,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +78491,both interview and exam,female,11,NA,black,1,139,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +78492,both interview and exam,female,4,NA,other,2,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +78493,both interview and exam,male,11,NA,white,2,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +78494,both interview and exam,female,0,5,mexican american,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +78495,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,30000 +78496,both interview and exam,female,19,NA,mexican american,1,232,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,17500 +78497,both interview and exam,male,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +78498,both interview and exam,female,78,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +78499,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,30000 +78500,both interview and exam,male,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +78501,both interview and exam,female,19,NA,other,2,229,FALSE,NA,FALSE,FALSE,0.5,9,NA,NA,NA,TRUE,2500 +78502,both interview and exam,female,1,16,mexican american,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78503,both interview and exam,female,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,2,widowed,NA,TRUE,12500 +78504,both interview and exam,female,60,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +78505,interview only,male,0,1,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78506,both interview and exam,male,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +78507,both interview and exam,male,2,24,black,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78508,both interview and exam,male,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +78509,both interview and exam,female,13,NA,mexican american,2,162,NA,NA,FALSE,FALSE,7.5,7,NA,NA,NA,FALSE,17500 +78510,both interview and exam,male,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78511,both interview and exam,male,15,NA,black,2,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +78512,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +78513,both interview and exam,female,2,NA,white,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 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exam,female,60,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,50000 +78524,both interview and exam,female,1,17,white,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +78525,both interview and exam,male,11,NA,other hispanic,1,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +78526,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,never_married,NA,TRUE,87500 +78527,both interview and exam,female,72,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +78528,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,87500 +78529,both interview and exam,female,19,NA,other hispanic,2,234,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,NA +78530,both interview and exam,female,7,NA,black,1,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +78531,both interview and exam,male,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78532,interview only,male,28,NA,mexican 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exam,male,11,NA,asian,1,140,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,70000 +78542,both interview and exam,female,41,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,living_with_partner,no,FALSE,30000 +78543,both interview and exam,female,3,NA,white,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78544,both interview and exam,male,1,23,white,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +78545,both interview and exam,male,1,20,black,1,21,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +78546,both interview and exam,female,10,NA,mexican american,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +78547,both interview and exam,male,7,NA,white,2,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +78548,both interview and exam,female,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,NA +78549,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +78550,interview only,female,2,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78551,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +78552,both interview and exam,female,68,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,7500 +78553,both interview and exam,female,10,NA,white,2,125,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +78554,both interview and exam,male,10,NA,mexican american,2,122,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +78555,both interview and exam,male,5,NA,mexican american,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,60000 +78556,both interview and exam,female,60,NA,white,1,NA,FALSE,NA,FALSE,FALSE,55,NA,3,divorced,NA,TRUE,2500 +78557,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +78558,both interview and exam,female,5,NA,other hispanic,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +78559,both interview and exam,female,11,NA,white,1,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +78560,both interview and exam,male,22,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +78561,both interview and exam,male,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +78562,both interview and exam,male,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +78563,both interview and exam,male,9,NA,asian,2,109,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +78564,both interview and exam,male,8,NA,other hispanic,1,102,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +78565,both interview and exam,male,6,NA,black,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +78566,both interview and exam,male,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +78567,both interview and exam,female,0,3,white,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78568,both interview and exam,female,29,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,30000 +78569,both interview and exam,female,19,NA,white,2,233,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,7500 +78570,both interview and exam,male,0,4,white,1,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78571,both interview and exam,female,0,8,mexican american,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +78572,both interview and exam,male,51,NA,white,2,NA,FALSE,NA,FALSE,TRUE,45,NA,5,widowed,NA,TRUE,40000 +78573,both interview and exam,male,5,NA,mexican american,1,68,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,FALSE,12500 +78574,both interview and exam,female,10,NA,black,2,120,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +78575,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,2500 +78576,both interview and exam,female,15,NA,black,2,182,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +78577,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,NA +78578,both interview and exam,female,11,NA,mexican american,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +78579,both interview and exam,male,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +78580,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +78581,both interview and exam,female,44,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,no,TRUE,50000 +78582,both interview and exam,female,15,NA,white,2,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +78583,both interview and exam,male,54,NA,other hispanic,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +78584,both interview and exam,female,11,NA,white,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +78585,both interview and exam,male,8,NA,black,1,107,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +78586,both interview and exam,female,41,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +78587,both interview and exam,female,57,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,NA,TRUE,60000 +78588,both interview and exam,male,49,NA,other 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exam,male,2,NA,black,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +78691,both interview and exam,female,42,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,NA +78692,both interview and exam,female,39,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,no,TRUE,100000 +78693,both interview and exam,male,14,NA,black,1,177,NA,NA,FALSE,FALSE,12.5,8,NA,NA,NA,TRUE,22500 +78694,both interview and exam,female,22,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +78695,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,NA +78696,both interview and exam,male,8,NA,black,2,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +78697,both interview and exam,female,9,NA,mexican american,2,116,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,40000 +78698,both interview and exam,female,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,7500 +78699,interview 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exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +78737,both interview and exam,female,71,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,7500 +78738,both interview and exam,female,2,NA,other,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78739,both interview and exam,male,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78740,both interview and exam,male,10,NA,mexican american,2,124,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,50000 +78741,both interview and exam,male,37,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,50000 +78742,both interview and exam,male,53,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +78743,both interview and exam,female,8,NA,black,1,107,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +78744,both interview and exam,female,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78745,both interview and exam,male,2,NA,mexican 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interview and exam,male,33,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,3,married,NA,TRUE,NA +78766,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78767,both interview and exam,male,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +78768,both interview and exam,female,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +78769,both interview and exam,male,19,NA,mexican american,2,236,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +78770,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +78771,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +78772,both interview and exam,female,30,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,no,FALSE,2500 +78773,both interview and exam,female,8,NA,other,1,96,NA,NA,FALSE,TRUE,3,1,NA,NA,NA,TRUE,NA +78774,both interview and 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exam,female,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,87500 +78943,both interview and exam,male,12,NA,other hispanic,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +78944,both interview and exam,female,56,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +78945,both interview and exam,female,5,NA,black,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +78946,both interview and exam,male,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +78947,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +78948,both interview and exam,female,5,NA,black,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78949,both interview and exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +78950,both interview and exam,female,73,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,7500 +78951,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +78952,both interview and exam,female,44,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,TRUE,100000 +78953,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +78954,interview only,male,34,NA,white,NA,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,TRUE,17500 +78955,both interview and exam,female,6,NA,mexican american,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,7500 +78956,both interview and exam,female,1,18,white,2,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +78957,both interview and exam,male,19,NA,black,2,238,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,12500 +78958,both interview and exam,female,14,NA,other hispanic,2,178,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +78959,both interview and exam,female,39,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,no,TRUE,100000 +78960,both interview and exam,female,3,NA,black,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 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exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78971,both interview and exam,female,10,NA,black,1,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +78972,both interview and exam,female,4,NA,white,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +78973,both interview and exam,female,27,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,30000 +78974,both interview and exam,male,54,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +78975,both interview and exam,male,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,2500 +78976,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +78977,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,40000 +78978,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +78979,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78980,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,22500 +78981,both interview and exam,female,71,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,55,NA,1,widowed,NA,TRUE,12500 +78982,both interview and exam,female,9,NA,mexican american,2,108,NA,NA,FALSE,FALSE,3,2,NA,NA,NA,FALSE,50000 +78983,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78984,both interview and exam,male,17,NA,white,2,215,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,7500 +78985,both interview and exam,female,5,NA,white,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78986,interview only,female,19,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,12500 +78987,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,NA +78988,both interview and exam,male,2,NA,other,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 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exam,male,8,NA,white,2,98,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +78999,both interview and exam,male,23,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,70000 +79000,both interview and exam,male,36,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,50000 +79001,both interview and exam,male,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,7500 +79002,both interview and exam,female,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,50000 +79003,both interview and exam,female,7,NA,mexican american,2,85,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +79004,both interview and exam,male,2,NA,black,1,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +79005,both interview and exam,male,44,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +79006,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,FALSE,TRUE,55,NA,3,married,NA,TRUE,100000 +79007,both interview and exam,female,52,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +79008,both interview and exam,female,11,NA,white,1,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +79009,both interview and exam,male,10,NA,mexican american,1,132,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,22500 +79010,both interview and exam,male,5,NA,white,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79011,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,widowed,NA,TRUE,30000 +79012,interview only,female,50,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +79013,both interview and exam,male,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,2500 +79014,both interview and exam,female,54,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +79015,both interview and exam,male,64,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +79016,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +79017,both interview and exam,male,61,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,30000 +79018,both interview and exam,female,18,NA,white,2,221,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +79019,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +79020,both interview and exam,male,0,7,white,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +79021,both interview and exam,female,7,NA,black,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +79022,both interview and exam,male,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,2500 +79023,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +79024,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +79025,both interview and exam,female,54,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +79026,both interview and exam,male,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +79027,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +79028,both interview and exam,male,12,NA,mexican american,1,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,30000 +79029,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +79030,both interview and exam,male,4,NA,mexican american,2,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +79031,both interview and exam,male,68,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +79032,both interview and exam,male,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +79033,both interview and exam,male,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,100000 +79034,interview 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exam,female,14,NA,white,1,170,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +79044,both interview and exam,male,31,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,50000 +79045,both interview and exam,female,11,NA,mexican american,1,134,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,NA +79046,both interview and exam,female,0,1,asian,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79047,both interview and exam,female,13,NA,white,1,169,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +79048,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +79049,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,50000 +79050,both interview and exam,female,74,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,3,married,NA,TRUE,87500 +79051,both interview and exam,female,14,NA,other,2,174,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +79052,both interview and exam,male,4,NA,white,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 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exam,male,9,NA,white,1,109,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,70000 +79118,both interview and exam,male,8,NA,black,1,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +79119,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +79120,both interview and exam,male,11,NA,white,2,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +79121,both interview and exam,female,62,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,30000 +79122,both interview and exam,female,9,NA,other hispanic,1,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +79123,both interview and exam,male,4,NA,mexican american,2,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +79124,both interview and exam,female,3,NA,mexican american,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +79125,both interview and exam,female,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +79126,interview only,male,3,NA,other hispanic,NA,NA,NA,NA,NA,TRUE,NA,NA,NA,NA,NA,TRUE,NA 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interview and exam,female,26,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,no,TRUE,30000 +79147,both interview and exam,female,38,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,no,TRUE,30000 +79148,both interview and exam,male,33,NA,mexican american,1,NA,FALSE,NA,FALSE,NA,7.5,NA,2,living_with_partner,NA,FALSE,22500 +79149,both interview and exam,female,6,NA,asian,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +79150,both interview and exam,male,10,NA,mexican american,2,130,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +79151,interview only,female,37,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,12500 +79152,both interview and exam,male,53,NA,white,2,NA,TRUE,FALSE,FALSE,TRUE,55,NA,5,married,NA,TRUE,30000 +79153,both interview and exam,female,29,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +79154,both interview and exam,male,71,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,100000 +79155,both interview and exam,female,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +79156,interview only,female,8,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +79157,both interview and exam,male,4,NA,black,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +79158,interview only,male,4,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +79159,interview only,male,62,NA,other hispanic,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,NA,FALSE,22500 +79160,both interview and exam,female,14,NA,white,2,178,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +79161,both interview and exam,female,55,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,NA,FALSE,30000 +79162,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +79163,both interview and exam,male,19,NA,white,2,239,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,2500 +79164,both interview and exam,male,33,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 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exam,female,1,20,asian,2,21,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79175,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +79176,both interview and exam,male,55,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +79177,both interview and exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +79178,both interview and exam,male,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,never_married,NA,TRUE,100000 +79179,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +79180,both interview and exam,female,69,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,widowed,NA,FALSE,50000 +79181,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,separated,no,TRUE,7500 +79182,both interview and exam,male,12,NA,other,1,154,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +79183,both interview and exam,female,4,NA,white,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +79184,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +79185,both interview and exam,male,79,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,22500 +79186,both interview and exam,female,80,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,30000 +79187,both interview and exam,female,52,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +79188,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,NA +79189,both interview and exam,male,74,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +79190,both interview and exam,male,41,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,100000 +79191,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +79192,both interview and exam,female,1,13,mexican 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exam,male,75,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +79202,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +79203,both interview and exam,female,4,NA,asian,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79204,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +79205,both interview and exam,male,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +79206,both interview and exam,male,72,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +79207,both interview and exam,female,25,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +79208,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +79209,both interview and exam,male,6,NA,white,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +79210,both interview and exam,male,25,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +79211,both interview and exam,female,39,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,never_married,no,TRUE,12500 +79212,both interview and exam,female,0,2,other hispanic,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +79213,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,40000 +79214,both interview and exam,female,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +79215,both interview and exam,female,28,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,living_with_partner,yes,TRUE,50000 +79216,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,100000 +79217,both interview and exam,male,33,NA,black,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,4,married,NA,TRUE,100000 +79218,both interview and exam,male,14,NA,black,1,170,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +79219,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +79220,both interview and exam,male,55,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,30000 +79221,both interview and exam,male,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +79222,both interview and exam,female,9,NA,other hispanic,2,117,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,22500 +79223,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,60000 +79224,both interview and exam,female,19,NA,asian,1,237,FALSE,NA,FALSE,TRUE,7.5,13,NA,NA,NA,TRUE,2500 +79225,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,12500 +79226,both interview and exam,male,24,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,87500 +79227,both interview and exam,female,8,NA,asian,2,107,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +79228,both interview and 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exam,female,19,NA,white,1,229,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,NA +79405,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +79406,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +79407,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,2500 +79408,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +79409,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +79410,both interview and exam,male,6,NA,black,1,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +79411,interview only,male,64,NA,mexican american,NA,NA,FALSE,NA,FALSE,TRUE,17.5,NA,1,married,NA,FALSE,12500 +79412,both interview and exam,male,12,NA,black,1,150,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,22500 +79413,both interview and exam,male,0,0,mexican 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interview and exam,female,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +79424,both interview and exam,female,17,NA,black,2,211,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +79425,both interview and exam,male,53,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,NA,TRUE,87500 +79426,both interview and exam,female,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,NA +79427,both interview and exam,male,6,NA,mexican american,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,60000 +79428,both interview and exam,male,6,NA,other hispanic,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,2500 +79429,both interview and exam,female,18,NA,black,2,220,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +79430,both interview and exam,male,18,NA,black,1,222,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +79431,both interview and exam,male,56,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,FALSE,30000 +79432,both interview and 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exam,female,67,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +79442,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +79443,both interview and exam,male,44,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +79444,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,50000 +79445,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +79446,both interview and exam,male,47,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,3,divorced,NA,TRUE,17500 +79447,both interview and exam,female,11,NA,other,1,134,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +79448,both interview and exam,male,1,13,other hispanic,2,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79449,both interview and exam,female,37,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,40000 +79450,both interview and exam,female,5,NA,black,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +79451,both interview and exam,female,47,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +79452,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,22500 +79453,both interview and exam,male,54,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +79454,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +79455,both interview and exam,female,37,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,3,NA,4,married,no,FALSE,NA +79456,both interview and exam,male,18,NA,mexican american,1,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,12500 +79457,both interview and exam,male,68,NA,white,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,living_with_partner,NA,TRUE,70000 +79458,both interview and exam,female,10,NA,mexican american,2,126,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,50000 +79459,both interview and 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exam,male,52,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,7500 +79469,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +79470,both interview and exam,female,14,NA,asian,1,169,NA,NA,FALSE,FALSE,7.5,7,NA,NA,NA,TRUE,7500 +79471,both interview and exam,male,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +79472,both interview and exam,male,5,NA,mexican american,1,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +79473,both interview and exam,female,27,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,22500 +79474,both interview and exam,female,50,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,22500 +79475,both interview and exam,male,3,NA,asian,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +79476,both interview and exam,female,66,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +79477,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +79478,both interview and exam,female,4,NA,white,2,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +79479,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +79480,both interview and exam,female,38,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +79481,both interview and exam,male,72,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +79482,both interview and exam,female,55,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,40000 +79483,both interview and exam,female,4,NA,white,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +79484,both interview and exam,male,54,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,87500 +79485,both interview and exam,male,3,NA,white,1,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +79486,both interview and exam,female,72,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +79487,both interview and exam,female,42,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,married,no,FALSE,22500 +79488,both interview and exam,male,42,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,40000 +79489,both interview and exam,female,8,NA,white,1,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +79490,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,2500 +79491,both interview and exam,female,34,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,no,TRUE,100000 +79492,both interview and exam,male,13,NA,other hispanic,1,162,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +79493,both interview and exam,female,16,NA,mexican american,2,201,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,30000 +79494,both interview and exam,male,80,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,100000 +79495,both interview and exam,male,4,NA,black,2,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +79496,both interview and exam,male,54,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,FALSE,NA +79497,both interview and exam,female,6,NA,mexican american,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +79498,both interview and exam,female,4,NA,black,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +79499,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +79500,both interview and exam,female,6,NA,white,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +79501,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,87500 +79502,both interview and exam,male,18,NA,white,1,227,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +79503,both interview and exam,female,68,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,87500 +79504,both interview and exam,male,14,NA,black,1,176,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 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exam,male,13,NA,black,2,157,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +79525,both interview and exam,male,64,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,30000 +79526,both interview and exam,male,27,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,60000 +79527,interview only,female,15,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,30000 +79528,both interview and exam,female,1,20,other,1,21,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +79529,both interview and exam,male,8,NA,white,2,105,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +79530,both interview and exam,female,13,NA,asian,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +79531,both interview and exam,male,10,NA,mexican american,1,124,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,7500 +79532,both interview and exam,male,9,NA,black,2,111,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +79533,both interview and exam,male,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +79534,both 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interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,50000 +79545,both interview and exam,female,33,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,never_married,no,FALSE,17500 +79546,both interview and exam,female,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +79547,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,7500 +79548,interview only,female,62,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +79549,both interview and exam,female,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,50000 +79550,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,yes,TRUE,2500 +79551,both interview and exam,female,1,22,white,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79552,both interview and exam,female,5,NA,mexican american,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +79553,both interview and 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exam,male,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80016,both interview and exam,male,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,living_with_partner,NA,FALSE,22500 +80017,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +80018,both interview and exam,male,10,NA,other,2,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +80019,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,22500 +80020,both interview and exam,female,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,50000 +80021,both interview and exam,female,16,NA,other,1,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,NA +80022,both interview and exam,male,21,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +80023,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80024,both interview and exam,female,48,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,2,married,NA,TRUE,40000 +80025,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,no,TRUE,22500 +80026,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +80027,both interview and exam,female,32,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,never_married,no,FALSE,70000 +80028,interview only,female,54,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80029,both interview and exam,male,7,NA,white,1,89,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +80030,both interview and exam,male,63,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,35,NA,5,married,NA,TRUE,100000 +80031,both interview and exam,male,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +80032,both interview and exam,male,11,NA,other hispanic,1,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80033,both interview and exam,male,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +80034,both interview and exam,female,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,no,TRUE,40000 +80035,both interview and exam,male,4,NA,white,2,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80036,both interview and exam,female,16,NA,other hispanic,1,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +80037,both interview and exam,male,64,NA,mexican american,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +80038,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,NA +80039,both interview and exam,male,3,NA,asian,2,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80040,both interview and exam,female,70,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,7500 +80041,both interview and exam,female,42,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,TRUE,22500 +80042,both interview and exam,female,10,NA,white,2,121,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,NA +80043,both interview and exam,female,38,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +80044,both interview and exam,male,77,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +80045,both interview and exam,male,3,NA,black,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80046,both interview and exam,female,1,13,mexican american,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +80047,both interview and exam,female,22,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +80048,both interview and exam,male,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +80049,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80050,both interview and exam,male,8,NA,white,1,104,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +80051,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +80052,both interview and exam,female,62,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,never_married,NA,FALSE,NA +80053,both interview and exam,male,16,NA,black,2,198,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +80054,both interview and exam,male,13,NA,other hispanic,1,161,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +80055,both interview and exam,female,44,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,no,FALSE,50000 +80056,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,70000 +80057,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +80058,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,17500 +80059,both interview and exam,female,47,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,22500 +80060,both interview and exam,female,42,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +80061,both interview and exam,female,50,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +80062,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +80063,both interview and exam,male,80,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +80064,both interview and exam,male,32,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,22500 +80065,both interview and exam,male,2,NA,mexican american,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80066,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,87500 +80067,both interview and exam,male,65,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,NA,FALSE,2500 +80068,both interview and exam,female,9,NA,asian,1,120,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +80069,both interview and exam,male,10,NA,black,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +80070,both interview and exam,female,1,17,white,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80071,interview only,female,66,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +80072,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,22500 +80073,both interview and exam,female,57,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,50000 +80074,both interview and exam,female,10,NA,mexican american,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,40000 +80075,both interview and exam,male,32,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +80076,both interview and exam,female,2,NA,other hispanic,1,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +80077,both interview and exam,female,12,NA,white,1,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80078,both interview and exam,male,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,1,widowed,NA,TRUE,12500 +80079,both interview and exam,male,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +80080,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80081,both interview and exam,female,1,17,mexican american,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80082,both interview and exam,female,79,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,50000 +80083,both interview and exam,male,41,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,30000 +80084,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +80085,both interview and exam,male,7,NA,black,2,95,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +80086,both interview and exam,female,0,1,other hispanic,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80087,both interview and exam,female,30,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,100000 +80088,both interview and exam,male,22,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,never_married,NA,TRUE,12500 +80089,both interview and exam,female,51,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,2,never_married,NA,TRUE,12500 +80090,both interview and exam,female,0,8,white,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80091,both interview and exam,male,65,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +80092,both interview and exam,female,65,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80093,both interview and exam,female,8,NA,asian,2,104,NA,NA,FALSE,FALSE,3,2,NA,NA,NA,TRUE,100000 +80094,both interview and exam,female,69,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,60000 +80095,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +80096,both interview and exam,female,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,NA +80097,both interview and exam,male,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80098,both interview and exam,male,15,NA,mexican american,2,185,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +80099,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,70000 +80100,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +80101,both interview and exam,male,29,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,70000 +80102,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,separated,NA,TRUE,40000 +80103,both interview and exam,male,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,87500 +80104,both interview and exam,male,11,NA,mexican american,1,138,NA,NA,FALSE,FALSE,NA,3,NA,NA,NA,FALSE,30000 +80105,both interview and exam,male,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,30000 +80106,both interview and exam,female,19,NA,mexican american,1,238,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +80107,both interview and exam,female,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +80108,both interview and exam,female,4,NA,other hispanic,2,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +80109,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,yes,TRUE,87500 +80110,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +80111,both interview and exam,female,18,NA,black,2,228,FALSE,NA,FALSE,TRUE,12.5,13,NA,NA,NA,TRUE,NA +80112,both interview and exam,male,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +80113,both interview and exam,male,1,16,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80114,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +80115,both interview and exam,male,80,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +80116,interview only,female,61,NA,black,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,separated,NA,TRUE,2500 +80117,both interview and exam,male,0,0,black,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80118,both interview and exam,female,8,NA,white,2,102,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +80119,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,70000 +80120,both interview and exam,female,65,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +80121,both interview and exam,male,68,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,TRUE,NA +80122,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +80123,both interview and exam,male,71,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +80124,both interview and exam,male,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +80125,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,unable to ascertain,TRUE,22500 +80126,both interview and exam,male,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +80127,both interview and exam,male,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80128,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,22500 +80129,both interview and exam,male,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +80130,both interview and exam,male,51,NA,other,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,NA,TRUE,100000 +80131,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,7500 +80132,both interview and exam,male,37,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,never_married,NA,TRUE,NA +80133,both interview and exam,male,80,NA,black,2,NA,TRUE,FALSE,FALSE,TRUE,55,NA,5,married,NA,TRUE,100000 +80134,both interview and exam,female,18,NA,mexican american,2,223,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,30000 +80135,interview only,female,22,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,NA,never_married,unable to ascertain,TRUE,NA +80136,both interview and exam,male,65,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,FALSE,22500 +80137,both interview and exam,male,30,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,married,NA,TRUE,40000 +80138,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +80139,both interview and exam,female,39,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,divorced,no,TRUE,50000 +80140,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +80141,both interview and exam,male,16,NA,black,1,204,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +80142,both interview and exam,male,3,NA,white,1,38,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,100000 +80143,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,never_married,NA,TRUE,NA +80144,both interview and exam,male,50,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +80145,both interview and exam,male,22,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,FALSE,7500 +80146,both interview and exam,male,33,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,FALSE,7500 +80147,both interview and exam,female,0,4,white,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80148,both interview and exam,male,80,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,7500 +80149,both interview and exam,female,20,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,NA +80150,both interview and exam,female,12,NA,other hispanic,2,151,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,22500 +80151,both interview and exam,male,6,NA,white,2,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +80152,both interview and exam,male,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +80153,both interview and exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80154,both interview and exam,female,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +80155,both interview and exam,male,52,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,FALSE,NA +80156,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +80157,interview only,female,42,NA,mexican american,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,unable to ascertain,FALSE,22500 +80158,both interview and exam,male,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +80159,both interview and exam,male,7,NA,black,2,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,2500 +80160,both interview and exam,female,13,NA,white,1,161,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +80161,both interview and exam,female,10,NA,other hispanic,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,50000 +80162,both interview and exam,female,17,NA,white,2,211,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,60000 +80163,both interview and exam,female,63,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +80164,both interview and exam,male,19,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,12500 +80165,both interview and exam,female,65,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,60000 +80166,both interview and exam,male,17,NA,other hispanic,1,210,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +80167,both interview and exam,female,9,NA,white,1,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +80168,both interview and exam,male,38,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +80169,both interview and exam,female,42,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,no,FALSE,NA +80170,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +80171,both interview and exam,female,8,NA,black,2,106,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +80172,both interview and exam,female,2,NA,other hispanic,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +80173,both interview and exam,female,15,NA,white,2,188,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +80174,both interview and exam,female,61,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,FALSE,40000 +80175,both interview and exam,male,64,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +80176,both interview and exam,female,15,NA,white,2,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +80177,both interview and exam,male,2,NA,white,1,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80178,both interview and exam,male,35,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,70000 +80179,both interview and exam,female,75,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +80180,both interview and exam,male,9,NA,other,1,117,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +80181,both interview and exam,female,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,30000 +80182,both interview and exam,female,14,NA,asian,1,171,NA,NA,FALSE,FALSE,0.5,7,NA,NA,NA,TRUE,2500 +80183,both interview and exam,male,75,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +80184,both interview and exam,male,13,NA,other hispanic,2,166,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +80185,both interview and exam,male,61,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,2,married,NA,TRUE,30000 +80186,both interview and exam,female,10,NA,black,2,131,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80187,both interview and exam,male,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +80188,both interview and exam,male,55,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,50000 +80189,both interview and exam,male,18,NA,other,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +80190,both interview and exam,female,33,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +80191,both interview and exam,male,6,NA,other,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,50000 +80192,both interview and exam,male,0,6,black,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80193,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,60000 +80194,both interview and exam,female,18,NA,mexican american,1,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +80195,both interview and exam,male,1,13,mexican american,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +80196,both interview and exam,male,13,NA,mexican american,2,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,70000 +80197,both interview and exam,male,44,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,living_with_partner,NA,FALSE,30000 +80198,both interview and exam,female,7,NA,white,1,91,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +80199,both interview and exam,female,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,50000 +80200,both interview and exam,male,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +80201,both interview and exam,female,63,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,divorced,NA,TRUE,30000 +80202,both interview and exam,male,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +80203,both interview and exam,male,67,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,NA +80204,both interview and exam,male,59,NA,white,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,TRUE,40000 +80205,both interview and exam,male,75,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +80206,both interview and exam,female,63,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,2,married,NA,FALSE,12500 +80207,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +80208,interview only,male,1,20,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80209,both interview and exam,male,0,3,black,2,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80210,both interview and exam,male,37,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,FALSE,87500 +80211,both interview and exam,female,7,NA,mexican american,1,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +80212,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +80213,both interview and exam,female,0,5,mexican american,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80214,both interview and exam,male,46,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +80215,both interview and exam,male,22,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +80216,both interview and exam,female,8,NA,white,2,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +80217,both interview and exam,female,28,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +80218,both interview and exam,female,72,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,NA +80219,both interview and exam,female,5,NA,other hispanic,1,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80220,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,100000 +80221,interview only,male,33,NA,mexican american,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,living_with_partner,NA,FALSE,30000 +80222,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +80223,both interview and exam,female,11,NA,other,1,136,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +80224,both interview and exam,female,0,6,other hispanic,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80225,both interview and exam,female,40,NA,mexican 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exam,female,12,NA,white,2,152,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +80244,both interview and exam,female,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,yes,TRUE,100000 +80245,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +80246,both interview and exam,male,4,NA,white,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80247,both interview and exam,female,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,17500 +80248,both interview and exam,female,29,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +80249,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +80250,both interview and exam,male,72,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +80251,both interview and exam,female,27,NA,black,2,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,no,TRUE,40000 +80252,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +80253,both interview and exam,male,8,NA,asian,2,104,NA,NA,FALSE,FALSE,7.5,2,NA,NA,NA,TRUE,87500 +80254,both interview and exam,female,31,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,unable to ascertain,TRUE,60000 +80255,interview only,female,3,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80256,both interview and exam,male,2,NA,other hispanic,1,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +80257,both interview and exam,female,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +80258,both interview and exam,male,19,NA,black,2,229,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +80259,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,40000 +80260,both interview and exam,male,40,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,TRUE,87500 +80261,both interview and exam,female,38,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,100000 +80262,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +80263,both interview and exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +80264,both interview and exam,female,21,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,NA +80265,both interview and exam,female,35,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,100000 +80266,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +80267,both interview and exam,male,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +80268,both interview and exam,male,71,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,60000 +80269,both interview and exam,male,25,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,never_married,NA,TRUE,40000 +80270,interview only,male,37,NA,mexican 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exam,male,38,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80280,both interview and exam,female,31,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,living_with_partner,no,FALSE,100000 +80281,both interview and exam,female,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +80282,both interview and exam,female,5,NA,mexican american,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +80283,both interview and exam,female,13,NA,other hispanic,1,162,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,2500 +80284,both interview and exam,male,11,NA,black,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80285,both interview and exam,male,50,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +80286,both interview and exam,male,38,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,40000 +80287,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,60000 +80288,both interview and exam,male,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,17500 +80289,both interview and exam,female,37,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,no,TRUE,12500 +80290,both interview and exam,male,1,13,black,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80291,both interview and exam,male,31,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +80292,both interview and exam,female,69,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +80293,both interview and exam,female,11,NA,black,2,142,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +80294,both interview and exam,female,75,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +80295,both interview and exam,female,38,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,no,TRUE,87500 +80296,both interview and exam,female,64,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,22500 +80297,both interview and exam,female,16,NA,mexican american,2,194,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +80298,both interview and exam,female,4,NA,other hispanic,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80299,both interview and exam,male,15,NA,black,1,181,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +80300,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +80301,both interview and exam,male,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +80302,both interview and exam,female,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,unable to ascertain,TRUE,12500 +80303,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +80304,both interview and exam,male,43,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,30000 +80305,both interview and exam,female,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +80306,both interview and exam,female,4,NA,mexican american,2,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80307,both interview and exam,female,75,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +80308,both interview and exam,male,39,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,TRUE,60000 +80309,both interview and exam,female,44,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,no,FALSE,NA +80310,both interview and exam,male,18,NA,black,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +80311,both interview and exam,female,11,NA,black,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +80312,both interview and exam,male,40,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +80313,both interview and exam,female,2,NA,white,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80314,both interview and exam,female,10,NA,black,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +80315,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +80316,both interview and exam,female,11,NA,black,2,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,NA +80317,both interview and exam,female,14,NA,white,1,177,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +80318,both interview and exam,female,2,NA,black,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +80319,both interview and exam,female,8,NA,mexican american,1,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +80320,both interview and exam,female,9,NA,black,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +80321,both interview and exam,male,72,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +80322,both interview and exam,female,55,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,TRUE,70000 +80323,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,2500 +80324,both interview and exam,female,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +80325,both interview and exam,female,19,NA,mexican 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exam,female,14,NA,white,2,173,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +80335,both interview and exam,male,28,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,30000 +80336,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +80337,both interview and exam,female,14,NA,asian,2,180,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +80338,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,30000 +80339,both interview and exam,female,37,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,living_with_partner,no,FALSE,17500 +80340,both interview and exam,male,61,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +80341,both interview and exam,female,8,NA,white,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,70000 +80342,both interview and exam,female,2,NA,black,1,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80343,both interview and exam,female,24,NA,other 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exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,40000 +80353,both interview and exam,female,9,NA,mexican american,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +80354,both interview and exam,female,12,NA,asian,2,151,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +80355,both interview and exam,female,70,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,separated,NA,FALSE,12500 +80356,both interview and exam,male,12,NA,black,1,145,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +80357,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,12500 +80358,both interview and exam,male,4,NA,black,1,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80359,both interview and exam,male,4,NA,other hispanic,2,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +80360,both interview and exam,female,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80361,both interview and 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exam,male,0,10,black,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80371,both interview and exam,female,39,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,no,TRUE,40000 +80372,both interview and exam,male,42,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80373,both interview and exam,female,1,16,mexican american,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80374,both interview and exam,female,0,5,black,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +80375,both interview and exam,male,47,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,100000 +80376,both interview and exam,female,3,NA,white,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +80377,both interview and exam,male,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +80378,both interview and exam,female,3,NA,mexican american,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80379,both interview and exam,male,67,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,30000 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exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,12500 +80390,both interview and exam,female,65,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +80391,both interview and exam,male,23,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,never_married,NA,FALSE,22500 +80392,both interview and exam,female,16,NA,white,1,195,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +80393,both interview and exam,male,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +80394,both interview and exam,male,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,87500 +80395,both interview and exam,male,9,NA,mexican american,1,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +80396,both interview and exam,male,31,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +80397,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,NA +80398,both interview and 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interview and exam,female,43,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,widowed,no,TRUE,40000 +80409,both interview and exam,female,5,NA,white,1,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80410,both interview and exam,male,47,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,NA,TRUE,NA +80411,both interview and exam,male,41,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,living_with_partner,NA,FALSE,22500 +80412,both interview and exam,male,3,NA,white,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80413,both interview and exam,male,46,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +80414,both interview and exam,male,24,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,never_married,NA,FALSE,40000 +80415,both interview and exam,male,6,NA,white,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +80416,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +80417,both interview and exam,female,60,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,TRUE,22500 +80418,both interview and exam,male,2,NA,other hispanic,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +80419,both interview and exam,female,12,NA,black,1,152,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +80420,both interview and exam,female,6,NA,black,2,73,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +80421,both interview and exam,female,13,NA,white,2,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +80422,both interview and exam,female,0,1,white,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80423,both interview and exam,male,8,NA,white,1,104,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +80424,both interview and exam,female,14,NA,other hispanic,1,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +80425,both interview and exam,male,19,NA,mexican american,2,231,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,22500 +80426,both interview and exam,female,0,9,mexican american,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 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exam,female,55,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +80483,interview only,female,56,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,12500 +80484,both interview and exam,male,13,NA,mexican american,1,168,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +80485,both interview and exam,male,0,9,other,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80486,both interview and exam,female,69,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80487,both interview and exam,female,6,NA,mexican american,2,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +80488,interview only,male,7,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +80489,both interview and exam,female,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,60000 +80490,both interview and exam,female,33,NA,black,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,never_married,no,TRUE,40000 +80491,both interview and 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interview and exam,male,51,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,FALSE,17500 +80557,both interview and exam,female,0,9,mexican american,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,40000 +80558,both interview and exam,female,9,NA,mexican american,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,70000 +80559,both interview and exam,male,26,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +80560,both interview and exam,male,25,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +80561,both interview and exam,male,41,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,100000 +80562,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,60000 +80563,both interview and exam,female,12,NA,white,1,151,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +80564,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80565,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +80566,both interview and exam,female,6,NA,mexican american,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +80567,interview only,male,12,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +80568,both interview and exam,female,2,24,white,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80569,both interview and exam,female,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,100000 +80570,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80571,both interview and exam,male,9,NA,asian,1,112,NA,NA,FALSE,TRUE,7.5,2,NA,NA,NA,TRUE,50000 +80572,interview only,female,8,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,7500 +80573,both interview and exam,female,63,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,married,NA,TRUE,100000 +80574,both interview and exam,female,12,NA,other hispanic,1,147,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,NA +80575,both 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exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80595,both interview and exam,female,66,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +80596,both interview and exam,male,32,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +80597,both interview and exam,female,5,NA,white,1,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80598,both interview and exam,female,7,NA,black,1,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +80599,both interview and exam,male,77,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +80600,both interview and exam,female,3,NA,black,1,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80601,both interview and exam,female,71,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +80602,both interview and exam,female,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +80603,both interview and exam,female,31,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,yes,TRUE,50000 +80604,both interview and exam,male,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +80605,both interview and exam,male,14,NA,black,2,170,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +80606,both interview and exam,male,0,5,mexican american,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80607,both interview and exam,male,16,NA,mexican american,2,201,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +80608,both interview and exam,male,11,NA,white,2,139,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +80609,both interview and exam,male,0,11,white,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80610,both interview and exam,female,0,9,asian,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80611,both interview and exam,female,42,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,no,TRUE,100000 +80612,both interview and exam,female,1,13,white,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80613,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +80614,both interview and exam,female,4,NA,white,2,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80615,both interview and exam,male,1,18,other hispanic,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80616,both interview and exam,female,14,NA,mexican american,2,178,NA,NA,FALSE,TRUE,7.5,8,NA,NA,NA,FALSE,87500 +80617,interview only,male,29,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,12500 +80618,both interview and exam,male,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +80619,both interview and exam,male,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +80620,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +80621,both interview and exam,female,5,NA,black,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80622,both interview and exam,female,45,NA,mexican 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exam,male,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +80633,both interview and exam,female,30,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,7500 +80634,both interview and exam,female,46,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,5,married,NA,TRUE,NA +80635,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +80636,both interview and exam,female,49,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,17500 +80637,both interview and exam,female,36,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,unable to ascertain,TRUE,87500 +80638,both interview and exam,female,1,18,mexican american,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +80639,both interview and exam,male,32,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +80640,both interview and exam,male,8,NA,white,2,100,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +80641,both interview and 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exam,female,11,NA,white,1,137,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +80825,both interview and exam,male,30,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +80826,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +80827,both interview and exam,male,6,NA,other hispanic,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +80828,both interview and exam,male,13,NA,black,1,168,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +80829,both interview and exam,male,11,NA,white,2,133,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +80830,both interview and exam,female,9,NA,black,1,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,50000 +80831,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,30000 +80832,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +80833,both interview and exam,male,33,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +80834,both interview and exam,female,4,NA,asian,2,51,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,TRUE,22500 +80835,both interview and exam,male,3,NA,black,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80836,both interview and exam,male,64,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80837,both interview and exam,male,55,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +80838,both interview and exam,male,8,NA,black,1,98,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +80839,both interview and exam,female,1,12,other hispanic,2,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80840,both interview and exam,female,44,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,no,TRUE,NA +80841,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +80842,both interview and exam,female,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +80843,both interview and exam,female,77,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,50000 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american,1,222,FALSE,NA,FALSE,FALSE,17.5,12,NA,NA,NA,TRUE,40000 +80854,both interview and exam,female,27,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +80855,both interview and exam,female,12,NA,other hispanic,1,155,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +80856,both interview and exam,female,11,NA,mexican american,1,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,30000 +80857,both interview and exam,male,17,NA,white,2,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +80858,both interview and exam,male,65,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80859,both interview and exam,female,75,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +80860,both interview and exam,female,9,NA,black,1,117,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +80861,both interview and exam,female,0,11,mexican american,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +80862,both interview and exam,male,21,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,never_married,NA,TRUE,100000 +80863,both interview and exam,female,37,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,no,TRUE,100000 +80864,both interview and exam,male,54,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,7500 +80865,both interview and exam,female,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,7500 +80866,both interview and exam,male,0,1,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80867,both interview and exam,female,6,NA,mexican american,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,50000 +80868,both interview and exam,female,61,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,3,widowed,NA,FALSE,100000 +80869,both interview and exam,male,18,NA,white,1,221,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +80870,both interview and exam,male,10,NA,other hispanic,2,128,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,12500 +80871,both interview and exam,female,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +80872,both interview and exam,male,66,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,TRUE,NA +80873,both interview and exam,female,36,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,no,TRUE,100000 +80874,interview only,female,74,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +80875,both interview and exam,female,0,5,mexican american,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80876,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,70000 +80877,both interview and exam,male,8,NA,black,1,106,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +80878,both interview and exam,female,65,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +80879,both interview and exam,female,48,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +80880,both interview and exam,male,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,40000 +80881,both interview and exam,female,30,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,NA +80882,both interview and exam,male,18,NA,black,2,220,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,50000 +80883,both interview and exam,male,18,NA,mexican american,2,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,22500 +80884,both interview and exam,male,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,17500 +80885,both interview and exam,male,32,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +80886,both interview and exam,male,4,NA,other,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80887,interview only,male,2,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80888,both interview and exam,female,4,NA,other,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80889,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80890,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +80891,both interview and exam,female,1,14,white,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80892,both interview and exam,female,59,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +80893,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +80894,both interview and exam,female,67,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +80895,both interview and exam,male,14,NA,asian,1,180,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +80896,both interview and exam,female,9,NA,mexican american,2,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +80897,both interview and exam,male,7,NA,black,1,89,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,2500 +80898,both interview and exam,male,76,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,7500 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exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +80909,both interview and exam,female,12,NA,mexican american,1,151,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,40000 +80910,both interview and exam,male,14,NA,black,1,169,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +80911,both interview and exam,male,44,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80912,both interview and exam,female,28,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,no,FALSE,87500 +80913,both interview and exam,male,1,15,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80914,both interview and exam,female,2,NA,other,2,34,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,2500 +80915,both interview and exam,female,66,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +80916,both interview and exam,female,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,100000 +80917,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +80918,both interview and exam,female,3,NA,black,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80919,both interview and exam,male,6,NA,asian,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +80920,both interview and exam,female,28,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,living_with_partner,unable to ascertain,FALSE,30000 +80921,both interview and exam,female,25,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,living_with_partner,no,FALSE,87500 +80922,both interview and exam,male,14,NA,mexican american,2,177,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,17500 +80923,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +80924,both interview and exam,female,39,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,NA +80925,both interview and exam,male,3,NA,black,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80926,both interview and exam,female,1,21,other hispanic,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80927,both interview and exam,male,4,NA,other,2,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80928,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,70000 +80929,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +80930,both interview and exam,male,73,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,100000 +80931,both interview and exam,female,11,NA,other,2,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80932,both interview and exam,male,39,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +80933,both interview and exam,male,11,NA,other hispanic,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +80934,both interview and exam,male,65,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,TRUE,22500 +80935,both interview and exam,female,0,1,white,1,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80936,both interview 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interview and exam,male,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +80947,both interview and exam,male,12,NA,white,1,156,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +80948,both interview and exam,male,18,NA,black,1,219,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +80949,both interview and exam,female,7,NA,mexican american,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +80950,both interview and exam,male,0,4,other hispanic,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80951,both interview and exam,female,5,NA,white,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +80952,both interview and exam,female,1,15,other hispanic,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,70000 +80953,both interview and exam,male,15,NA,mexican american,2,188,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +80954,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +80955,both interview and exam,female,72,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +80956,both interview and exam,female,18,NA,asian,2,221,FALSE,NA,FALSE,FALSE,0.5,12,NA,NA,NA,TRUE,2500 +80957,both interview and exam,male,12,NA,black,1,156,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +80958,both interview and exam,male,9,NA,mexican american,2,113,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +80959,interview only,female,24,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,living_with_partner,unable to ascertain,TRUE,70000 +80960,both interview and exam,male,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,30000 +80961,both interview and exam,female,41,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,87500 +80962,both interview and exam,female,72,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,22500 +80963,both interview and exam,male,4,NA,black,1,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80964,both interview and exam,female,19,NA,white,1,238,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,60000 +80965,both interview and exam,male,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +80966,both interview and exam,female,27,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +80967,both interview and exam,male,40,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,22500 +80968,both interview and exam,male,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +80969,interview only,female,17,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +80970,both interview and exam,male,14,NA,mexican american,1,171,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +80971,both interview and exam,male,8,NA,white,2,103,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +80972,both interview and exam,male,8,NA,asian,1,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +80973,both interview and exam,female,47,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,NA,TRUE,12500 +80974,both interview and exam,female,14,NA,other,2,175,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +80975,both interview and exam,female,26,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +80976,both interview and exam,male,59,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +80977,both interview and exam,male,0,8,mexican american,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +80978,both interview and exam,male,0,1,other,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80979,both interview and exam,male,29,NA,other hispanic,1,NA,TRUE,FALSE,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +80980,both interview and exam,female,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,50000 +80981,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +80982,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +80983,both interview and exam,female,5,NA,black,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80984,both interview and exam,female,7,NA,other,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +80985,both interview and exam,male,46,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,25,NA,5,married,NA,TRUE,87500 +80986,both interview and exam,female,1,19,other,2,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80987,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,30000 +80988,both interview and exam,female,65,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,30000 +80989,both interview and exam,male,46,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +80990,both interview and exam,male,35,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,NA +80991,both interview and exam,female,11,NA,black,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 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hispanic,2,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,40000 +81002,both interview and exam,male,9,NA,white,1,109,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +81003,both interview and exam,female,16,NA,white,2,192,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +81004,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +81005,both interview and exam,female,1,16,white,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81006,both interview and exam,female,10,NA,mexican american,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +81007,interview only,female,3,NA,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81008,both interview and exam,male,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81009,both interview and exam,female,56,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,TRUE,17500 +81010,both interview and exam,male,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +81011,both interview and exam,female,60,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81012,both interview and exam,male,34,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,12500 +81013,both interview and exam,male,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81014,both interview and exam,male,27,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +81015,both interview and exam,female,20,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +81016,both interview and exam,male,6,NA,other hispanic,1,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +81017,both interview and exam,male,15,NA,white,2,187,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,60000 +81018,both interview and exam,female,9,NA,black,2,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,50000 +81019,both interview and exam,female,14,NA,black,1,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +81020,both interview and exam,male,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +81021,interview only,male,2,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81022,both interview and exam,male,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,30000 +81023,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,yes,TRUE,17500 +81024,both interview and exam,male,6,NA,white,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +81025,both interview and exam,female,69,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,divorced,NA,FALSE,NA +81026,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,30000 +81027,both interview and exam,female,0,9,black,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81028,both interview and exam,male,12,NA,other hispanic,1,147,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,NA +81029,both interview and exam,male,43,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,married,NA,FALSE,NA +81030,both interview and exam,male,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +81031,both interview and exam,male,9,NA,black,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,2500 +81032,both interview and exam,male,71,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +81033,both interview and exam,female,9,NA,mexican american,1,120,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,30000 +81034,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +81035,both interview and exam,male,10,NA,white,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +81036,both interview and exam,male,2,NA,black,1,37,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81037,both interview and exam,male,60,NA,black,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,NA,TRUE,87500 +81038,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +81039,both interview and exam,male,64,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,7500 +81040,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,60000 +81041,both interview and exam,female,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +81042,both interview and exam,male,63,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,separated,NA,TRUE,100000 +81043,both interview and exam,female,18,NA,white,2,218,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +81044,both interview and exam,male,10,NA,mexican american,1,130,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,30000 +81045,both interview and exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81046,interview only,female,4,NA,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81047,both interview and exam,female,8,NA,mexican american,2,108,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +81048,both interview and exam,female,13,NA,black,1,162,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,2500 +81049,both interview and exam,female,12,NA,other hispanic,1,146,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81050,both interview and exam,female,38,NA,other,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,no,TRUE,50000 +81051,both interview and exam,male,41,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81052,both interview and exam,female,44,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,70000 +81053,both interview and exam,male,3,NA,mexican american,1,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +81054,both interview and exam,female,66,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,22500 +81055,both interview and exam,female,48,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,40000 +81056,both interview and exam,female,49,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +81057,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +81058,both interview and exam,female,5,NA,white,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81059,both interview and exam,male,4,NA,other hispanic,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81060,both interview and exam,female,14,NA,white,2,172,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +81061,both interview and exam,male,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +81062,interview only,female,48,NA,asian,NA,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +81063,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,22500 +81064,both interview and exam,male,11,NA,white,2,141,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +81065,both interview and exam,female,19,NA,black,2,231,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +81066,both interview and exam,female,1,18,white,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81067,both interview and exam,female,7,NA,white,1,85,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +81068,both interview and exam,male,59,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81069,both interview and exam,female,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,no,TRUE,7500 +81070,both interview and exam,male,31,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,NA,FALSE,40000 +81071,both interview and exam,male,2,NA,mexican american,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81072,both interview and exam,male,17,NA,mexican american,2,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,22500 +81073,both interview and exam,female,13,NA,black,2,164,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,NA +81074,both interview and exam,female,19,NA,other hispanic,1,234,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,22500 +81075,both interview and exam,male,30,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +81076,both interview and exam,female,18,NA,asian,2,224,FALSE,NA,FALSE,TRUE,7.5,13,NA,NA,NA,TRUE,30000 +81077,both interview and exam,male,0,8,mexican american,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81078,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,4,never_married,NA,FALSE,NA +81079,both interview and exam,male,76,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +81080,both interview and exam,female,12,NA,black,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81081,both interview and exam,male,3,NA,black,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81082,both interview and exam,female,60,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,never_married,NA,FALSE,NA +81083,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81084,both interview and exam,female,26,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,never_married,no,TRUE,100000 +81085,both interview and exam,male,4,NA,other,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81086,interview only,female,9,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +81087,both interview and exam,female,36,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81088,both interview and exam,female,54,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,30000 +81089,both interview and exam,male,11,NA,other hispanic,1,144,NA,NA,FALSE,FALSE,7.5,6,NA,NA,NA,FALSE,NA +81090,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,22500 +81091,both interview and exam,female,11,NA,black,1,136,NA,NA,FALSE,FALSE,NA,5,NA,NA,NA,TRUE,30000 +81092,both interview and exam,male,29,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,living_with_partner,NA,TRUE,12500 +81093,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,17500 +81094,both interview and exam,male,6,NA,other hispanic,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +81095,both interview and exam,male,51,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,40000 +81096,both interview and exam,female,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,unable to ascertain,TRUE,7500 +81097,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,30000 +81098,both interview and exam,female,5,NA,white,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81099,both interview and exam,female,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +81100,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +81101,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +81102,both interview and exam,male,4,NA,mexican american,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +81103,both interview and exam,male,80,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +81104,both interview and exam,female,67,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,7500 +81105,both interview and exam,male,63,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +81106,both interview and exam,female,10,NA,mexican american,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +81107,both interview and exam,female,54,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81108,both interview and exam,female,13,NA,mexican american,1,167,NA,NA,FALSE,FALSE,12.5,7,NA,NA,NA,FALSE,30000 +81109,both interview and exam,female,77,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81110,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81111,both interview and exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +81112,both interview and exam,female,3,NA,white,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81113,interview only,female,80,NA,other,NA,NA,FALSE,NA,FALSE,TRUE,55,NA,3,married,NA,TRUE,40000 +81114,both interview and exam,female,9,NA,black,1,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +81115,both interview and exam,male,60,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,100000 +81116,both interview and exam,female,16,NA,mexican american,1,200,NA,NA,FALSE,FALSE,7.5,10,NA,NA,NA,TRUE,22500 +81117,both interview and exam,male,19,NA,mexican american,1,236,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,FALSE,40000 +81118,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,no,TRUE,60000 +81119,both interview and exam,female,37,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +81120,both interview and exam,male,3,NA,other hispanic,1,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81121,both interview and exam,male,61,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +81122,both interview and exam,female,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,22500 +81123,both interview and exam,male,8,NA,white,1,103,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81124,both interview and exam,female,15,NA,white,2,190,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,7500 +81125,both interview and exam,male,15,NA,white,2,192,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +81126,both interview and exam,female,11,NA,other hispanic,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +81127,both interview and exam,male,9,NA,white,2,112,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +81128,both interview and exam,female,10,NA,other,2,125,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +81129,both interview and exam,male,12,NA,black,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +81130,both interview and exam,male,18,NA,asian,2,226,FALSE,NA,FALSE,TRUE,12.5,14,NA,NA,NA,TRUE,100000 +81131,both interview and exam,male,49,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +81132,both interview and exam,male,6,NA,black,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +81133,both interview and exam,female,17,NA,white,2,210,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81134,both interview and exam,female,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81135,both interview and exam,male,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,60000 +81136,both interview and exam,female,78,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,widowed,NA,TRUE,22500 +81137,both interview and exam,female,16,NA,mexican american,1,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +81138,both interview and exam,female,42,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,4,married,no,TRUE,100000 +81139,both interview and exam,male,23,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,4,never_married,NA,TRUE,87500 +81140,both interview and exam,male,6,NA,asian,1,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81141,both interview and exam,male,70,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,22500 +81142,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +81143,interview only,female,80,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +81144,both interview and exam,male,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +81145,both interview and exam,female,3,NA,black,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81146,both interview and exam,female,8,NA,other,2,99,NA,NA,FALSE,FALSE,0.5,0,NA,NA,NA,TRUE,2500 +81147,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81148,both interview and exam,female,73,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +81149,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81150,both interview and exam,male,13,NA,mexican american,2,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +81151,both interview and exam,male,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81152,both interview and exam,female,34,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,yes,TRUE,40000 +81153,both interview and exam,female,30,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,no,TRUE,30000 +81154,both interview and exam,male,50,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,FALSE,70000 +81155,both interview and exam,female,56,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +81156,both interview and exam,male,7,NA,black,1,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +81157,both interview and exam,female,3,NA,mexican american,2,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81158,both interview and exam,female,13,NA,mexican american,1,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,NA +81159,both interview and exam,female,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,60000 +81160,both interview and exam,male,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +81161,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,17500 +81162,both interview and exam,female,80,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,widowed,NA,TRUE,87500 +81163,both interview and exam,female,79,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,30000 +81164,both interview and exam,male,5,NA,black,1,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81165,both interview and exam,male,51,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,FALSE,100000 +81166,both interview and exam,female,73,NA,white,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,NA,TRUE,7500 +81167,both interview and exam,male,7,NA,white,1,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81168,both interview and exam,female,28,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,never_married,no,TRUE,60000 +81169,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +81170,both interview and exam,female,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,40000 +81171,both interview and exam,female,49,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,60000 +81172,both interview and exam,female,4,NA,white,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +81173,both interview and exam,female,50,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +81174,both interview and exam,female,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,30000 +81175,both interview and exam,male,80,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +81176,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,no,FALSE,40000 +81177,both interview and exam,female,48,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81178,both interview and exam,male,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +81179,interview only,male,80,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,NA +81180,both interview and exam,female,14,NA,mexican american,2,176,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +81181,both interview and exam,male,4,NA,white,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81182,both interview and exam,female,16,NA,asian,1,203,NA,NA,FALSE,FALSE,3,9,NA,NA,NA,TRUE,7500 +81183,both interview and exam,female,5,NA,mexican american,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81184,both interview and exam,male,7,NA,white,2,91,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81185,interview only,female,25,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,unable to ascertain,TRUE,100000 +81186,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +81187,both interview and exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,22500 +81188,both interview and exam,female,14,NA,mexican american,2,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +81189,both interview and exam,male,5,NA,white,2,63,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81190,both interview and exam,female,23,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +81191,both interview and exam,female,14,NA,asian,2,176,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +81192,both interview and exam,female,41,NA,other,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,TRUE,70000 +81193,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +81194,both interview and exam,female,11,NA,mexican american,2,144,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +81195,both interview and exam,female,4,NA,mexican american,1,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +81196,both interview and exam,female,41,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,divorced,no,TRUE,40000 +81197,both interview and exam,female,47,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,NA +81198,both interview and exam,male,0,7,black,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81199,both interview and exam,female,10,NA,asian,2,122,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +81200,both interview and exam,male,5,NA,black,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81201,both interview and exam,male,56,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,40000 +81202,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,22500 +81203,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81204,both interview and exam,female,65,NA,black,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,TRUE,NA +81205,both interview and exam,female,4,NA,white,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81206,both interview and exam,male,47,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +81207,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,NA,TRUE,100000 +81208,both interview and exam,female,2,NA,black,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +81209,both interview and exam,male,58,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,100000 +81210,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,100000 +81211,both interview and exam,male,3,NA,asian,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81212,both interview and exam,female,37,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +81213,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,40000 +81214,both interview and exam,male,50,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,NA,TRUE,30000 +81215,both interview and exam,female,0,7,white,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81216,both interview and exam,female,30,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81217,both interview and exam,male,45,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +81218,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81219,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,40000 +81220,both interview and exam,male,12,NA,white,2,150,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81221,both interview and exam,female,68,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,widowed,NA,FALSE,100000 +81222,both interview and exam,male,14,NA,white,2,174,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +81223,both interview and exam,female,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,17500 +81224,both interview and exam,female,18,NA,white,2,221,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,100000 +81225,both interview and exam,male,37,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +81226,both interview and exam,male,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,12500 +81227,both interview and exam,female,12,NA,white,1,150,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,NA +81228,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81229,both interview and exam,male,74,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,widowed,NA,FALSE,2500 +81230,both interview and exam,female,52,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +81231,both interview and exam,female,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +81232,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +81233,both interview and exam,male,10,NA,white,2,122,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +81234,both interview and exam,male,67,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,55,NA,5,divorced,NA,TRUE,NA +81235,both interview and exam,male,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +81236,both interview and exam,female,7,NA,black,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +81237,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +81238,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,40000 +81239,both interview and exam,female,14,NA,white,2,179,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,22500 +81240,both interview and exam,male,7,NA,black,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +81241,both interview and exam,male,51,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,50000 +81242,both interview and exam,male,14,NA,mexican american,1,177,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,17500 +81243,both interview and exam,male,8,NA,black,1,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +81244,both interview and exam,female,47,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81245,interview only,female,16,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +81246,both interview and exam,male,17,NA,black,1,215,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,22500 +81247,both interview and exam,male,15,NA,black,1,187,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +81248,both interview and exam,female,68,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +81249,both interview and exam,female,7,NA,white,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81250,both interview and exam,male,50,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,7500 +81251,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,FALSE,TRUE,55,NA,3,widowed,NA,TRUE,22500 +81252,both interview and exam,male,15,NA,black,2,189,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +81253,both interview and exam,male,4,NA,mexican american,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81254,both interview and exam,female,12,NA,other hispanic,2,156,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,NA +81255,both interview and exam,female,1,20,white,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81256,both interview and exam,male,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,12500 +81257,both interview and exam,male,7,NA,black,1,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +81258,both interview and exam,male,2,NA,other,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +81259,both interview and exam,male,75,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +81260,both interview and exam,male,44,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +81261,both interview and exam,female,14,NA,white,2,177,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +81262,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81263,both interview and exam,male,2,NA,black,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81264,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,87500 +81265,both interview and exam,male,7,NA,other,2,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +81266,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +81267,both interview and exam,female,75,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +81268,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,12500 +81269,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +81270,both interview and exam,male,43,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,100000 +81271,interview only,male,1,14,other,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81272,both interview and exam,female,46,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,never_married,NA,FALSE,NA +81273,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +81274,both interview and exam,male,13,NA,mexican american,2,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +81275,both interview and exam,female,50,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,FALSE,30000 +81276,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81277,both interview and exam,male,3,NA,mexican american,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +81278,both interview and exam,male,18,NA,other,2,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +81279,both interview and exam,male,7,NA,other,2,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +81280,both interview and exam,male,15,NA,asian,1,182,NA,NA,FALSE,FALSE,12.5,8,NA,NA,NA,TRUE,100000 +81281,both interview and exam,male,17,NA,black,1,207,FALSE,NA,FALSE,FALSE,NA,11,NA,NA,NA,TRUE,NA +81282,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +81283,both interview and exam,female,67,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,TRUE,40000 +81284,both interview and exam,female,64,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,FALSE,30000 +81285,both interview and exam,female,74,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +81286,both interview and exam,female,16,NA,asian,1,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +81287,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,60000 +81288,both interview and exam,female,71,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,widowed,NA,TRUE,17500 +81289,both interview and exam,female,17,NA,white,2,211,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81290,both interview and exam,male,30,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,2500 +81291,both interview and exam,male,21,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +81292,both interview and exam,male,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,87500 +81293,both interview and exam,male,7,NA,black,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81294,both interview and exam,male,18,NA,black,1,220,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +81295,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81296,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +81297,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +81298,both interview and exam,male,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,5,married,NA,TRUE,NA +81299,both interview and exam,female,2,NA,white,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81300,both interview and exam,male,17,NA,white,1,215,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +81301,both interview and exam,male,3,NA,white,1,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81302,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +81303,both interview and exam,male,20,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +81304,both interview and exam,female,20,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,never_married,unable to ascertain,FALSE,87500 +81305,both interview and exam,female,2,NA,mexican american,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +81306,both interview and exam,male,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +81307,both interview and exam,female,8,NA,mexican american,2,106,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +81308,both interview and exam,male,4,NA,mexican american,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +81309,both interview and exam,female,55,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,40000 +81310,both interview and exam,male,19,NA,mexican american,2,239,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +81311,both interview and exam,male,68,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,NA +81312,both interview and exam,female,19,NA,asian,2,237,FALSE,NA,FALSE,FALSE,3,13,NA,NA,NA,TRUE,22500 +81313,both interview and exam,male,20,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +81314,both interview and exam,male,10,NA,other,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +81315,both interview and exam,male,3,NA,other,2,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81316,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,40000 +81317,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81318,both interview and exam,female,16,NA,white,2,198,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +81319,both interview and exam,female,38,NA,black,1,NA,FALSE,NA,FALSE,FALSE,35,NA,4,divorced,no,TRUE,40000 +81320,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +81321,both interview and exam,female,80,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,2,widowed,NA,TRUE,70000 +81322,both interview and exam,female,55,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,divorced,NA,TRUE,40000 +81323,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81324,both interview and exam,male,1,22,black,1,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +81325,both interview and exam,female,9,NA,asian,2,112,NA,NA,FALSE,TRUE,7.5,3,NA,NA,NA,TRUE,100000 +81326,both interview and exam,female,16,NA,mexican american,2,201,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,50000 +81327,both interview and exam,male,11,NA,white,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81328,both interview and exam,male,18,NA,white,1,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +81329,both interview and exam,female,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +81330,both interview and exam,female,6,NA,mexican american,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +81331,both interview and exam,female,27,NA,white,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,never_married,no,TRUE,50000 +81332,both interview and exam,female,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +81333,both interview and exam,male,2,NA,black,2,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 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interview and exam,male,59,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,70000 +81345,both interview and exam,female,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,40000 +81346,both interview and exam,male,2,NA,white,1,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81347,both interview and exam,male,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81348,both interview and exam,male,21,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,never_married,NA,FALSE,50000 +81349,both interview and exam,male,36,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,living_with_partner,NA,FALSE,17500 +81350,both interview and exam,female,58,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,FALSE,30000 +81351,both interview and exam,female,14,NA,other,2,175,NA,NA,FALSE,FALSE,0.5,7,NA,NA,NA,TRUE,2500 +81352,both interview and exam,male,58,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,22500 +81353,both interview and exam,male,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81354,both interview and exam,female,3,NA,white,1,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81355,both interview and exam,female,6,NA,black,1,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +81356,both interview and exam,male,12,NA,black,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +81357,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +81358,both interview and exam,female,77,NA,black,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,widowed,NA,TRUE,7500 +81359,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +81360,both interview and exam,male,0,5,other hispanic,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81361,both interview and exam,female,8,NA,mexican american,2,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +81362,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,NA 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exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,70000 +81373,both interview and exam,male,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +81374,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,no,TRUE,60000 +81375,both interview and exam,female,41,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,no,TRUE,87500 +81376,both interview and exam,female,5,NA,asian,1,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81377,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81378,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +81379,both interview and exam,male,48,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +81380,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,12500 +81381,both interview and exam,female,73,NA,white,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,1,widowed,NA,TRUE,12500 +81382,both interview and exam,male,71,NA,mexican american,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81383,both interview and exam,male,16,NA,white,2,196,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +81384,both interview and exam,male,40,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,100000 +81385,both interview and exam,male,69,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81386,both interview and exam,female,18,NA,mexican american,1,220,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 +81387,both interview and exam,female,52,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,never_married,NA,TRUE,12500 +81388,both interview and exam,male,26,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,TRUE,22500 +81389,both interview and exam,male,13,NA,asian,2,160,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,70000 +81390,both interview and exam,male,3,NA,other,1,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81391,both interview and exam,male,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +81392,both interview and exam,female,11,NA,mexican american,2,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,70000 +81393,both interview and exam,female,16,NA,other hispanic,2,201,NA,NA,FALSE,FALSE,3,9,NA,NA,NA,FALSE,NA +81394,both interview and exam,female,10,NA,mexican american,1,130,NA,NA,FALSE,FALSE,7.5,4,NA,NA,NA,FALSE,40000 +81395,both interview and exam,male,23,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +81396,both interview and exam,male,21,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,never_married,NA,TRUE,50000 +81397,interview only,male,15,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,22500 +81398,both interview and exam,female,2,NA,white,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81399,interview 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exam,female,65,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,70000 +81410,both interview and exam,male,6,NA,white,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,60000 +81411,both interview and exam,male,15,NA,asian,2,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +81412,both interview and exam,male,67,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,5,divorced,NA,TRUE,22500 +81413,both interview and exam,female,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,70000 +81414,both interview and exam,male,13,NA,black,2,163,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +81415,both interview and exam,male,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81416,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +81417,both interview and exam,male,2,NA,black,1,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +81418,both interview and exam,female,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +81419,both interview and exam,female,14,NA,mexican american,1,169,NA,NA,FALSE,FALSE,12.5,7,NA,NA,NA,TRUE,22500 +81420,both interview and exam,male,1,15,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81421,both interview and exam,female,7,NA,black,1,85,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +81422,both interview and exam,male,4,NA,mexican american,2,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81423,both interview and exam,male,7,NA,asian,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +81424,both interview and exam,female,27,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +81425,both interview and exam,male,2,NA,black,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81426,both interview and exam,female,12,NA,black,1,155,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +81427,both interview and exam,male,52,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,living_with_partner,NA,FALSE,17500 +81428,both interview and exam,female,26,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +81429,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81430,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81431,interview only,male,5,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81432,both interview and exam,male,8,NA,black,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +81433,both interview and exam,male,17,NA,mexican american,1,206,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +81434,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +81435,both interview and exam,male,18,NA,white,1,216,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +81436,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,7500 +81437,both interview and exam,male,16,NA,black,1,195,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +81438,both interview and exam,female,56,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +81439,both interview and exam,male,0,3,white,1,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81440,both interview and exam,female,2,NA,other hispanic,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81441,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +81442,both interview and exam,female,32,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,divorced,no,FALSE,NA +81443,both interview and exam,male,1,12,white,1,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81444,both interview and exam,female,51,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,FALSE,70000 +81445,both interview and exam,male,10,NA,mexican american,1,129,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,NA +81446,both interview and exam,female,11,NA,mexican american,1,136,NA,NA,FALSE,FALSE,12.5,5,NA,NA,NA,FALSE,30000 +81447,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,7500 +81448,both interview and exam,male,18,NA,other hispanic,2,226,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,7500 +81449,both interview and exam,male,6,NA,black,2,79,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81450,both interview and exam,female,56,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,divorced,NA,TRUE,50000 +81451,both interview and exam,male,19,NA,white,1,236,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,40000 +81452,both interview and exam,male,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +81453,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +81454,both interview and exam,male,15,NA,other,1,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,22500 +81455,both interview and exam,male,1,15,black,2,16,NA,NA,FALSE,TRUE,0.5,NA,NA,NA,NA,TRUE,100000 +81456,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +81457,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,100000 +81458,both interview and exam,female,0,9,mexican american,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81459,both interview and exam,female,1,23,mexican american,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +81460,both interview and exam,female,46,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,87500 +81461,both interview and exam,male,24,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,NA,TRUE,22500 +81462,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,FALSE,NA +81463,both interview and exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,22500 +81464,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81465,both interview and exam,female,68,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,married,NA,TRUE,12500 +81466,both interview and exam,male,0,4,mexican american,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +81467,both interview and exam,female,7,NA,asian,1,85,NA,NA,FALSE,TRUE,3,0,NA,NA,NA,TRUE,100000 +81468,both interview and exam,male,74,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81469,both interview and exam,male,16,NA,mexican american,1,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,NA +81470,both interview and exam,female,43,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,87500 +81471,both interview and exam,female,14,NA,asian,1,170,NA,NA,FALSE,FALSE,0.5,7,NA,NA,NA,TRUE,87500 +81472,both interview and exam,male,29,NA,other,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,never_married,NA,TRUE,NA +81473,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,unable to ascertain,TRUE,17500 +81474,both interview and exam,female,78,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,40000 +81475,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,22500 +81476,both interview and exam,male,12,NA,white,2,147,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +81477,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +81478,both interview and exam,female,4,NA,black,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81479,both interview and exam,male,11,NA,black,2,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81480,both interview and exam,male,12,NA,black,1,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,60000 +81481,both interview and exam,female,28,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,married,no,TRUE,60000 +81482,both interview and exam,male,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81483,both interview and exam,male,5,NA,mexican american,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 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exam,male,5,NA,black,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81494,both interview and exam,male,38,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +81495,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +81496,both interview and exam,male,14,NA,white,2,174,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,87500 +81497,both interview and exam,female,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,50000 +81498,both interview and exam,female,11,NA,mexican american,2,133,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81499,both interview and exam,female,18,NA,mexican american,2,220,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +81500,both interview and exam,female,10,NA,mexican american,1,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +81501,both interview and exam,female,6,NA,black,1,75,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +81502,both interview and exam,male,17,NA,black,2,205,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 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exam,male,69,NA,asian,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +81513,both interview and exam,male,7,NA,black,2,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +81514,both interview and exam,male,23,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +81515,both interview and exam,male,2,NA,mexican american,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81516,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +81517,both interview and exam,female,15,NA,asian,1,191,NA,NA,FALSE,FALSE,7.5,9,NA,NA,NA,TRUE,17500 +81518,both interview and exam,female,13,NA,black,1,159,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +81519,both interview and exam,male,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81520,interview only,female,15,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,22500 +81521,both interview and exam,female,55,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,100000 +81522,both interview and exam,female,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +81523,both interview and exam,female,57,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +81524,both interview and exam,male,73,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,50000 +81525,both interview and exam,male,10,NA,mexican american,1,120,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +81526,both interview and exam,female,16,NA,other,2,203,NA,NA,FALSE,FALSE,0.5,8,NA,NA,NA,TRUE,2500 +81527,both interview and exam,male,35,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +81528,both interview and exam,female,41,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,17500 +81529,both interview and exam,female,1,13,mexican american,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +81530,both interview and exam,female,73,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81531,both interview and exam,female,5,NA,other hispanic,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +81532,both interview and exam,male,5,NA,asian,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81533,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +81534,both interview and exam,female,49,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,17500 +81535,both interview and exam,female,46,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +81536,both interview and exam,female,8,NA,other hispanic,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +81537,both interview and exam,female,55,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,NA,FALSE,NA +81538,both interview and exam,male,12,NA,mexican american,2,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,7500 +81539,both interview and exam,male,7,NA,mexican american,2,94,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +81540,both interview and exam,female,7,NA,black,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81541,both interview and exam,female,15,NA,black,1,188,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +81542,both interview and exam,male,3,NA,white,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81543,both interview and exam,male,14,NA,white,2,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81544,both interview and exam,male,37,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,87500 +81545,both interview and exam,male,16,NA,mexican american,2,200,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +81546,both interview and exam,male,6,NA,black,1,82,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +81547,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,12500 +81548,both interview and exam,male,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,40000 +81549,both interview and exam,female,6,NA,white,2,81,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +81550,both interview and exam,male,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81551,both interview and exam,female,15,NA,mexican american,2,191,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +81552,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +81553,both interview and exam,female,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81554,both interview and exam,female,8,NA,mexican american,2,98,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,40000 +81555,both interview and exam,female,6,NA,black,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +81556,both interview and exam,female,25,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +81557,both interview and exam,male,13,NA,other,1,160,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +81558,both interview and exam,female,7,NA,white,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81559,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81560,both interview and exam,male,1,15,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81561,both interview and exam,male,10,NA,white,1,127,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +81562,both interview and exam,male,2,NA,other hispanic,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81563,both interview and exam,male,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +81564,both interview and exam,male,50,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,TRUE,17500 +81565,both interview and exam,male,9,NA,mexican american,1,119,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,17500 +81566,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +81567,both interview and exam,male,3,NA,asian,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81568,both interview and exam,female,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,50000 +81569,both interview and exam,male,1,12,asian,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81570,both interview and exam,female,58,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +81571,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,yes,TRUE,30000 +81572,both interview and exam,female,15,NA,black,1,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +81573,both interview and exam,female,64,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,never_married,NA,TRUE,2500 +81574,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81575,both interview and exam,male,11,NA,mexican american,2,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,60000 +81576,both interview and exam,female,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,no,FALSE,NA +81577,both interview and exam,male,9,NA,mexican american,2,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +81578,both interview and exam,male,60,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81579,both interview and exam,female,73,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,1,never_married,NA,FALSE,22500 +81580,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +81581,both interview and exam,male,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,widowed,NA,TRUE,12500 +81582,both interview and exam,male,72,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,22500 +81583,both interview and exam,female,18,NA,mexican american,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +81584,both interview and exam,female,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81585,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,22500 +81586,both interview and exam,male,6,NA,other hispanic,1,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +81587,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +81588,both interview and exam,female,11,NA,black,2,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +81589,both interview and exam,female,9,NA,asian,2,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +81590,both interview and exam,male,28,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,living_with_partner,NA,FALSE,30000 +81591,both interview and exam,female,14,NA,other,2,170,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +81592,interview only,female,4,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81593,both interview and exam,male,68,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,3,separated,NA,FALSE,17500 +81594,both interview and exam,male,60,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +81595,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +81596,both interview and exam,male,35,NA,white,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,NA,TRUE,22500 +81597,interview only,male,63,NA,black,NA,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,50000 +81598,both interview and exam,male,50,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,30000 +81599,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81600,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81601,both interview and exam,male,65,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,17500 +81602,both interview and exam,female,37,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,NA +81603,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +81604,both interview and exam,female,29,NA,black,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,never_married,no,TRUE,30000 +81605,both interview and exam,male,43,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,100000 +81606,both interview and exam,female,42,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,100000 +81607,both interview and exam,female,29,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +81608,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81609,both interview and exam,male,54,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,FALSE,NA +81610,both interview and exam,male,60,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,NA +81611,both interview and exam,male,31,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,separated,NA,FALSE,NA +81612,both interview and exam,female,3,NA,mexican american,1,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +81613,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,17500 +81614,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +81615,both interview and exam,female,10,NA,mexican american,2,127,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,17500 +81616,both interview and exam,female,10,NA,mexican american,1,122,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,17500 +81617,both interview and exam,male,52,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,never_married,NA,FALSE,NA +81618,both interview and exam,female,19,NA,white,1,230,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +81619,both interview and exam,female,18,NA,mexican american,2,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,40000 +81620,both interview and exam,male,26,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +81621,both interview and exam,female,15,NA,white,2,186,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +81622,both interview and exam,female,65,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +81623,both interview and exam,female,63,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,50000 +81624,both interview and exam,female,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81625,both interview and exam,female,41,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,married,no,TRUE,70000 +81626,both interview and exam,female,40,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,separated,no,TRUE,30000 +81627,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,NA +81628,both interview and exam,female,66,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +81629,both interview and exam,female,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81630,both interview and exam,female,14,NA,white,1,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,60000 +81631,both interview and exam,male,1,15,other,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +81632,both interview and exam,female,3,NA,black,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81633,both interview and exam,male,51,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +81634,both interview and exam,male,14,NA,white,2,175,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +81635,both interview and exam,female,5,NA,other hispanic,1,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81636,both interview and exam,male,79,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +81637,both interview and exam,male,5,NA,mexican american,1,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +81638,both interview and exam,female,15,NA,mexican american,1,188,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,22500 +81639,both interview and exam,female,13,NA,black,1,158,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +81640,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +81641,both interview and exam,female,9,NA,black,2,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +81642,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +81643,both interview and exam,female,50,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,22500 +81644,both interview and exam,male,6,NA,white,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81645,both interview and exam,female,52,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,FALSE,100000 +81646,both interview and exam,male,0,9,black,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81647,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +81648,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +81649,both interview and exam,female,19,NA,mexican american,1,237,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,70000 +81650,both interview and exam,male,9,NA,mexican american,1,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,30000 +81651,both interview and exam,male,2,NA,white,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81652,both interview and exam,male,0,0,black,2,0,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81653,both interview and exam,male,14,NA,mexican american,1,173,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,NA +81654,both interview and exam,male,67,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81655,interview only,male,80,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +81656,both interview and exam,male,14,NA,other,2,175,NA,NA,FALSE,FALSE,0.5,7,NA,NA,NA,TRUE,2500 +81657,both interview and exam,male,3,NA,white,2,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +81658,both interview and exam,female,2,NA,other hispanic,2,25,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,87500 +81659,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,separated,no,FALSE,7500 +81660,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,22500 +81661,both interview and exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +81662,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +81663,both interview and exam,female,9,NA,mexican american,2,116,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,12500 +81664,both interview and exam,female,51,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,60000 +81665,both interview and exam,male,36,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +81666,both interview and exam,female,37,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,NA +81667,both interview and exam,female,19,NA,black,2,229,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,50000 +81668,both interview and exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +81669,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,30000 +81670,both interview and exam,female,15,NA,asian,2,181,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,NA +81671,both interview and exam,male,65,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,40000 +81672,both interview and exam,female,33,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,separated,no,TRUE,12500 +81673,both interview and exam,female,2,NA,white,1,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81674,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,22500 +81675,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +81676,both interview and exam,female,14,NA,other hispanic,1,173,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +81677,both interview and exam,male,60,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,FALSE,87500 +81678,both interview and exam,male,17,NA,black,1,213,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +81679,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81680,both interview and exam,female,18,NA,mexican american,1,222,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,70000 +81681,both interview and exam,female,42,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,3,married,no,FALSE,87500 +81682,both interview and exam,female,6,NA,other hispanic,1,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +81683,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +81684,both interview and exam,female,2,NA,white,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81685,both interview and exam,male,12,NA,white,1,153,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81686,both interview and exam,female,55,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,70000 +81687,both interview and exam,male,13,NA,mexican american,1,168,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +81688,both interview and exam,female,3,NA,other,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81689,both interview and exam,female,18,NA,white,1,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,22500 +81690,both interview and exam,male,1,14,white,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81691,both interview and exam,male,9,NA,white,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +81692,both interview and exam,female,17,NA,black,2,214,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,60000 +81693,both interview and exam,female,7,NA,black,2,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +81694,both interview and exam,female,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +81695,both interview and exam,female,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,unable to ascertain,TRUE,40000 +81696,both interview and exam,female,3,NA,asian,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81697,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +81698,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81699,both interview and exam,female,19,NA,black,2,238,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,60000 +81700,both interview and exam,female,30,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +81701,both interview and exam,male,52,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81702,both interview and exam,male,6,NA,other,1,76,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81703,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81704,both interview and exam,male,45,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81705,both interview and exam,male,9,NA,white,2,112,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +81706,both interview and exam,male,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81707,both interview and exam,male,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +81708,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,2500 +81709,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +81710,both interview and exam,female,3,NA,white,1,38,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,100000 +81711,both interview and exam,female,32,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +81712,both interview and exam,male,66,NA,other hispanic,2,NA,TRUE,TRUE,FALSE,TRUE,55,NA,4,married,NA,TRUE,60000 +81713,both interview and exam,female,16,NA,black,1,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,22500 +81714,both interview and exam,female,58,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81715,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,NA +81716,both interview and exam,female,11,NA,other,2,142,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +81717,both interview and exam,male,35,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +81718,both interview and exam,male,1,18,white,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81719,both interview and exam,male,43,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,40000 +81720,both interview and exam,male,11,NA,mexican american,1,144,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,70000 +81721,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +81722,both interview and exam,female,47,NA,black,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,100000 +81723,both interview and exam,male,1,16,other hispanic,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81724,both interview and exam,male,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +81725,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,no,TRUE,100000 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american,2,150,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +81736,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81737,both interview and exam,male,70,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,60000 +81738,both interview and exam,female,15,NA,mexican american,2,188,NA,NA,FALSE,TRUE,12.5,9,NA,NA,NA,FALSE,40000 +81739,interview only,female,13,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81740,both interview and exam,male,21,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,4,never_married,NA,TRUE,22500 +81741,both interview and exam,male,43,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +81742,both interview and exam,male,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81743,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,FALSE,TRUE,55,NA,2,widowed,NA,TRUE,22500 +81744,both interview and exam,female,5,NA,white,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81745,both interview and exam,male,16,NA,black,1,204,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +81746,both interview and exam,female,8,NA,black,1,98,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81747,both interview and exam,male,1,15,black,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81748,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +81749,both interview and exam,male,0,1,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81750,both interview and exam,female,22,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,22500 +81751,both interview and exam,female,17,NA,mexican american,1,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +81752,both interview and exam,male,41,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +81753,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81754,both interview and exam,female,16,NA,black,1,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81755,both interview and exam,male,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81756,both interview and exam,male,2,NA,white,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81757,both interview and exam,male,10,NA,black,2,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,17500 +81758,both interview and exam,male,14,NA,black,1,172,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +81759,both interview and exam,male,9,NA,black,2,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +81760,both interview and exam,female,36,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,no,FALSE,22500 +81761,both interview and exam,female,1,14,black,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81762,both interview and exam,female,22,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,no,TRUE,NA +81763,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,30000 +81764,both interview and exam,male,74,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +81765,both interview and exam,male,17,NA,other hispanic,1,211,FALSE,NA,FALSE,FALSE,0.5,9,NA,NA,NA,FALSE,50000 +81766,both interview and exam,male,32,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81767,interview only,female,57,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,60000 +81768,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +81769,both interview and exam,male,4,NA,asian,1,51,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,87500 +81770,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,2,married,NA,FALSE,NA +81771,both interview and exam,male,18,NA,white,2,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +81772,both interview and exam,male,49,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,FALSE,30000 +81773,both interview and exam,male,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +81774,both interview and exam,male,0,3,other,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81775,both interview and exam,male,17,NA,white,2,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +81776,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,no,TRUE,7500 +81777,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,70000 +81778,both interview and exam,male,18,NA,black,1,221,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81779,both interview and exam,female,63,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,7500 +81780,both interview and exam,male,22,NA,mexican american,2,NA,TRUE,TRUE,FALSE,TRUE,17.5,NA,3,never_married,NA,TRUE,40000 +81781,both interview and exam,male,50,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81782,both interview and exam,male,17,NA,asian,1,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +81783,both interview and exam,male,44,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +81784,both interview and exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +81785,both interview and exam,female,70,NA,other hispanic,2,NA,FALSE,NA,FALSE,NA,55,NA,1,widowed,NA,TRUE,12500 +81786,both interview and exam,female,1,20,other hispanic,2,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81787,both interview and exam,male,34,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,40000 +81788,both interview and exam,male,0,6,white,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81789,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +81790,both interview and exam,female,8,NA,asian,1,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +81791,both interview and exam,male,1,21,white,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81792,interview only,male,49,NA,white,NA,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +81793,both interview and exam,male,4,NA,mexican american,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81794,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +81795,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,TRUE,70000 +81796,both interview and exam,female,8,NA,black,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +81797,both interview and exam,female,74,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,40000 +81798,both interview and exam,male,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,22500 +81799,both interview and exam,male,10,NA,other,2,130,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +81800,both interview and exam,male,7,NA,black,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,2500 +81801,both interview and exam,male,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,100000 +81802,both interview and exam,male,30,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,never_married,NA,TRUE,100000 +81803,both interview and exam,male,18,NA,asian,1,225,FALSE,NA,FALSE,FALSE,3,13,NA,NA,NA,TRUE,2500 +81804,both interview and exam,female,14,NA,black,1,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81805,both interview and exam,female,21,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,yes,TRUE,22500 +81806,both interview and exam,female,32,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,no,TRUE,70000 +81807,both interview and exam,male,0,4,black,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81808,both interview and exam,female,18,NA,mexican american,2,218,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +81809,both interview and exam,male,40,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81810,both interview and exam,male,11,NA,other,2,140,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +81811,interview only,female,2,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81812,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +81813,both interview and exam,female,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,60000 +81814,both interview and exam,male,67,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81815,both interview and exam,male,75,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,12500 +81816,both interview and exam,female,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,12500 +81817,both interview and exam,male,6,NA,black,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,50000 +81818,both interview and exam,male,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +81819,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,17500 +81820,both interview and exam,male,65,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +81821,both interview and exam,male,0,9,other hispanic,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81822,both interview and exam,female,51,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +81823,both interview and exam,male,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +81824,both interview and exam,male,78,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +81825,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,22500 +81826,both interview and exam,female,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +81827,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81828,both interview and exam,female,45,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81829,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,separated,no,TRUE,40000 +81830,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +81831,both interview and exam,female,72,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +81832,interview only,male,80,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +81833,both interview and exam,male,72,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81834,both interview and exam,male,33,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,50000 +81835,both interview and exam,female,47,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,NA +81836,both interview and exam,female,36,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +81837,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,unable to ascertain,TRUE,17500 +81838,both interview and exam,male,5,NA,other,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81839,both interview and exam,male,13,NA,other hispanic,1,160,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +81840,both interview and exam,male,6,NA,asian,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81841,both interview and exam,female,11,NA,white,1,133,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +81842,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,40000 +81843,both interview and exam,male,19,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +81844,both interview and exam,male,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,70000 +81845,both interview and exam,male,75,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81846,both interview and exam,female,19,NA,mexican american,1,232,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,7500 +81847,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +81848,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,4,never_married,no,TRUE,100000 +81849,both interview and exam,female,44,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,22500 +81850,both interview and exam,male,67,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81851,both interview and exam,male,73,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81852,both interview and exam,male,1,15,mexican american,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81853,both interview and exam,male,17,NA,asian,1,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +81854,both interview and exam,male,38,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +81855,both interview and exam,female,27,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,17500 +81856,both interview and exam,male,7,NA,other hispanic,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +81857,both interview and exam,male,5,NA,mexican american,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,40000 +81858,both interview and exam,female,22,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +81859,both interview and exam,male,0,8,white,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81860,both interview and exam,male,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +81861,both interview and exam,female,14,NA,white,2,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81862,interview only,female,20,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,7500 +81863,both interview and exam,male,56,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +81864,both interview and exam,male,17,NA,white,2,208,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +81865,both interview and exam,male,42,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81866,both interview and exam,female,53,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,separated,NA,TRUE,12500 +81867,both interview and exam,male,57,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,40000 +81868,both interview and exam,female,2,NA,other hispanic,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81869,both interview and exam,female,9,NA,other hispanic,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +81870,interview only,female,37,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,unable to ascertain,TRUE,100000 +81871,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +81872,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,30000 +81873,interview only,male,62,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,45,NA,5,never_married,NA,TRUE,100000 +81874,both interview and exam,male,3,NA,white,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81875,both interview and exam,female,70,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,17500 +81876,both interview and exam,male,9,NA,black,2,115,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +81877,both interview and exam,female,44,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81878,both interview and exam,male,7,NA,asian,2,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81879,both interview and exam,male,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +81880,both interview and exam,female,8,NA,mexican american,1,99,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +81881,both interview and exam,male,9,NA,mexican american,2,120,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,87500 +81882,both interview and exam,female,36,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,3,living_with_partner,no,FALSE,2500 +81883,both interview and exam,male,19,NA,white,2,237,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,40000 +81884,both interview and exam,male,6,NA,white,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,2500 +81885,both interview and exam,female,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,NA +81886,both interview and exam,male,47,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81887,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,12500 +81888,both interview and exam,male,0,10,asian,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81889,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,yes,TRUE,7500 +81890,both interview and exam,female,67,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +81891,both interview and exam,female,28,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,no,TRUE,100000 +81892,both interview and exam,male,16,NA,white,2,194,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81893,both interview and exam,male,30,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,TRUE,50000 +81894,both interview and exam,female,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,30000 +81895,both interview and exam,female,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +81896,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,22500 +81897,both interview and exam,female,12,NA,other hispanic,2,155,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,17500 +81898,both interview and exam,female,29,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,unable to ascertain,TRUE,30000 +81899,both interview and exam,male,55,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +81900,both interview and exam,female,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +81901,both interview and exam,male,0,6,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +81902,both interview and exam,male,6,NA,white,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +81903,both interview and exam,male,30,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +81904,both interview and exam,female,47,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,never_married,NA,TRUE,70000 +81905,both interview and exam,male,15,NA,black,2,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,60000 +81906,both interview and exam,male,8,NA,mexican american,2,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +81907,both interview and exam,male,13,NA,black,2,157,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +81908,both interview and exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81909,both interview and exam,female,18,NA,black,2,224,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +81910,both interview and exam,male,30,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,60000 +81911,both interview and exam,male,13,NA,black,1,161,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +81912,both interview and exam,male,6,NA,mexican american,2,82,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,NA +81913,both interview and exam,female,18,NA,mexican american,1,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 +81914,both interview and exam,male,15,NA,other,1,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81915,both interview and exam,male,6,NA,asian,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81916,both interview and exam,male,6,NA,white,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +81917,both interview and exam,male,14,NA,black,1,169,NA,NA,FALSE,FALSE,7.5,7,NA,NA,NA,TRUE,22500 +81918,interview only,female,19,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,17.5,14,NA,NA,NA,TRUE,7500 +81919,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +81920,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81921,both interview and exam,female,14,NA,black,2,180,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,7500 +81922,both interview and exam,female,9,NA,white,2,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +81923,both interview and exam,male,35,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +81924,both interview and exam,female,10,NA,mexican american,2,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,30000 +81925,both interview and exam,male,23,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,never_married,NA,TRUE,50000 +81926,both interview and exam,male,12,NA,white,1,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +81927,both interview and exam,female,5,NA,other hispanic,2,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +81928,both interview and exam,male,2,NA,mexican american,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +81929,both interview and exam,female,15,NA,mexican american,2,188,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +81930,both interview and exam,male,18,NA,other hispanic,2,228,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,30000 +81931,both interview and exam,male,6,NA,white,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81932,both interview and exam,female,24,NA,black,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,living_with_partner,yes,TRUE,50000 +81933,both interview and exam,female,80,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,7500 +81934,both interview and exam,female,61,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81935,both interview and exam,female,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,7500 +81936,both interview and exam,female,1,23,other hispanic,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81937,interview only,male,15,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +81938,interview only,female,34,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,unable to ascertain,TRUE,87500 +81939,both interview and exam,female,5,NA,mexican american,2,69,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,FALSE,12500 +81940,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,NA +81941,both interview and exam,male,17,NA,other hispanic,2,209,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +81942,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,30000 +81943,both interview and exam,female,13,NA,other,2,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +81944,both interview and exam,female,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,60000 +81945,both interview and exam,female,53,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,87500 +81946,both interview and exam,female,30,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,no,FALSE,NA +81947,both interview and exam,female,0,1,black,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81948,both interview and exam,male,17,NA,mexican american,1,207,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,NA +81949,both interview and exam,male,47,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,87500 +81950,both interview and exam,male,52,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +81951,both interview and exam,male,14,NA,mexican american,2,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,100000 +81952,both interview and exam,male,56,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +81953,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,40000 +81954,both interview and exam,male,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81955,both interview and exam,male,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +81956,both interview and exam,female,35,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,no,TRUE,87500 +81957,both interview and exam,male,49,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +81958,both interview and exam,female,2,NA,white,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81959,both interview and exam,male,77,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81960,both interview and exam,male,17,NA,asian,2,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +81961,both interview and exam,female,13,NA,white,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +81962,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +81963,both interview and exam,male,3,NA,asian,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +81964,both interview and exam,male,0,8,black,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81965,both interview and exam,male,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +81966,both interview and exam,female,31,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +81967,both interview and exam,female,30,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,2500 +81968,both interview and exam,female,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,7500 +81969,both interview and exam,male,58,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,NA,TRUE,40000 +81970,both interview and exam,female,53,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +81971,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +81972,interview only,female,6,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,30000 +81973,both interview and exam,female,0,9,black,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81974,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81975,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +81976,both interview and exam,female,6,NA,white,2,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +81977,both interview and exam,female,16,NA,mexican american,1,196,NA,NA,FALSE,FALSE,12.5,9,NA,NA,NA,TRUE,22500 +81978,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +81979,both interview and exam,male,53,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +81980,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +81981,both interview and exam,female,3,NA,other hispanic,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81982,both interview and exam,female,55,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +81983,both interview and exam,female,72,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81984,both interview and exam,female,6,NA,asian,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81985,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +81986,both interview and exam,male,6,NA,other hispanic,1,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +81987,both interview and exam,female,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,TRUE,40000 +81988,both interview and exam,male,65,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +81989,both interview and exam,female,46,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,12500 +81990,both interview and exam,female,3,NA,white,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81991,both interview and exam,female,12,NA,black,2,147,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +81992,both interview and exam,female,51,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,NA,TRUE,87500 +81993,both interview and exam,male,43,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,NA,TRUE,100000 +81994,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,60000 +81995,both interview and exam,male,74,NA,asian,2,NA,TRUE,TRUE,FALSE,TRUE,45,NA,4,married,NA,TRUE,NA +81996,both interview and exam,male,48,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,FALSE,NA +81997,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +81998,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,NA +81999,both interview and exam,male,3,NA,black,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82000,both interview and exam,male,6,NA,white,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +82001,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,TRUE,60000 +82002,both interview and exam,female,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +82003,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +82004,both interview and exam,male,1,15,black,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82005,both interview and exam,male,68,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,30000 +82006,both interview and exam,male,46,NA,black,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,TRUE,50000 +82007,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +82008,both interview and exam,female,9,NA,mexican american,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +82009,interview only,female,8,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +82010,interview only,female,36,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,unable to ascertain,TRUE,100000 +82011,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,87500 +82012,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82013,both interview and exam,female,2,NA,black,2,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82014,both interview and exam,male,12,NA,white,2,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +82015,interview only,female,70,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,50000 +82016,both interview and exam,female,3,NA,white,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82017,both interview and exam,female,18,NA,white,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +82018,both interview and exam,male,11,NA,black,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +82019,both interview and exam,male,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +82020,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +82021,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +82022,both interview and exam,female,10,NA,black,1,122,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +82023,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,40000 +82024,both interview and exam,female,7,NA,black,1,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +82025,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +82026,both interview and exam,male,68,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82027,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,30000 +82028,both interview and exam,female,46,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +82029,both interview and exam,female,6,NA,other hispanic,2,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82030,both interview and exam,female,3,NA,asian,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82031,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +82032,both interview and exam,male,8,NA,black,2,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +82033,both interview and exam,male,7,NA,black,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +82034,both interview and exam,male,13,NA,other hispanic,2,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +82035,interview only,female,1,23,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82036,both interview and exam,male,17,NA,other hispanic,2,206,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +82037,both interview and exam,female,43,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,30000 +82038,both interview and exam,male,0,4,white,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82039,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,never_married,no,TRUE,22500 +82040,both interview and exam,male,7,NA,black,2,90,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +82041,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +82042,both interview and exam,male,17,NA,black,2,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +82043,both interview and exam,female,57,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,35,NA,5,married,NA,TRUE,70000 +82044,both interview and exam,female,9,NA,asian,2,112,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +82045,both interview and exam,female,6,NA,mexican american,2,82,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,2500 +82046,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,3,widowed,NA,TRUE,87500 +82047,both interview and exam,male,64,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +82048,both interview and exam,male,6,NA,black,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +82049,both interview and exam,female,15,NA,black,2,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +82050,both interview and exam,female,19,NA,other hispanic,2,228,FALSE,NA,FALSE,FALSE,7.5,13,NA,NA,NA,FALSE,NA +82051,both interview and exam,female,42,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,no,TRUE,100000 +82052,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +82053,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +82054,both interview and exam,male,8,NA,mexican american,2,107,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,7500 +82055,both interview and exam,male,77,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +82056,both interview and exam,male,76,NA,other hispanic,1,NA,TRUE,FALSE,FALSE,TRUE,55,NA,4,married,NA,TRUE,30000 +82057,both interview and exam,female,36,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +82058,both interview and exam,male,34,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,100000 +82059,both interview and exam,female,29,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +82060,both interview and exam,female,25,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +82061,both interview and exam,female,80,NA,black,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,widowed,NA,TRUE,NA +82062,both interview and exam,female,54,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +82063,both interview and exam,male,10,NA,white,1,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,NA +82064,both interview and exam,female,6,NA,other hispanic,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +82065,both interview and exam,male,3,NA,white,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +82066,both interview and exam,female,15,NA,white,2,183,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +82067,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,7500 +82068,both interview and exam,male,44,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,living_with_partner,NA,FALSE,30000 +82069,both interview and exam,male,10,NA,black,2,132,NA,NA,FALSE,FALSE,NA,5,NA,NA,NA,TRUE,50000 +82070,both interview and exam,male,18,NA,white,2,218,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +82071,both interview and exam,female,16,NA,white,1,201,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +82072,both interview and exam,male,14,NA,white,2,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +82073,both interview and exam,male,19,NA,white,1,237,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +82074,both interview and exam,female,1,14,white,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +82075,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82076,both interview and exam,female,5,NA,other,2,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82077,both interview and exam,male,40,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,87500 +82078,both interview and exam,male,8,NA,mexican american,1,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +82079,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,70000 +82080,both interview and exam,male,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82081,both interview and exam,male,0,8,mexican american,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +82082,both interview and exam,male,2,NA,asian,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82083,both interview and exam,female,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +82084,both interview and exam,male,1,13,white,1,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82085,both interview and exam,male,54,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +82086,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +82087,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82088,both interview and exam,female,19,NA,black,1,236,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,12500 +82089,both interview and exam,male,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,7500 +82090,both interview and exam,female,48,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,40000 +82091,both interview and exam,female,69,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,30000 +82092,interview only,female,62,NA,other hispanic,NA,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,divorced,NA,FALSE,12500 +82093,both interview and exam,male,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +82094,interview only,male,27,NA,other hispanic,NA,NA,FALSE,NA,FALSE,FALSE,3,NA,1,never_married,NA,FALSE,40000 +82095,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,70000 +82096,both interview and exam,male,16,NA,black,2,199,NA,NA,FALSE,FALSE,3,11,NA,NA,NA,TRUE,40000 +82097,both interview and exam,male,6,NA,asian,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +82098,both interview and exam,male,64,NA,mexican 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exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82108,both interview and exam,male,61,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,NA,FALSE,50000 +82109,both interview and exam,male,19,NA,white,2,235,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,22500 +82110,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,7500 +82111,both interview and exam,male,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82112,both interview and exam,female,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +82113,both interview and exam,male,69,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +82114,both interview and exam,female,14,NA,black,1,174,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +82115,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,17500 +82116,both interview and exam,female,18,NA,mexican 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exam,male,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82136,both interview and exam,male,0,7,asian,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82137,both interview and exam,male,17,NA,mexican american,2,210,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +82138,both interview and exam,male,61,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82139,both interview and exam,female,39,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,NA +82140,both interview and exam,male,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +82141,both interview and exam,female,12,NA,asian,1,151,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +82142,both interview and exam,male,10,NA,white,1,122,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +82143,both interview and exam,male,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82144,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,7500 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exam,female,12,NA,white,2,146,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +82155,both interview and exam,female,3,NA,white,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +82156,interview only,female,10,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +82157,both interview and exam,male,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +82158,both interview and exam,male,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82159,both interview and exam,female,7,NA,black,2,90,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +82160,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,30000 +82161,both interview and exam,female,39,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +82162,both interview and exam,male,68,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82163,both interview and exam,female,51,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +82164,both interview and exam,male,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,7500 +82165,both interview and exam,male,44,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +82166,both interview and exam,male,6,NA,black,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,2500 +82167,both interview and exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82168,interview only,male,17,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +82169,both interview and exam,female,58,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,never_married,NA,FALSE,NA +82170,both interview and exam,female,62,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,25,NA,5,married,NA,TRUE,100000 +82171,both interview and exam,male,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +82172,both interview and exam,male,29,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +82173,both interview and exam,female,63,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82174,both interview and exam,male,10,NA,other,2,124,NA,NA,FALSE,FALSE,0.5,3,NA,NA,NA,TRUE,2500 +82175,both interview and exam,male,9,NA,white,1,115,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +82176,both interview and exam,male,57,NA,black,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,TRUE,70000 +82177,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +82178,both interview and exam,male,0,7,mexican american,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +82179,both interview and exam,female,16,NA,asian,1,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +82180,both interview and exam,male,4,NA,mexican american,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82181,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,70000 +82182,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 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exam,female,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +82212,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +82213,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82214,both interview and exam,female,9,NA,mexican american,2,115,NA,NA,FALSE,FALSE,3,3,NA,NA,NA,FALSE,30000 +82215,both interview and exam,female,9,NA,other,2,112,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +82216,both interview and exam,male,52,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +82217,interview only,male,23,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +82218,both interview and exam,female,15,NA,white,2,182,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,60000 +82219,both interview and exam,male,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,NA +82220,both interview and exam,female,9,NA,white,2,109,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,2500 +82221,both interview and exam,male,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82222,both interview and exam,male,3,NA,other hispanic,2,45,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,50000 +82223,both interview and exam,male,27,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,87500 +82224,both interview and exam,female,20,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,50000 +82225,both interview and exam,male,55,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +82226,both interview and exam,male,80,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +82227,both interview and exam,female,79,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82228,both interview and exam,male,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,60000 +82229,both interview and exam,male,16,NA,white,2,194,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +82230,both interview and exam,male,60,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,30000 +82231,both interview and exam,male,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +82232,both interview and exam,male,15,NA,mexican american,1,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,70000 +82233,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,17500 +82234,both interview and exam,male,1,13,other,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82235,both interview and exam,female,73,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +82236,both interview and exam,male,79,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +82237,both interview and exam,female,4,NA,black,1,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +82238,both interview and exam,female,66,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +82239,both interview and exam,male,10,NA,other hispanic,1,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 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exam,female,17,NA,black,2,208,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,70000 +82250,both interview and exam,male,19,NA,mexican american,2,230,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,60000 +82251,both interview and exam,male,10,NA,mexican american,2,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +82252,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,unable to ascertain,TRUE,30000 +82253,both interview and exam,female,19,NA,black,1,234,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,40000 +82254,both interview and exam,male,77,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +82255,both interview and exam,male,0,1,white,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +82256,both interview and exam,male,6,NA,white,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +82257,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,40000 +82258,both interview and exam,female,50,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,50000 +82259,both interview and exam,male,20,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,7500 +82260,both interview and exam,male,9,NA,white,2,120,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +82261,both interview and exam,male,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +82262,both interview and exam,female,1,13,mexican american,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +82263,both interview and exam,female,9,NA,black,1,117,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +82264,both interview and exam,male,5,NA,other hispanic,1,72,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +82265,both interview and exam,male,8,NA,white,2,98,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +82266,interview only,female,0,10,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82267,both interview and exam,female,6,NA,white,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +82268,both interview and exam,female,4,NA,white,1,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82269,both interview and exam,female,23,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,never_married,no,FALSE,NA +82270,both interview and exam,male,49,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,40000 +82271,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,30000 +82272,both interview and exam,female,0,2,mexican american,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82273,both interview and exam,female,1,23,white,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82274,both interview and exam,male,5,NA,other hispanic,2,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82275,both interview and exam,female,42,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,unable to ascertain,TRUE,30000 +82276,interview only,female,51,NA,other,NA,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +82277,both interview and exam,female,71,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +82278,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +82279,both interview and exam,female,13,NA,black,2,164,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,NA +82280,both interview and exam,male,6,NA,white,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82281,both interview and exam,female,41,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +82282,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,30000 +82283,both interview and exam,male,48,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,FALSE,NA +82284,both interview and exam,female,8,NA,white,2,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +82285,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +82286,both interview and exam,female,14,NA,white,1,178,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +82287,both interview and exam,female,19,NA,other hispanic,1,233,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,12500 +82288,both interview and exam,male,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +82289,both interview and exam,female,0,11,mexican american,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82290,both interview and exam,male,43,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,2,married,NA,TRUE,40000 +82291,both interview and exam,female,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82292,interview only,female,3,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82293,both interview and exam,female,4,NA,asian,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82294,both interview and exam,male,8,NA,asian,1,103,NA,NA,FALSE,FALSE,3,3,NA,NA,NA,TRUE,7500 +82295,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 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interview and exam,male,43,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,NA +82307,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +82308,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +82309,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,7500 +82310,both interview and exam,female,19,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +82311,both interview and exam,male,17,NA,black,1,209,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +82312,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,22500 +82313,both interview and exam,female,15,NA,black,1,192,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +82314,both interview and exam,male,13,NA,other hispanic,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,17500 +82315,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82316,both interview and exam,male,73,NA,mexican american,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +82317,both interview and exam,male,7,NA,mexican american,2,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,30000 +82318,both interview and exam,male,27,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,never_married,NA,TRUE,2500 +82319,both interview and exam,female,35,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +82320,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +82321,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82322,interview only,male,41,NA,other,NA,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +82323,both interview and exam,male,2,NA,black,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82324,both interview and exam,male,6,NA,other hispanic,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +82325,both interview and exam,male,39,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +82326,both interview and exam,male,10,NA,white,2,133,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +82327,both interview and exam,female,2,NA,black,1,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +82328,both interview and exam,male,2,NA,black,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +82329,both interview and exam,male,45,NA,white,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,NA,TRUE,100000 +82330,both interview and exam,female,51,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82331,both interview and exam,male,16,NA,asian,2,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,NA +82332,both interview and exam,male,0,1,asian,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82333,both interview and exam,female,10,NA,other hispanic,2,127,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,NA +82334,both interview and exam,female,50,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,7500 +82335,both interview and exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +82336,both interview and exam,male,28,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,NA +82337,both interview and exam,female,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,30000 +82338,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,30000 +82339,both interview and exam,male,0,10,mexican american,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +82340,both interview and exam,female,19,NA,asian,1,229,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +82341,both interview and exam,male,16,NA,black,2,199,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +82342,both interview and exam,female,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,50000 +82343,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82344,both interview and exam,male,70,NA,black,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,divorced,NA,TRUE,30000 +82345,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +82346,both interview and exam,female,51,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,separated,NA,TRUE,40000 +82347,both interview and exam,male,2,NA,mexican american,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82348,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,yes,TRUE,87500 +82349,both interview and exam,female,11,NA,white,2,137,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +82350,both interview and exam,female,7,NA,other hispanic,1,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +82351,both interview and exam,male,65,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,30000 +82352,both interview and exam,male,0,11,mexican american,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +82353,both interview and exam,male,53,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +82354,both interview and exam,female,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82355,both interview and exam,female,70,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +82356,both interview and exam,female,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82357,both interview and exam,female,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,30000 +82358,both interview and exam,male,13,NA,other,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,17500 +82359,both interview and exam,male,48,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +82360,both interview and exam,female,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +82361,both interview and exam,male,17,NA,mexican american,2,206,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +82362,both interview and exam,male,7,NA,other hispanic,1,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,17500 +82363,both interview and exam,male,38,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +82364,both interview and exam,female,0,9,white,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82365,both interview and exam,female,17,NA,black,1,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +82366,both interview and exam,female,6,NA,mexican american,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +82367,both interview and exam,male,35,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,NA,FALSE,2500 +82368,both interview and exam,female,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +82369,both interview and exam,female,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,no,TRUE,30000 +82370,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,2500 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exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82381,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,45,NA,2,widowed,NA,TRUE,NA +82382,both interview and exam,male,3,NA,black,2,37,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82383,both interview and exam,male,62,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,30000 +82384,both interview and exam,female,65,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82385,both interview and exam,male,2,NA,white,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82386,both interview and exam,female,2,NA,black,1,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82387,both interview and exam,female,0,4,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82388,both interview and exam,male,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +82389,both interview and exam,female,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,40000 +82390,both interview and exam,male,0,6,asian,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82391,both interview and exam,male,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +82392,both interview and exam,male,6,NA,black,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +82393,both interview and exam,male,20,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +82394,both interview and exam,male,18,NA,mexican american,2,216,FALSE,NA,FALSE,FALSE,12.5,14,NA,NA,NA,TRUE,NA +82395,both interview and exam,female,25,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,50000 +82396,both interview and exam,male,19,NA,white,1,237,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,50000 +82397,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +82398,both interview and exam,male,31,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +82399,both interview and exam,male,2,NA,other,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82400,both interview and exam,male,16,NA,black,2,197,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +82401,both interview and exam,female,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +82402,both interview and exam,male,65,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,87500 +82403,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82404,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,22500 +82405,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +82406,both interview and exam,male,73,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,NA,never_married,NA,TRUE,12500 +82407,both interview and exam,male,44,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +82408,both interview and exam,male,18,NA,white,2,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 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exam,male,16,NA,white,2,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,50000 +82419,both interview and exam,female,1,23,asian,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82420,both interview and exam,male,35,NA,black,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,TRUE,40000 +82421,both interview and exam,female,13,NA,asian,1,164,NA,NA,FALSE,TRUE,12.5,7,NA,NA,NA,TRUE,100000 +82422,both interview and exam,female,10,NA,asian,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +82423,both interview and exam,male,56,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82424,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,7500 +82425,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,50000 +82426,both interview and exam,male,24,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +82427,both interview and exam,male,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,70000 +82428,both interview and exam,female,26,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,40000 +82429,both interview and exam,male,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82430,both interview and exam,female,24,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,40000 +82431,interview only,female,0,8,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +82432,both interview and exam,male,60,NA,black,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,TRUE,NA +82433,both interview and exam,male,1,16,black,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82434,both interview and exam,female,70,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,NA +82435,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +82436,both interview and exam,male,61,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,married,NA,FALSE,87500 +82437,both interview and exam,female,1,12,other hispanic,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +82438,both interview and exam,male,7,NA,black,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +82439,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82440,both interview and exam,female,63,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82441,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,87500 +82442,both interview and exam,female,0,7,mexican american,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82443,both interview and exam,male,11,NA,black,1,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,7500 +82444,both interview and exam,male,2,NA,black,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82445,both interview and exam,female,52,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82446,both interview and exam,male,66,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +82447,both interview and exam,female,15,NA,other,1,192,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +82448,both interview and exam,male,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +82449,both interview and exam,male,42,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,12500 +82450,both interview and exam,female,34,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,no,FALSE,7500 +82451,both interview and exam,female,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,17500 +82452,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,87500 +82453,both interview and exam,female,0,4,other,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82454,both interview and exam,female,37,NA,other,1,NA,FALSE,NA,FALSE,FALSE,3,NA,4,married,no,TRUE,30000 +82455,both interview and exam,female,25,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,NA +82456,both interview and exam,female,0,6,black,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82457,both interview and exam,male,10,NA,mexican american,1,130,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,17500 +82458,both interview and exam,female,3,NA,other,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82459,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +82460,both interview and exam,female,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,NA +82461,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +82462,both interview and exam,male,36,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,30000 +82463,both interview and exam,female,48,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +82464,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,50000 +82465,both interview and exam,female,44,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,living_with_partner,no,TRUE,12500 +82466,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,70000 +82467,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,30000 +82468,both interview and exam,male,11,NA,other,2,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,70000 +82469,both interview and exam,male,1,18,asian,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82470,both interview and exam,male,13,NA,black,1,158,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +82471,interview only,female,22,NA,other hispanic,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,unable to ascertain,TRUE,12500 +82472,both interview and exam,male,13,NA,white,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +82473,interview only,female,8,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 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exam,male,32,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,60000 +82484,both interview and exam,male,14,NA,black,1,174,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +82485,both interview and exam,female,33,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,TRUE,40000 +82486,both interview and exam,male,40,NA,other,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,TRUE,30000 +82487,both interview and exam,male,21,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +82488,both interview and exam,male,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82489,both interview and exam,male,41,NA,asian,2,NA,TRUE,TRUE,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +82490,interview only,male,0,1,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82491,both interview and exam,male,14,NA,black,1,171,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +82492,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +82493,both interview and exam,female,9,NA,white,2,120,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +82494,both interview and exam,female,19,NA,mexican american,1,236,FALSE,NA,FALSE,FALSE,NA,13,NA,NA,NA,TRUE,NA +82495,both interview and exam,female,51,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +82496,both interview and exam,male,8,NA,mexican american,1,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +82497,both interview and exam,female,11,NA,mexican american,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +82498,both interview and exam,male,18,NA,mexican american,1,227,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,FALSE,NA +82499,both interview and exam,male,12,NA,black,2,152,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +82500,both interview and exam,male,38,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +82501,both interview and exam,female,38,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,married,no,TRUE,100000 +82502,both interview and exam,female,16,NA,white,2,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +82503,both interview and exam,female,16,NA,black,1,193,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +82504,both interview and exam,male,73,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,3,separated,NA,FALSE,7500 +82505,both interview and exam,male,8,NA,white,1,103,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +82506,both interview and exam,female,1,17,mexican american,1,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82507,both interview and exam,male,72,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +82508,both interview and exam,male,5,NA,black,1,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82509,both interview and exam,male,63,NA,mexican american,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +82510,both interview and exam,male,0,11,white,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82511,both interview and exam,female,9,NA,other,1,109,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +82512,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +82513,both interview and exam,male,47,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +82514,both interview and exam,female,4,NA,asian,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82515,both interview and exam,male,11,NA,asian,2,144,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +82516,both interview and exam,male,11,NA,mexican american,1,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,2500 +82517,both interview and exam,male,59,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,50000 +82518,both interview and exam,male,13,NA,mexican american,1,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,70000 +82519,both interview and exam,female,25,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,30000 +82520,both interview and exam,female,16,NA,mexican american,1,201,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,70000 +82521,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +82522,both interview and exam,male,15,NA,other hispanic,2,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,50000 +82523,both interview and exam,female,7,NA,other hispanic,2,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +82524,both interview and exam,female,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +82525,both interview and exam,male,6,NA,other,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +82526,both interview and exam,female,2,NA,mexican american,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82527,both interview and exam,female,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +82528,both interview and exam,male,15,NA,other hispanic,2,191,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +82529,both interview and exam,female,35,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,separated,no,TRUE,60000 +82530,both interview and exam,female,4,NA,asian,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82531,both interview and exam,female,36,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,no,FALSE,NA +82532,both interview and exam,male,16,NA,asian,1,194,NA,NA,FALSE,FALSE,0.5,9,NA,NA,NA,TRUE,17500 +82533,both interview and exam,female,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,NA +82534,both interview and exam,male,18,NA,mexican american,1,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,40000 +82535,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +82536,both interview and exam,female,49,NA,other,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +82537,interview only,female,25,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,unable to ascertain,TRUE,12500 +82538,both interview and exam,female,26,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,30000 +82539,both interview and exam,female,1,18,asian,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82540,both interview and exam,male,20,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,TRUE,22500 +82541,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +82542,both interview and exam,male,66,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,FALSE,22500 +82543,both interview and exam,female,12,NA,other,2,147,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +82544,both interview and exam,male,9,NA,mexican american,2,117,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,22500 +82545,both interview and exam,male,8,NA,other hispanic,2,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +82546,both interview and exam,male,4,NA,white,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +82547,both interview and exam,female,65,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,NA +82548,both interview and exam,female,0,7,white,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82549,both interview and exam,male,8,NA,mexican american,2,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +82550,both interview and exam,female,34,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +82551,both interview and exam,female,2,NA,black,2,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +82552,both interview and exam,female,2,NA,mexican american,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82553,both interview and exam,male,0,10,white,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82554,both interview and exam,female,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,100000 +82555,both interview and exam,female,1,18,white,1,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +82556,both interview and exam,female,4,NA,mexican american,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 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exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +82567,both interview and exam,male,25,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,60000 +82568,both interview and exam,male,3,NA,asian,2,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82569,both interview and exam,male,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,7500 +82570,both interview and exam,male,80,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +82571,interview only,male,46,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82572,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +82573,both interview and exam,female,7,NA,other hispanic,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82574,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,40000 +82575,both interview and exam,male,4,NA,other,2,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82576,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +82577,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +82578,both interview and exam,female,11,NA,white,2,133,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +82579,both interview and exam,female,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +82580,both interview and exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +82581,both interview and exam,male,17,NA,other hispanic,2,216,FALSE,NA,FALSE,TRUE,3,13,NA,NA,NA,TRUE,40000 +82582,both interview and exam,male,71,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,1,married,NA,TRUE,12500 +82583,both interview and exam,female,6,NA,white,2,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82584,interview only,male,0,2,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 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exam,female,3,NA,white,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82595,both interview and exam,male,18,NA,white,2,225,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,7500 +82596,both interview and exam,male,73,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,widowed,NA,FALSE,70000 +82597,both interview and exam,male,56,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,100000 +82598,both interview and exam,male,0,4,white,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82599,both interview and exam,male,2,NA,white,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +82600,both interview and exam,male,12,NA,black,2,148,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +82601,both interview and exam,male,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,17500 +82602,both interview and exam,male,6,NA,other,2,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +82603,both interview and exam,female,44,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,no,TRUE,100000 +82604,both interview and exam,male,49,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,NA +82605,both interview and exam,female,46,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +82606,both interview and exam,male,10,NA,mexican american,1,130,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,22500 +82607,both interview and exam,male,3,NA,other hispanic,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,87500 +82608,both interview and exam,male,78,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,living_with_partner,NA,TRUE,NA +82609,both interview and exam,female,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +82610,both interview and exam,male,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82611,both interview and exam,male,33,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,never_married,NA,TRUE,100000 +82612,both interview and exam,female,64,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,living_with_partner,NA,FALSE,12500 +82613,both interview and exam,male,19,NA,black,2,233,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +82614,both interview and exam,female,14,NA,asian,1,173,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +82615,both interview and exam,male,57,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82616,both interview and exam,male,63,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,12500 +82617,both interview and exam,female,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,70000 +82618,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +82619,both interview and exam,male,69,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +82620,both interview and exam,male,3,NA,white,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +82621,both interview and exam,male,41,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,100000 +82622,both interview and exam,female,5,NA,white,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 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exam,male,78,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +82652,both interview and exam,male,73,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,87500 +82653,both interview and exam,male,7,NA,white,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +82654,both interview and exam,female,18,NA,other hispanic,1,219,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +82655,both interview and exam,female,75,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,widowed,NA,TRUE,50000 +82656,both interview and exam,male,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +82657,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +82658,both interview and exam,male,6,NA,black,1,80,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,17500 +82659,both interview and exam,female,0,6,black,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82660,both interview and exam,female,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +82661,both interview and exam,female,6,NA,asian,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +82662,interview only,female,13,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +82663,both interview and exam,female,0,4,black,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82664,both interview and exam,male,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +82665,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,22500 +82666,both interview and exam,male,47,NA,black,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,NA,TRUE,NA +82667,both interview and exam,male,5,NA,asian,2,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +82668,both interview and exam,male,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,NA +82669,both interview and exam,female,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +82670,both interview and exam,male,18,NA,mexican american,2,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,17500 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exam,male,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +82681,both interview and exam,male,1,17,black,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82682,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,widowed,NA,TRUE,100000 +82683,interview only,male,9,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +82684,both interview and exam,female,42,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,40000 +82685,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,divorced,NA,TRUE,40000 +82686,both interview and exam,male,10,NA,other hispanic,2,121,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,2500 +82687,both interview and exam,female,5,NA,black,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82688,both interview and exam,male,63,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,35,NA,5,widowed,NA,TRUE,NA +82689,both interview and exam,female,0,1,white,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82690,both interview and exam,male,6,NA,white,1,72,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82691,both interview and exam,male,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,NA +82692,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,7500 +82693,both interview and exam,male,6,NA,mexican american,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +82694,both interview and exam,female,8,NA,mexican american,2,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +82695,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +82696,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,12500 +82697,both interview and exam,female,18,NA,asian,1,227,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +82698,both interview and exam,male,74,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +82699,both interview and exam,male,7,NA,other,1,95,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +82700,both interview and exam,male,4,NA,asian,2,52,NA,NA,FALSE,NA,3,NA,NA,NA,NA,TRUE,87500 +82701,both interview and exam,female,14,NA,white,2,179,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,2500 +82702,both interview and exam,female,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,50000 +82703,both interview and exam,male,50,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,living_with_partner,NA,TRUE,50000 +82704,both interview and exam,male,41,NA,white,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,100000 +82705,both interview and exam,female,76,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82706,both interview and exam,female,9,NA,white,1,113,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +82707,interview only,male,73,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +82708,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 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exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +82719,both interview and exam,female,35,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +82720,both interview and exam,male,58,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,50000 +82721,both interview and exam,male,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82722,both interview and exam,male,6,NA,mexican american,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +82723,both interview and exam,female,74,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +82724,both interview and exam,female,28,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +82725,both interview and exam,female,17,NA,asian,1,208,FALSE,NA,FALSE,TRUE,3,11,NA,NA,NA,TRUE,7500 +82726,both interview and exam,female,16,NA,black,1,197,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +82727,both interview and exam,male,77,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82728,both interview and exam,female,18,NA,mexican american,2,218,FALSE,NA,FALSE,FALSE,17.5,11,NA,NA,NA,TRUE,NA +82729,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,17500 +82730,both interview and exam,female,14,NA,asian,1,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +82731,both interview and exam,female,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,40000 +82732,both interview and exam,male,9,NA,white,2,116,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +82733,both interview and exam,female,40,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +82734,interview only,male,29,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +82735,both interview and exam,female,23,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,living_with_partner,no,TRUE,40000 +82736,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +82737,both interview and exam,female,66,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +82738,both interview and exam,male,3,NA,black,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +82739,both interview and exam,female,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +82740,both interview and exam,male,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,40000 +82741,both interview and exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,7500 +82742,both interview and exam,female,52,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,divorced,NA,TRUE,100000 +82743,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,NA +82744,both interview and exam,male,0,0,black,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82745,both interview and 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interview and exam,female,76,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +82880,both interview and exam,female,6,NA,other hispanic,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +82881,both interview and exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82882,both interview and exam,female,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,widowed,NA,TRUE,NA +82883,both interview and exam,female,1,17,asian,2,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82884,both interview and exam,male,18,NA,white,1,228,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +82885,both interview and exam,male,10,NA,black,1,131,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +82886,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +82887,both interview and exam,female,7,NA,black,1,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +82888,both interview and exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +82889,both interview and exam,male,66,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +82890,both interview and exam,female,2,NA,mexican american,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82891,both interview and exam,male,11,NA,other hispanic,1,137,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +82892,both interview and exam,male,0,9,mexican american,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82893,both interview and exam,female,15,NA,white,2,189,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +82894,both interview and exam,male,49,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,NA +82895,both interview and exam,female,57,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,100000 +82896,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +82897,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,17500 +82898,both interview and exam,male,66,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,TRUE,30000 +82899,both interview and exam,male,66,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,3,married,NA,TRUE,NA +82900,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82901,both interview and exam,male,68,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,living_with_partner,NA,FALSE,12500 +82902,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,FALSE,TRUE,0.5,NA,5,married,no,TRUE,100000 +82903,both interview and exam,female,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,50000 +82904,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82905,both interview and exam,male,7,NA,mexican american,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +82906,both interview 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exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +82917,both interview and exam,male,42,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,100000 +82918,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,22500 +82919,both interview and exam,male,6,NA,white,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +82920,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +82921,both interview and exam,male,9,NA,other hispanic,1,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,30000 +82922,both interview and exam,male,1,16,other,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82923,both interview and exam,male,6,NA,white,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +82924,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +82925,both interview and exam,male,38,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 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exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +82946,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +82947,both interview and exam,female,0,4,white,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82948,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +82949,both interview and exam,male,67,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +82950,interview only,female,2,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82951,both interview and exam,female,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +82952,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82953,both interview and exam,male,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82954,interview only,male,4,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82955,interview 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exam,male,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +82965,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,no,FALSE,50000 +82966,both interview and exam,male,1,20,black,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +82967,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +82968,both interview and exam,female,79,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,17500 +82969,both interview and exam,male,54,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +82970,both interview and exam,male,60,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,2500 +82971,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,70000 +82972,both interview and exam,female,1,16,asian,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82973,both interview and 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exam,female,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,50000 +83020,both interview and exam,male,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +83021,both interview and exam,female,15,NA,mexican american,1,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,30000 +83022,both interview and exam,male,10,NA,white,2,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +83023,interview only,male,19,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,17500 +83024,both interview and exam,female,13,NA,other hispanic,2,161,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +83025,both interview and exam,female,15,NA,black,2,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,60000 +83026,both interview and exam,male,76,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,widowed,NA,TRUE,100000 +83027,both interview and exam,female,50,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +83028,both interview and exam,male,7,NA,other,2,91,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,17500 +83029,both interview and exam,male,8,NA,white,1,99,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +83030,both interview and exam,male,7,NA,black,2,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,70000 +83031,both interview and exam,male,49,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,87500 +83032,both interview and exam,male,8,NA,black,2,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,70000 +83033,both interview and exam,female,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +83034,interview only,male,10,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,17500 +83035,both interview and exam,male,9,NA,other hispanic,2,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +83036,both interview and exam,female,17,NA,mexican american,2,209,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +83037,both interview and exam,female,66,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +83038,both interview and exam,male,12,NA,white,2,156,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 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exam,male,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,100000 +83049,both interview and exam,male,4,NA,other hispanic,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +83050,both interview and exam,female,46,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,FALSE,50000 +83051,both interview and exam,male,13,NA,black,1,166,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +83052,both interview and exam,male,76,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +83053,both interview and exam,female,11,NA,white,2,142,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +83054,both interview and exam,male,12,NA,white,2,156,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +83055,both interview and exam,female,10,NA,black,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +83056,both interview and exam,female,16,NA,mexican american,2,205,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,NA +83057,both interview and exam,male,6,NA,other hispanic,2,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 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exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +83068,both interview and exam,female,59,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +83069,both interview and exam,female,25,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,no,TRUE,60000 +83070,both interview and exam,female,71,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,widowed,NA,TRUE,100000 +83071,both interview and exam,female,10,NA,white,1,125,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +83072,both interview and exam,female,7,NA,other hispanic,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,30000 +83073,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +83074,both interview and exam,female,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,70000 +83075,both interview and exam,female,77,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,widowed,NA,TRUE,100000 +83076,both interview and exam,female,13,NA,mexican 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exam,male,18,NA,asian,1,226,FALSE,NA,FALSE,TRUE,0.5,13,NA,NA,NA,TRUE,2500 +83086,both interview and exam,male,1,18,mexican american,2,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +83087,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +83088,both interview and exam,female,78,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +83089,both interview and exam,female,0,2,asian,2,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +83090,both interview and exam,male,4,NA,white,1,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +83091,both interview and exam,female,6,NA,black,1,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +83092,both interview and exam,male,57,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,3,married,NA,TRUE,100000 +83093,both interview and exam,male,16,NA,mexican american,1,203,NA,NA,FALSE,FALSE,7.5,10,NA,NA,NA,TRUE,22500 +83094,both interview and exam,male,43,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,100000 +83095,both interview and exam,male,0,10,white,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +83096,both interview and exam,female,23,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,NA +83097,both interview and exam,male,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +83098,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +83099,both interview and exam,male,32,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,TRUE,NA +83100,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,22500 +83101,both interview and exam,female,21,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +83102,both interview and exam,male,11,NA,mexican american,2,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +83103,both interview and exam,female,32,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,no,TRUE,50000 +83104,both interview and exam,male,59,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,100000 +83105,both interview and exam,male,4,NA,other hispanic,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +83106,both interview and exam,male,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +83107,both interview and exam,male,1,20,other hispanic,1,21,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +83108,both interview and exam,female,49,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,NA +83109,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,FALSE,TRUE,55,NA,5,never_married,NA,TRUE,22500 +83110,both interview and exam,male,34,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +83111,both interview and exam,female,64,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,TRUE,60000 +83112,both interview and exam,female,0,1,mexican 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exam,female,30,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,no,TRUE,100000 +83132,both interview and exam,female,0,7,asian,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +83133,both interview and exam,female,10,NA,black,1,123,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +83134,both interview and exam,female,13,NA,white,1,162,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,2500 +83135,both interview and exam,female,2,NA,mexican american,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +83136,both interview and exam,male,31,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +83137,interview only,male,80,NA,white,NA,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +83138,both interview and exam,male,54,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +83139,both interview and exam,male,16,NA,white,1,192,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +83140,both interview and exam,female,44,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,0.5,NA,1,married,no,TRUE,2500 +83141,both interview and exam,male,7,NA,black,1,84,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +83142,both interview and exam,female,79,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +83143,both interview and exam,male,71,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +83144,both interview and exam,female,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +83145,both interview and exam,male,16,NA,white,2,204,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +83146,both interview and exam,male,67,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,2,married,NA,FALSE,30000 +83147,both interview and exam,male,73,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +83148,both interview and exam,male,54,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,2500 +83149,both interview and exam,male,5,NA,other hispanic,1,63,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +83150,both interview and exam,female,43,NA,other 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exam,male,47,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,7500 +83160,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +83161,both interview and exam,female,2,NA,asian,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +83162,both interview and exam,female,19,NA,white,2,234,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +83163,both interview and exam,male,57,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,NA +83164,both interview and exam,male,8,NA,white,1,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +83165,both interview and exam,female,47,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,separated,NA,TRUE,50000 +83166,both interview and exam,female,6,NA,other,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +83167,both interview and exam,female,2,NA,black,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +83168,both interview and exam,male,8,NA,asian,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +83169,both interview and exam,female,5,NA,other,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +83170,both interview and exam,female,68,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,7500 +83171,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +83172,both interview and exam,male,23,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +83173,both interview and exam,female,16,NA,asian,1,198,NA,NA,FALSE,FALSE,7.5,10,NA,NA,NA,TRUE,87500 +83174,both interview and exam,female,44,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,no,TRUE,100000 +83175,both interview and exam,female,0,9,mexican american,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +83176,both interview and exam,female,9,NA,black,1,112,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +83177,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +83178,both interview and exam,male,5,NA,asian,1,63,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +83179,both interview and exam,male,64,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +83180,both interview and exam,male,30,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,divorced,NA,TRUE,50000 +83181,both interview and exam,male,18,NA,asian,2,217,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,60000 +83182,both interview and exam,female,45,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +83183,both interview and exam,male,76,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +83184,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,12500 +83185,both interview and exam,female,17,NA,white,1,205,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +83186,both interview and exam,female,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +83187,both interview and exam,male,65,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +83188,both interview and exam,male,18,NA,white,1,225,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +83189,both interview and exam,male,1,21,mexican american,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +83190,both interview and exam,male,66,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,100000 +83191,both interview and exam,female,62,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,1,divorced,NA,TRUE,70000 +83192,both interview and exam,male,57,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,30000 +83193,both interview and exam,female,80,NA,other,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,widowed,NA,TRUE,12500 +83194,both interview and exam,female,3,NA,other hispanic,1,37,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +83195,both interview and exam,male,7,NA,asian,1,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +83196,both interview and exam,female,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,7500 +83197,both interview and exam,female,25,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,no,FALSE,22500 +83198,both interview and exam,male,1,17,white,2,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +83199,both interview and exam,female,9,NA,white,2,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +83200,both interview and exam,male,12,NA,mexican american,2,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,100000 +83201,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +83202,both interview and exam,male,73,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +83203,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +83204,both interview and exam,male,11,NA,white,2,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +83205,both interview and exam,male,4,NA,black,1,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 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exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,17500 +83216,both interview and exam,female,4,NA,mexican american,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +83217,both interview and exam,male,5,NA,black,2,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +83218,both interview and exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,17500 +83219,both interview and exam,female,8,NA,asian,2,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +83220,both interview and exam,male,23,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,NA +83221,both interview and exam,male,4,NA,white,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +83222,both interview and exam,female,51,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,divorced,NA,TRUE,40000 +83223,both interview and exam,male,6,NA,black,1,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +83224,both interview and exam,male,1,13,mexican 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exam,female,6,NA,white,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +83244,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +83245,both interview and exam,female,6,NA,white,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +83246,both interview and exam,female,17,NA,asian,1,206,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,NA +83247,both interview and exam,female,5,NA,black,1,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +83248,both interview and exam,female,35,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,never_married,no,FALSE,NA +83249,both interview and exam,female,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +83250,both interview and exam,male,66,NA,other,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,30000 +83251,both interview and exam,female,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,unable to ascertain,TRUE,NA +83252,both interview and exam,female,41,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,2500 +83253,both interview and exam,female,55,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +83254,interview only,male,47,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,60000 +83255,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,50000 +83256,both interview and exam,female,19,NA,white,1,234,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +83257,both interview and exam,female,9,NA,mexican american,1,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +83258,both interview and exam,female,33,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,NA +83259,both interview and exam,male,15,NA,black,1,185,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,17500 +83260,both interview and exam,female,24,NA,other,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,no,TRUE,30000 +83261,both interview and exam,female,63,NA,mexican 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exam,male,18,NA,asian,1,224,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,12500 +83271,both interview and exam,male,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,87500 +83272,both interview and exam,female,65,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,separated,NA,FALSE,12500 +83273,both interview and exam,female,10,NA,other,2,122,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +83274,both interview and exam,female,10,NA,black,2,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +83275,both interview and exam,male,17,NA,mexican american,1,210,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +83276,both interview and exam,male,35,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +83277,both interview and exam,male,51,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,NA +83278,both interview and exam,female,38,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +83279,both interview and exam,female,75,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +83280,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +83281,both interview and exam,male,5,NA,black,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +83282,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +83283,both interview and exam,female,1,16,black,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +83284,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +83285,both interview and exam,male,29,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +83286,both interview and exam,female,24,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +83287,both interview and exam,female,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,2500 +83288,both interview and exam,female,9,NA,asian,1,116,NA,NA,FALSE,TRUE,7.5,3,NA,NA,NA,TRUE,87500 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exam,female,6,NA,other hispanic,1,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +83299,both interview and exam,male,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +83300,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +83301,both interview and exam,female,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +83302,both interview and exam,male,1,23,black,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +83303,both interview and exam,male,10,NA,mexican american,2,130,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +83304,both interview and exam,male,0,6,mexican american,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,40000 +83305,both interview and exam,female,53,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +83306,both interview and exam,female,9,NA,other hispanic,2,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +83307,both interview and exam,female,10,NA,white,1,124,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,60000 +83308,both interview and exam,female,0,9,black,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +83309,both interview and exam,female,42,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,no,TRUE,70000 +83310,both interview and exam,female,4,NA,black,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +83311,both interview and exam,male,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +83312,both interview and exam,female,0,6,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +83313,both interview and exam,female,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +83314,both interview and exam,male,54,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +83315,both interview and exam,female,0,0,white,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +83316,both interview and exam,female,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,30000 +83317,both interview and exam,female,5,NA,asian,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +83318,both interview and exam,male,15,NA,mexican american,1,185,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +83319,both interview and exam,male,15,NA,asian,1,192,NA,NA,FALSE,FALSE,0.5,9,NA,NA,NA,TRUE,2500 +83320,both interview and exam,male,63,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,17500 +83321,both interview and exam,female,80,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,7500 +83322,both interview and exam,male,0,5,black,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +83323,both interview and exam,male,68,NA,black,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,TRUE,NA +83324,both interview and exam,male,0,8,black,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +83325,both interview and exam,female,13,NA,white,2,165,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +83326,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 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exam,female,32,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,no,FALSE,40000 +83337,both interview and exam,male,0,4,black,1,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +83338,both interview and exam,male,52,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +83339,both interview and exam,male,12,NA,other hispanic,2,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,50000 +83340,both interview and exam,male,6,NA,white,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +83341,both interview and exam,female,68,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,30000 +83342,both interview and exam,male,6,NA,white,2,85,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +83343,interview only,male,11,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,30000 +83344,both interview and exam,male,15,NA,asian,2,181,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +83345,both interview and exam,male,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +83346,both interview and exam,male,4,NA,white,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +83347,both interview and exam,female,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +83348,both interview and exam,male,15,NA,other hispanic,2,183,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,40000 +83349,both interview and exam,female,18,NA,black,1,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,40000 +83350,both interview and exam,male,15,NA,mexican american,1,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +83351,both interview and exam,male,63,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +83352,both interview and exam,male,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +83353,both interview and exam,female,0,9,other,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +83354,both interview and exam,female,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +83355,both interview and exam,male,15,NA,black,1,184,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,87500 +83356,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,17500 +83357,both interview and exam,male,10,NA,black,1,133,NA,NA,FALSE,FALSE,3,3,NA,NA,NA,TRUE,30000 +83358,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +83359,both interview and exam,female,60,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,NA +83360,both interview and exam,male,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +83361,interview only,male,31,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +83362,both interview and exam,female,31,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,no,TRUE,50000 +83363,both interview and exam,male,28,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +83364,both interview and exam,male,46,NA,mexican 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exam,male,15,NA,black,1,186,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +83374,both interview and exam,male,61,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +83375,both interview and exam,male,70,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,FALSE,100000 +83376,both interview and exam,female,43,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +83377,both interview and exam,female,11,NA,white,1,134,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +83378,both interview and exam,male,1,20,mexican american,1,21,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +83379,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,7500 +83380,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +83381,both interview and exam,male,59,NA,other,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +83382,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +83383,both interview and exam,female,12,NA,white,1,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +83384,both interview and exam,male,9,NA,white,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +83385,both interview and exam,female,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,7500 +83386,interview only,male,34,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +83387,interview only,male,48,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,NA,never_married,NA,TRUE,17500 +83388,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +83389,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,70000 +83390,both interview and exam,male,71,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +83391,both interview and exam,female,56,NA,mexican 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exam,male,2,NA,black,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +83420,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,70000 +83421,both interview and exam,female,2,NA,white,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +83422,both interview and exam,male,1,13,black,2,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +83423,both interview and exam,male,66,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,FALSE,100000 +83424,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +83425,both interview and exam,female,34,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,yes,TRUE,100000 +83426,both interview and exam,female,56,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +83427,both interview and exam,female,27,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +83428,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,30000 +83429,both interview and exam,female,61,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,married,NA,FALSE,30000 +83430,both interview and exam,female,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +83431,both interview and exam,female,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +83432,both interview and exam,male,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +83433,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +83434,both interview and exam,female,1,23,other hispanic,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +83435,both interview and exam,female,8,NA,black,2,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,7500 +83436,both interview and exam,male,76,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,60000 +83437,both interview and exam,female,49,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +83438,both interview and exam,male,57,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +83439,both interview and exam,male,30,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,never_married,NA,TRUE,NA +83440,both interview and exam,female,13,NA,asian,1,160,NA,NA,FALSE,FALSE,3,7,NA,NA,NA,TRUE,60000 +83441,both interview and exam,male,62,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,60000 +83442,both interview and exam,female,0,3,black,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +83443,both interview and exam,male,0,10,black,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +83444,both interview and exam,male,5,NA,other,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +83445,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,7500 +83446,both interview and exam,male,68,NA,black,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,1,living_with_partner,NA,TRUE,2500 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exam,female,65,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +83457,both interview and exam,female,13,NA,asian,2,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +83458,both interview and exam,female,11,NA,white,2,141,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +83459,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,living_with_partner,no,TRUE,2500 +83460,both interview and exam,male,79,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +83461,both interview and exam,female,42,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +83462,both interview and exam,male,2,NA,white,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +83463,both interview and exam,male,10,NA,white,1,121,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,60000 +83464,both interview and exam,female,75,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,NA +83465,both interview and 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exam,female,8,NA,mexican american,1,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +83503,both interview and exam,male,24,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,30000 +83504,both interview and exam,female,2,NA,asian,1,34,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,50000 +83505,both interview and exam,female,70,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,30000 +83506,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +83507,both interview and exam,male,50,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,NA,FALSE,30000 +83508,both interview and exam,male,0,2,other,1,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +83509,both interview and exam,male,5,NA,other hispanic,2,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +83510,both interview and exam,male,54,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +83511,both interview and exam,female,68,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +83512,both interview and exam,male,9,NA,mexican american,1,117,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +83513,both interview and exam,male,1,17,black,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +83514,both interview and exam,female,53,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,FALSE,NA +83515,both interview and exam,male,3,NA,asian,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +83516,both interview and exam,female,66,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,separated,NA,TRUE,7500 +83517,both interview and exam,female,17,NA,asian,1,205,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +83518,both interview and exam,female,33,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +83519,both interview and exam,male,19,NA,white,1,239,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,17500 +83520,both interview and exam,female,49,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,divorced,NA,FALSE,22500 +83521,both interview and exam,female,6,NA,white,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +83522,both interview and exam,female,35,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,no,TRUE,60000 +83523,both interview and exam,female,17,NA,white,2,211,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +83524,both interview and exam,female,55,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +83525,both interview and exam,male,33,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,70000 +83526,both interview and exam,male,58,NA,mexican american,2,NA,TRUE,TRUE,FALSE,TRUE,45,NA,3,married,NA,TRUE,50000 +83527,both interview and exam,male,18,NA,other hispanic,1,218,FALSE,NA,FALSE,TRUE,7.5,14,NA,NA,NA,TRUE,7500 +83528,both interview and exam,male,69,NA,black,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,divorced,NA,TRUE,17500 +83529,both interview and exam,female,59,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,TRUE,100000 +83530,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +83531,both interview and exam,male,15,NA,black,1,184,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +83532,both interview and exam,female,17,NA,mexican american,2,208,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +83533,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +83534,both interview and exam,male,2,NA,mexican american,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +83535,both interview and exam,male,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +83536,both interview and exam,female,20,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +83537,both interview and exam,male,0,1,white,1,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +83538,both interview and exam,male,0,10,black,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +83539,both interview and exam,female,73,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,never_married,NA,TRUE,40000 +83540,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +83541,both interview and exam,male,44,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,NA,FALSE,22500 +83542,both interview and exam,female,71,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,40000 +83543,both interview and exam,male,71,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +83544,both interview and exam,male,68,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,divorced,NA,TRUE,17500 +83545,both interview and exam,female,7,NA,black,2,93,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +83546,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +83547,both interview and exam,male,7,NA,white,2,85,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +83548,both interview and exam,male,10,NA,white,2,122,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +83549,interview only,male,28,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +83550,both interview and exam,male,8,NA,white,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +83551,interview only,male,28,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,never_married,NA,TRUE,NA +83552,both interview and exam,male,60,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,22500 +83553,both interview and exam,male,71,NA,other,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +83554,both interview and exam,male,49,NA,other,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,100000 +83555,both interview and exam,female,9,NA,black,2,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +83556,both interview and exam,female,55,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,NA,TRUE,NA +83557,both interview and exam,male,61,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +83558,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +83559,both interview and exam,male,14,NA,asian,1,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,NA +83560,both interview and exam,male,2,NA,white,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +83561,both interview and exam,male,14,NA,white,2,169,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +83562,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,12500 +83563,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +83564,both interview and exam,female,15,NA,mexican american,2,187,NA,NA,FALSE,FALSE,12.5,8,NA,NA,NA,FALSE,40000 +83565,both interview and exam,male,34,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +83566,both interview and exam,female,14,NA,white,1,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +83567,both interview and exam,male,68,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,30000 +83568,both interview and exam,female,32,NA,black,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,divorced,no,TRUE,40000 +83569,both interview and exam,male,53,NA,white,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,22500 +83570,both interview and exam,male,0,5,mexican american,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +83571,both interview and exam,male,5,NA,black,1,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +83572,both interview and exam,female,0,0,white,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +83573,both interview and exam,female,5,NA,white,1,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +83574,both interview and exam,male,19,NA,asian,1,239,FALSE,NA,FALSE,TRUE,3,13,NA,NA,NA,TRUE,87500 +83575,both interview and exam,male,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +83576,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,22500 +83577,both interview and exam,female,10,NA,white,2,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +83578,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,divorced,NA,TRUE,60000 +83579,both interview and exam,female,6,NA,black,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +83580,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,50000 +83581,both interview and exam,female,41,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,yes,TRUE,22500 +83582,both interview and exam,female,9,NA,mexican american,1,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,17500 +83583,both interview and exam,male,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +83584,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +83585,both interview and exam,male,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +83586,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +83587,both interview and exam,female,11,NA,black,2,143,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +83588,both interview and exam,male,10,NA,black,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +83589,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +83590,both interview and exam,male,77,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +83591,both interview and exam,female,16,NA,asian,2,195,NA,NA,FALSE,FALSE,17.5,10,NA,NA,NA,TRUE,100000 +83592,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +83593,interview only,female,44,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,unable to ascertain,TRUE,17500 +83594,both interview and exam,male,6,NA,white,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 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exam,male,60,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,married,NA,TRUE,100000 +83605,both interview and exam,male,68,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +83606,both interview and exam,male,7,NA,asian,2,93,NA,NA,FALSE,FALSE,0.5,1,NA,NA,NA,TRUE,100000 +83607,both interview and exam,female,4,NA,black,1,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +83608,both interview and exam,female,0,9,mexican american,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +83609,both interview and exam,female,10,NA,white,2,126,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +83610,both interview and exam,male,18,NA,white,2,222,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,22500 +83611,both interview and exam,female,2,NA,other hispanic,1,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +83612,both interview and exam,male,72,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +83613,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,87500 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exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +83624,both interview and exam,female,50,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +83625,both interview and exam,female,58,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,separated,NA,FALSE,17500 +83626,both interview and exam,male,8,NA,black,1,102,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +83627,both interview and exam,male,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,50000 +83628,both interview and exam,male,13,NA,white,2,161,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,12500 +83629,both interview and exam,male,7,NA,black,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +83630,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +83631,both interview and exam,female,9,NA,mexican american,1,119,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +83632,both interview and exam,male,47,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +83633,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +83634,both interview and exam,male,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +83635,interview only,female,17,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,2500 +83636,both interview and exam,male,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +83637,both interview and exam,male,40,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,87500 +83638,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +83639,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,50000 +83640,both interview and exam,female,79,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,widowed,NA,TRUE,40000 +83641,both interview and exam,female,15,NA,black,1,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +83642,both interview and exam,male,33,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +83643,both interview and exam,female,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,22500 +83644,both interview and exam,male,8,NA,mexican american,2,106,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,40000 +83645,both interview and exam,female,5,NA,other hispanic,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +83646,both interview and exam,male,56,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +83647,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,yes,TRUE,2500 +83648,both interview and exam,female,18,NA,white,2,219,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +83649,both interview and exam,male,6,NA,mexican american,2,83,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,100000 +83650,both interview and exam,female,67,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,widowed,NA,FALSE,87500 +83651,both interview and exam,male,10,NA,mexican american,2,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +83652,interview only,male,39,NA,asian,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +83653,both interview and exam,male,7,NA,other hispanic,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +83654,both interview and exam,male,8,NA,black,1,104,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +83655,both interview and exam,male,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +83656,both interview and exam,male,3,NA,other,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +83657,interview only,male,30,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,12500 +83658,both interview and exam,female,50,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +83659,both interview and exam,male,19,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,87500 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+--- +title: "Custom functions" +format: html +editor_options: + chunk_output_type: console +--- + +## A simple custom function + +In this notebook, you will learn how to define your own functions. + + +```{r} +# define a function called `add_one()` that adds 1 to its argument, x + +``` + +The code that is run when you "call" your function is inside the curly parentheses. + +```{r} +# apply function add_one() to 5 + +``` + +```{r} +# apply function add_one() to 5 using a *named argument* + +``` + + +What happens when the body of your function contains two pieces of code? + + +```{r} +# re-define add_one() with two lines of code: x - 1 and x + 1 + +``` + +```{r} +# apply add_one to 5 again + +``` + + +By default, any custom R function you create will automatically return the final result that is computed. + + + +For this reason, it is common to explicitly provide a "return statement". + +```{r} +# redefine add_one() but apply the return statement to x - 1 only + +``` + +```{r} +# apply add_one to 5 again + +``` + + + + + + + + + +## The general syntax of a custom function + +The general syntax of a custom function is shown below: + +```{r} +#| eval: false + +fn_name <- function(arg) { + # code involving arg + + return(object) +} +``` + + + + +## Exercise + +Write a function called "cube" that returns the cubic (`^3`) of the argument + +```{r} +# define function cube() + +``` + + +```{r} +# apply cube() to 3 + +``` + + + + + + +## Multiple arguments + +To create a function with multiple arguments, you need to provide two arguments inside the function definition, separated by a comma. The function below has two arguments: `x` and `y`: + +```{r} +# define a function called add_x2y that computes x + 2y + +``` + +When you call this `add_x2y()`, you can then specify a value for each argument, separated by a comma: + +```{r} +# apply add_x2y() to x = 2 and y = 5 + +``` + +When you have multiple arguments, funny things can start to happen when you don't name your arguments. + + + + + +What do you think will happen if you *first* provide a named argument for the *second* argument `y` by specifying `y = 2`, and then provide an unnamed argument afterwards? + +```{r} +#| error: true +add_x2y(y = 2, 5) +``` + + + + + + +R will be clever and it will first apply the named arguments by assigning `y` to the value 2, and then fill in the remaining argument, so `x` will be assigned to the value `5`. + +It is good practice to name your arguments if there is any chance for ambiguity. + +```{r} +# run add_x2y() with named arguments x = 2 and y = 5 + +``` + + + +Note that when you provide named arguments, it technically doesn't matter which order you provide them in (but this is *not* true when you don't provide named arguments!) + +```{r} +# run add_x2y() with named arguments y = 5 and x = 2 + +``` + + + + + + + + +Again, note that even when you provide named arguments in a function call (e.g., in `add_x2y(x = 2, y = 5)`), you are *not* defining a global version of the arguments, i.e., there is no `y` defined: + +```{r} +#| error: true + + +``` + + + + + + + +What do you think will happen when you call `add_x2y` without any parentheses? + +```{r} +# run add_x2y + +``` + +It will print out the definition of the function! + + + + +What do you think will happen when you call `add_x2y` with parentheses but no arguments? + +```{r} +#| error: true +# run add_x2y() + +``` + + + +You get an error! We can fix this by providing "default" values for the arguments. + + + + + + + + + + + +### Default values + +To provide *default* values for your arguments, you can assign the argument inside the function definition. In the example below, both `x` and `y` are given the default values of 1. + +```{r} +# redefine add_x2y() with default values for x and y (both 1) + +``` + + +```{r} +# call add_x2y() without any arguments + +``` + + +What happens if we only provide some of the arguments? + +```{r} +# run add_x2y() with a single unnamed argument, 4 + +``` + +```{r} +# run add_x2y() with a single argument: y = 3 + +``` + + + + + +### Exercise + + +Without using the `mean()` function, write a function called `my_mean()` that takes four values as its arguments and computes their mean. Ensure that each argument has a default of 0. Use your function to compute the mean of the values 4, 5, 2, 1. + +How would you modify your function to take a single vector of length 4 as its argument instead of four separate arguments? + + +#### Solution + +```{r} + +``` + + + + + + + + + + + + + + +## If/else statements + +### If statements + + +The following code defines a variable `a`, and then runs some *conditional* code that is only run if the condition `a == 1` is `TRUE`. + +```{r} +# define a variable `a` containing 5 + +# if `a` is equal to 1, print out some text + + + +# Then: +# 1. try the code again, with `a` equal to 1 +# 2. replace the code that is run in the if statement with a mathematical computation +# 3. replace the code that is run in the if statement with a variable definition (e.g., define y <- 3) +``` + + + +Unlike for a function, if you define a variable inside an if statement, then this variable will have been defined in our "global" environment too. + +```{r} +# Does y exist globally? + +``` + + + + + +### Else statemenets + +The "else" part of the "if/else" statement provides some code that will be run if the "if" condition is *not* `TRUE`. + +```{r} +# define a variable "a" containing 3 + +# if "a" equals 1, define y <- 3, else define y <- 9 + +``` + +```{r} +# check what y was assigned to + +``` + + + + + + +### Using "if" statements to provide custom errors for a function + +The following uses an "if" statement to add a "stop condition" that throws an error when innapropriate arguments are provided + +```{r} +# add an "if" condition to `my_mean()` to throw an error if the +# first argument `a` is either non-numeric OR +# if the length of `a` is greater than 1 + + +``` + + + + + +### Exercise + +1. Write a standalone if/else statement that checks whether the value in a variable called `age` is at least 18. If the age variable is 18 or older, your statement should return the character value of "You are eligible to vote" and if not, your statement should return "You are not eligible to vote" + +```{r} + +``` + +2. Write a function, `circle_area()`, that computes the area of a circle (`area = pi * radius^2`) with the radius as its argument, and throws an error if a non-numeric or a negative radius value is given. + +```{r} + +``` + + +Test your function on the following code + +```{r} +#| error: true + +# the following should throw an error: +circle_area("4") +circle_area(-4) +# the following should NOT throw an error: +circle_area(4) +``` + + + + + + + + + + +## Default argument options with `match.arg()` + +Below, we give an example of providing multiple options to an argument. + +```{r} +# define a function add_x2y() with three arguments: +# x: a numeric value with default value 1 +# y: a numeric value with default value 1 +# output_type: a character value with default value "numeric" and alternative option "character" + +# in the body of the function: +# use match.arg() to ensure that output_type is one of the options provided +# use an if statement to modify the output based on the value of output_type + + + +``` + + +```{r} +# apply add_x2y() to x = 2 and y = 3 and output_type = "character" + +``` + +```{r} +# apply add_x2y() to x = 2 and y = 3 with no output_type specified + +``` + +```{r} +#| error: true +# apply add_x2y() to x = 2 and y = 3 and output_type = "logical" + + +``` + + + + + + + +### Exercise + +Write a function called `calculate_area()` that will calculate the area of the shape specified in the argument `shape`, which has options "circle", "square", and "triangle". Your function will need to have the following additional arguments: + +- `radius` for computing the area of a circle (`pi * radius^2`), + +- `side` for computing the area of a square (`side^2`), + +- `base` and `height` for computing the area of a triangle (`height * base / 2`). + +Arguments that are not *always* required should have a default value of `NULL`. Your function should throw an error when you fail any value other than "circle", "square" or "triangle" for the `shape` argument (you can use `match.arg()` to do this!). + +Your function should throw an error when: + +1. the 'radius' argument is not provided when `shape == "circle"` + +1. the 'side' argument is not provided when `shape == "square"` + +1. the 'base' and 'height' arguments are not provided when `shape == "triangle"` + + +```{r} + +``` + + + + + + + + + + + + + +## Tidy evaluation for writing tidyverse-style functions + +Sometimes you want to write a function whose argument is a column of a data frame without quotes (i.e., in the tidyverse style) so that you can use it in a tidyverse function. + + + +```{r} +# load in the tidyverse and demographics NHANES data + +``` + +```{r} +# take a look at the demographics data + +``` + +Notice that when we refer to the variables from our data frame in the context of the tidyverse (including ggplot2), we do *not* use quotes around the column names: + +```{r} +# Use ggplot2 to compute boxplots for the age_years distribution across +# different levels of the language_english variable + +``` + + + +Let's try and turn this into a function. + +In this first attempt, we use `variable_name` as the argument: + +```{r} +# turn the above boxplot code into a function called createBoxplots() + +``` + + +```{r} +#| error: true + +# try to apply createBoxplots() to the language_english column + +``` + + +The issue is that ggplot wants us to refer to the column names without quotes, but our custom function doesn't know how to find our column name variable that we provide. + +We can use tidy evaluation (`{{ var_name }}`) to solve this problem. + +```{r} +# update our createBoxplots() function so that it uses tidy_evaluation + +``` + +And now it works: + +```{r} +# apply createBoxplots() to the language_english column + +``` + + +Let's use our function on a few different columns to make sure: + +```{r} +# apply createBoxplots() to the marital_status column + +# apply createBoxplots() to the pregnant column + +``` + + + + + + +#### Tip: Using patchwork to patch together plots + +The patchwork library can be used to create custom grids of ggplot objects (be sure to expand your plot window if the plots aren't showing up properly): + +```{r} +# load the patchwork library + +# create a grid of the language_english and marital_status boxplots + +``` + +```{r} +# create a grid of the language_english and pregnant boxplots on top +# with the marital_status boxplots underneath + +``` + + + + +### Exercise + +Create a function called createOrderedBars() that takes a categorical column from `demographics` as its argument and creates a bar chart for the average age for each level of the variable. + +*Hint*: Some example code for computing the average age for each level of the `marital_status` variable and creating a bar chart is shown below: + +```{r} +#| eval: false +demographics |> + group_by(marital_status) |> + summarize(mean_age = mean(age_years)) |> + ggplot() + + geom_col(aes(x = marital_status, + y = mean_age)) +``` + + +Challenge activity: Arrange the bars in ascending order, and provide an argument called `ascending` that allows the user to specify whether or not the bars will be arranged in ascending order. + + + +#### Solution + +Note that you'll want to use `geom_col()` instead of `geom_bar()` to create bar charts where the bars have the specific height provided in the y-variable. + +```{r} + +``` + diff --git a/content/incomplete/02_iteration_purrr.qmd b/content/incomplete/02_iteration_purrr.qmd new file mode 100644 index 0000000..3041b6a --- /dev/null +++ b/content/incomplete/02_iteration_purrr.qmd @@ -0,0 +1,300 @@ +--- +title: "Iteration with purrr" +format: html +editor_options: + chunk_output_type: console +--- + +The purpose of this lesson is to learn how to iteratively apply functions to all elements contained within an object, such as all columns in a data frame, or all entries in a vector. + +The "purrr" R package that we will be using in this lesson is *included* in the tidyverse package. + +```{r} +# load the tidyverse and demographics dataset + +``` + + + + +The function that we want to iterate first is the `n_distinct()` function from the tidyverse. + +Recall that to pull up the help page for a function, you can use the following syntax: + +```{r} +# pull up the help page for n_distinct + +``` + + +`n_distinct()` counts the number of unique values in a vector. + +```{r} +# apply n_distinct to the "gender" column of demographics + +``` + + +The code below uses the `map()` function to apply `n_distinct()` to every column of the `demographics` data frame simultaneously: + +```{r} +# use map() to apply n_distinct to every column of demographics + +``` + + +The output of the `map()` function is a list (more on that in a moment). + +The following code shows a simpler example, this time applying the `exp()` function to all entries/elements in a simple numeric vector: + +```{r} +# use map() to apply exp() to the vector c(4, 5, 6) + +``` + + + + + +### Lists + +Lists, like vectors, correspond to a collection of values contained in a single object. + +You can use the `list()` function to define a list, for example: + +```{r} +# define a list called my_list with three elements: 1, 4, and 7 + +``` + +You can extract elements from a list just as you would from a vector, using the square bracket notation. The code below extracts the third element from `my_list`: + +```{r} +# extract the third entry from my_list using [] + +# ask the class of the object above + +``` + +However, the output above is a list itself. + + +If you want to extract the actual object/value contained within the third element of the list, then you need to use double square parentheses: + +```{r} +# extract the third entry from my_list using [[]] + +``` + + + +Unlike vectors, lists are not vectorized. + +```{r} +#| error: true + +# try to add 1 to my_list + +``` + +Why would we ever prefer lists to vectors? The reason is that lists are infinitely more flexible than vectors. While all entries in a vector must be a *single value* of the *same type*, entries of a list can be anything. + + +```{r} +# create a list my_complex_list containing +# (1) the head of demographics, +# (2) the value 2, and +# (3) a vector containing "a" and "b" + +``` + +You can also create a *named* list when defining it as if you are defining argument names: + +```{r} +# create a named version of my_complex_list + +``` + + + +You can then extract entries from the named list using `$` or `[[]]` + +```{r} +# extract one of the elements from my_complex_list using $ + +# extract one of the elements from my_complex_list using [[]] + +``` + + + + + + + +### Exercise + +Use `map()` to apply `class()` to every column in the demographics dataset, and extract the class of the `household_income` column. + + + + + + + + + +## Using custom functions in purrr + + +To iterate using your own custom functions in a purrr `map()` function, you can define your function and provide it in the second argument of `map()`. + +```{r} +# define a function called exp_plus_one() that returns exp(x) + 1 + +# apply it to every entry in the vector c(1, 4, 5) + +``` + +For simple functions like this, we can define the function inside the `map()` function itself: + +```{r} +# apply the function exp(x) + 1 to every entry in the vector c(1, 4, 5) +# using an "anonymous" function + +``` + +However, we can go one step further and forego the `function(x)` part entirely using what I call the "tilde-dot" shorthand syntax. + +Here, we use the tilde `~` symbol to "start" an anonymous function and we use a `.` to represent the argument of our anonymous function. + +```{r} +# apply the function exp(x) + 1 to every entry in the vector c(1, 4, 5) +# using the "tilde-dot" syntax + +``` + + +To decide what should go inside the `~{}`, I typically use a representative value to test out my code first. + +Let's count the number of missing values in each column of demographics. + +For example, below, I take a single column `demographics$pregnant`, and I write out the code that I want to apply to it: + +```{r} +# compute the number of missing values in the "pregnant" column of demographics + +``` + +Generalize this code for the map function: + +```{r} +# use a map function to compute the number of missing values in every column + +``` + + + + + + + +### Exercise + +Use the tilde-dot short-hand syntax to compute the number of values in each column that is equal to 1. Recall that if a vector has missing values, and you want to use `sum()`, you will want to provide an argument `na.rm = TRUE` to ignore missing values. + + + + + + + + + + +## Alternative map functions for outputting doubles, characters and data frames + +Recall our `map()` function previously that we used to count the number of missing values in each column of the demographics data. + +```{r} +#| eval: false +map(demographics, ~sum(is.na(.))) +``` + +A list may not be the most useful format for this information... + + + + + +### Outputting numeric vectors + +The `map_dbl()` function will output a "double" (numeric) vector. + +```{r} +# use map_dbl to count the number of missing values in each column and +# output a numeric vector + +``` + + + +### Outputting character vectors + +The `map_chr()` function can output a *character* vector. + +```{r} +# use map_chr to apply class to every column and output a character vector + +``` + + + + +### Outputting data frames + +One of the most versatile functions is the `map_df()` function, which outputs a data frame. + + +```{r} +# apply map_df to demographics to determine the class of each column, outputting a "wide" data frame + +``` + +If you want your output to be in a "long" format, the function you are applying must output a single-column tibble/data frame. + +```{r} +# use tibble() to create a single-column tibble containing the class of demographics$pregnant + +# modify this code to be the function call in map_df to create a +# long-form data frame + +# provide an .id argument to include the original column names as a variable + +``` + + + + + + + +### Example + +This long-format is very useful if you want to create a plot, such as a bar chart for the number of missing values. + +```{r} +# create a bar chart of the number of missing values in each column +# use factors to order the columns by the number of missing values + +``` + +An alternative approach is to `map_df()` is to use `map_dbl()` and `enframe()` + +```{r} +# use map_dbl() and enframe() to create a long data frame of the +# number of missing values in each column + +``` + + diff --git a/content/incomplete/03_across.qmd b/content/incomplete/03_across.qmd new file mode 100644 index 0000000..bcc3995 --- /dev/null +++ b/content/incomplete/03_across.qmd @@ -0,0 +1,189 @@ +--- +title: "Across" +format: html +editor_options: + chunk_output_type: console +--- + +In this lesson, we will introduce the `across()` function, which can be used to apply dplyr functions like mutate, summarize, select, etc to subsets of columns that satisfy certain criteria, such as to all numeric columns, or all columns that start with `age_`. + + + +```{r} +# load the tidyverse and demographics dataset + +``` + + +Let's suppose that our task is to **convert all character columns of the demographics data to upper-case**. + +```{r} +# apply toupper() to the string value "abc" + +``` + + +Before introducing across, let's first see one way that we could do this using the `map()` functions that we have just learned: + +```{r} +# create a copy of demographics + +# create a logical vector for identifying character columns using map_chr() + +# re-assign the character columns to an upper-case version of themselves +# using map_df() applied to demographics_tmp[character_cols] with toupper() + + +# look at demographics_tmp + +# look at demographics (it should still have lowercase) + +``` + +While this works, it is fairly convoluted, is hard to read, and involves defining an intermediate variable (`character_cols`) -- in the tidyverse style, it is generally recommended to *avoid* defining intermediate variables whenever possible. + + + + + +## Introducing across() + +We could instead do this kind of operation using a `mutate()` operation in conjunction with `across()`. + +Let's figure out the code for just one column first +```{r} +# apply toupper to interview_examination with mutate + +``` + + + +To do this for *all character* columns, you need to provide `across()` to the argument of your mutate function. The `across()` function has two arguments: + +- The first argument is a "select statement" that specifies which columns you want to apply your function to. + +- The second argument is the function name, `toupper`, that we want to apply to all columns that are selected as a result of the first argument. + +The result is that `toupper()` is applied to all columns "where" `is.character()` would result in `TRUE`: + + +```{r} +# use across inside mutate to apply toupper() to all columns +# where(is.character) is TRUE... + +``` + + + + + + +## More across examples + +### Add 100 to all `age_` columns + +If we were to do this to just the `age_years` column, our code would look like: + +```{r} +# use mutate to add 100 to age_years + +``` + +To generalize this to all columns that start with `age_` using `across()`, we can use the `starts_with()` select helper, and apply the anonymous function `~{. + 100}`: + +```{r} +# use across inside mutate to apply ~{. + 100} to all columns +# that starts_with("age_")... + +``` + + + + + + + +### Convert `born_usa` and `citizen_usa` to numeric (binary) columns using `ends_with()` + + +```{r} +# take a look at born_usa and citizen_use using select() + +``` + + +```{r} +# use across inside mutate to apply as.numeric to all columns +# that ends_with("_usa")... + +``` + + + + + + +### Convert `born_usa` and `citizen_usa` to numeric (binary) columns using a vector of column names + +Suppose we had a vector of column names that we wanted to modify using `mutate()`: + +```{r} +# define a vector selected_columns with "born_usa" and "citizen_usa" + +``` + +Then we could use `all_of(selected_cols)` in `across()` to apply the function to all columns listed in the `selected_cols` vector as follows: + +```{r} +# use across inside mutate to apply as.numeric to all_of(selected_columns) + +``` + + + + + + + +## Select helpers summary + +So far we have seen the following "select helpers" that can be used to specify the columns inside `across()`: + +- `where()` -- across to all columns that satisfy a logical condition (`across(where(is.character), fun)`) + +- `starts_with()` and `ends_with()` -- across all columns that start or ends with a specified string (`across(starts_with("abc"), fun)`) + +- `contains()` -- across all columns that contain a specified string (`across(contains("abc"), fun)`) + +- `all_of()` and `any_of()` -- across all columns whose names are contained in a character vector, where `all_of()` requires all columns in the vector be present. (`across(all_of(vec_names), fun)`) + +- `everything()` -- across all columns + +These can also be used within `select()` + +```{r} +# select all columns that contain "age" + +# select all columns that start with "age" + +# select all columns that have a logical type + +``` + + + + + + + + +### Exercise + +a. For all columns that contain the word "education" (`education_youth` and `education`), add the number 5 to each value + +b. For all numeric columns, standardize the values by subtracting the mean and dividing by the standard deviation + +c. Compute the average age across all columns that start with `age_` (Hint: use `across()` within `summarize()`) + +d. Compute the total number of `TRUE` values in the `born_usa`, `citizen_usa`, and `language_english` columns (Hint: use `across()` within `summarize()`) + diff --git a/content/incomplete/04_recoding_variables.qmd b/content/incomplete/04_recoding_variables.qmd new file mode 100644 index 0000000..7a6020d --- /dev/null +++ b/content/incomplete/04_recoding_variables.qmd @@ -0,0 +1,101 @@ +--- +title: "Recoding variables using if_else and case_when" +format: html +editor_options: + chunk_output_type: console +--- + +```{r} +# load the tidyverse and demographics dataset + +``` + + +In this document, you will learn how to "recode" variables by replacing values in a variable with other values of your choice, e.g., converting numerically-encoded variables to categorical/character versions, and vice versa. + +We will introduce two functions for doing this: + +- `if_else()` which can be used to create binary variables (variables with just two distinct values) based on a logical "condition" + +- `case_when()` which can be used to create variables with many different values. + + + + + + +## if_else + +Take a look at `interview_examination`: + +```{r} +# apply count() to interview_examination + +``` + +Let's convert it to a numeric format using `if_else()`. + +```{r} +# use mutate() to create a new column called interview_examination_numeric +# which is 2 if interview_examination is "both interview and exam" +# and 1 otherwise +# then select just interview_examination and interview_examination_numeric + +``` + + + + + + +### Exercise + +Use `if_else()` to create a variable called `completed_high_school`, which has the values `"yes"` if `education` is equal to at least 3, and `"no"` otherwise. + +A link to the documentation for the demographics data can be found [here](https://wwwn.cdc.gov/Nchs/Nhanes/2017-2018/P_DEMO.htm#DMDEDUC2). + + + + + + + + + + +## case_when + +The `case_when()` function is similar to `if_else()`, but it allows you to have an unlimited number of conditions and corresponding recoded values. + +Take a look at the `marital_status` column of the demographics data: + +```{r} +# apply count() to the marital_status column + +``` + +Let's create a new variable based on `marital_status` that replaces + +- `"married"` with `3` + +- `"living_with_partner"` with `2` + +- `"divorced"`, `"widowed"`, `"never_married"`, and `"separated"` with `1` + +```{r} +# use mutate and case_when() to create marital_status_numeric +# with the values above + +``` + + + + + + + + +## Execise + +Use `case_when()` to convert `born_usa` and `citizen_usa` to "yes" and "no". Bonus points: use `across()`. + diff --git a/content/incomplete/05_pivoting.qmd b/content/incomplete/05_pivoting.qmd new file mode 100644 index 0000000..8d308ed --- /dev/null +++ b/content/incomplete/05_pivoting.qmd @@ -0,0 +1,73 @@ +--- +title: "Reshaping (Pivoting) Data" +format: html +editor_options: + chunk_output_type: console +--- + +In this lesson, we will be working with a new NHANES table that contains urine albumin and creatinine *lab* data. + +```{r} +# load the tidyverse and the urine_albumin_creatinine NHANES data + +``` + +```{r} +# take a look at the first 10 rows + +``` + +This data is in a **long format**--there are multiple rows for each observational unit, each corresponding to a different variable being measured (in this case, the different labs). + + +A **wide format**, on the other hand, will only have *one* row for each observational unit (respondent), and each of the individual variables being measured (the labs) will have their own column, each containing the *values* for the corresponding lab. + +You can convert from a long format to a wide format using the `pivor_wider()` function. + +The code below creates a wide-form version of the labs data, and saves it as a new data frame called `labs_data_wide`: + +```{r} +# use pivot_wider() to convert the labs data from a +# long format to a wide format. +# arguments are `names_from` and `values_from` +# save the wide data as `labs_data_wide`. + + +``` + +If you want to convert from a wide format dataset into a longer-format dataset, you can instead use the `pivot_longer()` function. + + +```{r} +# use pivot_longer() to convert labs_data_wide back to along format +# arguments are `cols` (use a select helper!), `names_to` and `values_to` + +``` + + +Use-case for long-format: creating a visualization that compares the different variables using ggplot2. + +```{r} +# create boxplots using the long format for the measurements from each lab +# maybe add a log-scale to the y-axis + +``` + + +### Exercise + +Load the demographics data and use `select()` to select just the `respondent_id`, `gender`, `marital_status` and `race` columns and then use `pivot_longer()` to create the following long-format table (below are just the first 10 rows). + + respondent_id name value + + 1 73557 gender male + 2 73557 marital_status separated + 3 73557 race black + 4 73558 gender male + 5 73558 marital_status married + 6 73558 race white + 7 73559 gender male + 8 73559 marital_status married + 9 73559 race white +10 73560 gender male + diff --git a/content/incomplete/06_joining.qmd b/content/incomplete/06_joining.qmd new file mode 100644 index 0000000..432730a --- /dev/null +++ b/content/incomplete/06_joining.qmd @@ -0,0 +1,163 @@ +--- +title: "Joining Data Together" +format: html +editor_options: + chunk_output_type: console +--- + +This lesson introduces techniques for "joining" multiple data tables together using a "key" variable + +A really helpful resource for learning about joins is the [R for Data Science](https://r4ds.had.co.nz/index.html) book (specifically the chapter about ["Relational Data"](https://r4ds.had.co.nz/relational-data.html)). + +At the end of this lesson we will have created a *single* data frame that contains the information from both the `demographics` data and the urine albumin and creatinine `labs` data. + +```{r} +# load the tidyverse, +# load the demographics, and +# load the urine_albumin_creatinine labs data + +``` + +## Determining what kind of join to do + +There are four kinds of joins that you might want to use for combining two tables into a single table: + +![Diagram of joins](figures/joins.png) + +- An **inner join**, which will keep only the data for the observational units that appear in both tables + +- A **left join**, which will keep all of the data for the observational units in the first (left) table, and will add missing values when there is no available data in the second table. + +- A **right join**, which will keep all of the data for the observational units in the second (right) table, and will add missing values when there is no available data in the first table. + +- A **full join**, which will keep all of the data for the observational units in both the first (left) table, and will add missing values when there is no available data in the other table. + +The kind of join that you will implement will depend on what you want to use your joined data for. + + + +### Checking the uniqueness of the key ID variables + +Below, we see that the `respondent_id` column is indeed unique for `demographics`: + +```{r} +# check whether the respondent ID values in demographics are unique? + +``` + +But not for `labs`: + +```{r} +# check whether the respondent ID values in labs are unique? + +``` + + + + + + + +### Checking overlap between tables + + +*Are there any observations in the demographics table that do not appear in the labs table?* + +```{r} +# Compute the proportion of people in demographics who are also in labs + +``` + +The calculation above shows that around 81% of observations in the demographics table have available labs data. + + + + + +*Are there any observations in the labs table that do not appear in the demographics table?* + +```{r} +# proportion of people in labs who are also in demographics + +``` + +The calculation above shows that 100% of observations in the labs table have available demographics data. + + + + + + + + + + +## Joining demographics and labs + +Our two options for to join demographics (left) and labs (right) are: + +- An inner or right join will only keep the 81% of people in demographics who have available labs data + +- A left or full join will keep all people in demographics data, and join missing values for those who don't have labs data available + +Since we don't want to discard any data, we will choose the left/full join. + + +```{r} +# perform a left/full join of demographics and labs + +``` + +Look at the results above, does something look wrong to you? + + + + + + + + + + + + + +**If your key ID variable has repeated values, your joined data will too**. + +A good check after completing a join is to make sure that the number of rows in the resulting joined data matches what you expect + + +```{r} +# check the number of rows in the joined data + +# check the number of rows in demographics + +``` + + + + + + + +Therefore, to ensure that we have just one row per observational unit (i.e., per `respondent_id` value), we need to join the wide-format `labs_wide` data instead of the long-format `labs` data. + +```{r} +# compute the wide format of the labs data + +``` + + +```{r} +# join demographics and labs_wide + +``` + + + + + + +## Exercise + +How many rows would you expect an *inner join* of `demographics` and `labs_wide` to have? Check your answer by conducting the join using `inner_join()` diff --git a/content/incomplete/data/demographics.csv b/content/incomplete/data/demographics.csv new file mode 100644 index 0000000..bef67f3 --- /dev/null +++ b/content/incomplete/data/demographics.csv @@ -0,0 +1,10176 @@ +respondent_id,interview_examination,gender,age_years,age_months_sc_0_2yr,race,six_month_period,age_months_ex_0_19yr,served_active_duty_us,served_active_duty_foreign,born_usa,citizen_usa,time_in_us,education_youth,education,marital_status,pregnant,language_english,household_income +73557,both interview and exam,male,69,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,17500 +73558,both interview and exam,male,54,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +73559,both interview and exam,male,72,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +73560,both interview and exam,male,9,NA,white,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,60000 +73561,both interview and 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exam,female,38,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,NA +73581,both interview and exam,male,50,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +73582,both interview and exam,female,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,yes,TRUE,12500 +73583,both interview and exam,female,7,NA,white,2,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +73584,both interview and exam,male,13,NA,white,2,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,60000 +73585,both interview and exam,male,28,NA,asian,2,NA,TRUE,TRUE,FALSE,TRUE,25,NA,4,married,NA,TRUE,40000 +73586,both interview and exam,female,4,NA,asian,1,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +73587,both interview and exam,male,14,NA,asian,1,174,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +73588,both interview and exam,male,11,NA,black,1,140,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +73589,both interview and exam,male,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +73590,both 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exam,male,3,NA,asian,1,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +73609,both interview and exam,female,11,NA,mexican american,1,140,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,30000 +73610,both interview and exam,male,43,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +73611,both interview and exam,female,3,NA,other hispanic,2,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +73612,both interview and exam,female,6,NA,asian,1,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +73613,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +73614,both interview and exam,female,55,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,3,widowed,NA,TRUE,22500 +73615,both interview and exam,female,65,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,1,widowed,NA,FALSE,12500 +73616,both interview and exam,female,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +73617,both interview and exam,male,6,NA,mexican 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exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,60000 +73703,both interview and exam,female,38,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,2,married,no,FALSE,NA +73704,both interview and exam,female,8,NA,white,2,104,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +73705,both interview and exam,male,10,NA,white,1,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +73706,both interview and exam,male,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +73707,both interview and exam,male,45,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +73708,both interview and exam,male,69,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +73709,both interview and exam,male,64,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +73710,both interview and exam,male,2,NA,white,1,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +73711,both interview and exam,male,5,NA,mexican american,2,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +73712,both interview and exam,male,18,NA,asian,1,224,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +73713,both interview and exam,male,3,NA,mexican american,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +73714,both interview and exam,female,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +73715,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +73716,both interview and exam,male,25,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,50000 +73717,both interview and exam,male,78,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +73718,both interview and exam,male,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +73719,both interview and exam,female,11,NA,mexican american,2,142,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +73720,both interview and exam,male,48,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 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exam,female,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,30000 +73740,both interview and exam,female,57,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,TRUE,60000 +73741,both interview and exam,female,47,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,NA +73742,both interview and exam,female,11,NA,other,2,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +73743,interview only,male,0,11,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +73744,both interview and exam,female,0,9,white,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +73745,both interview and exam,male,7,NA,other,2,88,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +73746,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +73747,both interview and exam,female,80,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +73748,both interview and exam,male,0,10,black,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +73749,both interview and exam,male,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,NA +73750,both interview and exam,male,9,NA,other,1,111,NA,NA,FALSE,TRUE,7.5,3,NA,NA,NA,TRUE,40000 +73751,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,12500 +73752,both interview and exam,female,8,NA,white,2,107,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +73753,both interview and exam,female,11,NA,white,1,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +73754,both interview and exam,male,15,NA,mexican american,2,190,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,17500 +73755,both interview and exam,male,75,NA,mexican american,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,40000 +73756,both interview and exam,male,56,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +73757,both interview and exam,female,29,NA,mexican 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exam,female,75,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +73767,both interview and exam,female,35,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,no,TRUE,100000 +73768,both interview and exam,female,4,NA,asian,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +73769,both interview and exam,male,42,NA,other hispanic,2,NA,FALSE,NA,NA,NA,NA,NA,5,divorced,NA,TRUE,NA +73770,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +73771,both interview and exam,male,0,3,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +73772,both interview and exam,female,21,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +73773,both interview and exam,female,39,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +73774,both interview and exam,female,80,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,NA +73775,both interview and exam,female,14,NA,black,2,179,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,12500 +73776,both interview and exam,female,19,NA,other hispanic,1,234,FALSE,NA,FALSE,FALSE,0.5,9,NA,NA,NA,FALSE,22500 +73777,interview only,male,5,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +73778,both interview and exam,male,62,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,4,married,NA,TRUE,22500 +73779,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,2500 +73780,both interview and exam,male,78,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +73781,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +73782,both interview and exam,male,68,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +73783,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +73784,interview only,female,7,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +73785,both interview and exam,male,46,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +73786,both interview and exam,female,18,NA,white,2,217,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +73787,both interview and exam,male,71,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,60000 +73788,both interview and exam,female,9,NA,other hispanic,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +73789,both interview and exam,female,2,NA,black,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +73790,both interview and exam,male,59,NA,white,2,NA,TRUE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +73791,interview only,male,8,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +73792,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +73793,both interview and exam,male,10,NA,mexican american,2,131,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +73794,both interview and exam,female,6,NA,other hispanic,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +73795,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +73796,both interview and exam,female,5,NA,mexican american,1,72,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +73797,both interview and exam,female,57,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +73798,both interview and exam,male,11,NA,other hispanic,1,133,NA,NA,FALSE,FALSE,0.5,4,NA,NA,NA,FALSE,22500 +73799,both interview and exam,female,10,NA,mexican american,1,129,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +73800,both interview and exam,female,54,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +73801,both interview and exam,female,46,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +73802,both interview and exam,female,18,NA,asian,1,218,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 +73803,both interview and exam,male,14,NA,asian,1,174,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +73804,both interview and exam,male,55,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,22500 +73805,both interview and exam,female,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +73806,both interview and exam,male,63,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +73807,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +73808,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +73809,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,30000 +73810,both interview and exam,male,48,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +73811,both interview and exam,male,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,22500 +73812,both interview and exam,male,5,NA,white,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +73813,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +73814,both interview and exam,male,0,4,black,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +73815,both interview and exam,female,72,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +73816,both interview and exam,male,64,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,married,NA,FALSE,30000 +73817,both interview and exam,male,0,6,mexican american,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +73818,both interview and exam,male,5,NA,black,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +73819,both interview and exam,male,4,NA,other hispanic,1,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +73820,both interview and exam,male,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +73821,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 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exam,female,48,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +73832,interview only,male,77,NA,black,NA,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +73833,both interview and exam,female,34,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,unable to ascertain,TRUE,100000 +73834,both interview and exam,male,64,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,never_married,NA,TRUE,NA +73835,both interview and exam,male,13,NA,mexican american,1,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +73836,both interview and exam,female,9,NA,white,2,112,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +73837,both interview and exam,male,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +73838,both interview and exam,female,2,NA,black,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +73839,both interview and exam,male,68,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +73840,both interview and exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,22500 +73841,both interview and exam,male,13,NA,mexican american,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,22500 +73842,both interview and exam,male,53,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,12500 +73843,both interview and exam,male,42,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,40000 +73844,both interview and exam,female,12,NA,white,1,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +73845,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +73846,both interview and exam,female,24,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +73847,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,40000 +73848,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,12500 +73849,both interview and exam,female,16,NA,white,2,200,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +73850,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +73851,both interview and exam,female,48,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +73852,both interview and exam,female,40,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,no,FALSE,50000 +73853,both interview and exam,male,13,NA,white,2,165,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +73854,both interview and exam,female,1,23,mexican american,1,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +73855,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,7500 +73856,both interview and exam,male,0,10,other hispanic,1,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +73857,interview only,male,23,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,FALSE,40000 +73858,both interview and exam,male,52,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +73859,both interview and exam,male,38,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +73860,both interview and exam,male,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,30000 +73861,both interview and exam,male,77,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +73862,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +73863,both interview and exam,male,26,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,never_married,NA,TRUE,50000 +73864,both interview and exam,female,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +73865,both interview and exam,male,48,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +73866,both interview and exam,female,47,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +73867,interview only,female,80,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +73868,both interview and exam,male,32,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +73869,both interview and exam,male,7,NA,black,1,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +73870,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +73871,interview only,female,28,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,unable to ascertain,TRUE,60000 +73872,both interview and exam,female,63,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,married,NA,TRUE,NA +73873,both interview and exam,male,80,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +73874,both interview and exam,female,2,NA,white,1,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +73875,both interview and exam,male,43,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,TRUE,50000 +73876,both interview and exam,female,0,5,white,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +73877,both interview and exam,female,0,6,black,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +73878,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,40000 +73879,both interview and exam,female,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +73880,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,70000 +73881,both interview and exam,male,38,NA,other hispanic,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +73882,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,12500 +73883,both interview and exam,male,67,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,1,married,NA,FALSE,7500 +73884,both interview and exam,male,43,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +73885,both interview and exam,male,6,NA,white,2,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +73886,both interview and exam,female,64,NA,other hispanic,1,NA,FALSE,NA,NA,NA,NA,NA,5,NA,NA,TRUE,100000 +73887,both interview and exam,male,16,NA,white,1,194,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +73888,both interview and exam,male,56,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +73889,both interview and exam,male,15,NA,other hispanic,1,184,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,17500 +73890,both interview and exam,male,16,NA,black,2,196,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,7500 +73891,both interview and exam,male,12,NA,black,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,60000 +73892,both interview and exam,male,15,NA,asian,2,183,NA,NA,FALSE,TRUE,12.5,8,NA,NA,NA,TRUE,100000 +73893,both interview and exam,male,17,NA,black,2,210,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,NA +73894,both interview and exam,male,6,NA,black,1,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +73895,both interview and exam,male,5,NA,mexican 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interview and exam,male,12,NA,mexican american,1,150,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,22500 +73906,both interview and exam,female,34,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,separated,no,FALSE,12500 +73907,both interview and exam,female,8,NA,white,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +73908,both interview and exam,male,67,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +73909,both interview and exam,male,0,7,black,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +73910,both interview and exam,male,51,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +73911,both interview and exam,male,3,NA,white,2,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +73912,both interview and exam,male,0,2,other hispanic,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +73913,both interview and exam,male,26,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +73914,both interview and exam,female,52,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +73915,both interview and exam,female,14,NA,white,2,178,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +73916,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +73917,both interview and exam,male,8,NA,white,2,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +73918,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +73919,both interview and exam,male,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,2500 +73920,both interview and exam,male,18,NA,mexican american,2,218,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,FALSE,40000 +73921,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,12500 +73922,both interview and exam,female,75,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +73923,both interview and exam,male,4,NA,mexican 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exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +73933,both interview and exam,female,10,NA,other,2,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,17500 +73934,both interview and exam,male,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +73935,both interview and exam,male,63,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +73936,both interview and exam,female,3,NA,white,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +73937,both interview and exam,female,41,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,no,FALSE,22500 +73938,both interview and exam,female,53,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +73939,both interview and exam,female,6,NA,other,1,80,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,2500 +73940,both interview and exam,male,7,NA,mexican american,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,NA +73941,both interview and exam,male,28,NA,black,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,living_with_partner,NA,TRUE,50000 +73942,both interview and exam,male,5,NA,black,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +73943,both interview and exam,male,19,NA,other hispanic,1,232,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,60000 +73944,both interview and exam,male,0,9,black,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +73945,both interview and exam,male,66,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +73946,both interview and exam,male,2,NA,mexican american,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +73947,both interview and exam,male,1,22,mexican american,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +73948,both interview and exam,female,4,NA,black,1,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +73949,both interview and exam,male,48,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +73950,both interview and exam,male,3,NA,white,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 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exam,female,11,NA,white,2,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +73961,both interview and exam,male,7,NA,black,1,95,NA,NA,FALSE,FALSE,3,0,NA,NA,NA,TRUE,30000 +73962,both interview and exam,male,49,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +73963,both interview and exam,male,16,NA,asian,1,204,NA,NA,FALSE,TRUE,12.5,10,NA,NA,NA,TRUE,87500 +73964,both interview and exam,male,45,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +73965,both interview and exam,male,0,1,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +73966,both interview and exam,male,7,NA,mexican american,1,85,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,22500 +73967,both interview and exam,male,9,NA,asian,1,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +73968,both interview and exam,male,15,NA,black,1,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +73969,both interview and exam,male,0,9,white,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +73970,both interview and exam,male,10,NA,other hispanic,2,125,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +73971,both interview and exam,female,15,NA,black,2,190,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +73972,both interview and exam,female,2,NA,mexican american,2,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +73973,both interview and exam,female,75,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,widowed,NA,TRUE,50000 +73974,both interview and exam,male,34,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +73975,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +73976,both interview and exam,female,11,NA,other,1,137,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +73977,both interview and exam,male,30,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +73978,both interview and exam,female,10,NA,asian,2,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +73979,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +73980,both interview and exam,male,43,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,NA +73981,both interview and exam,female,36,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,3,never_married,no,TRUE,40000 +73982,both interview and exam,male,13,NA,black,2,162,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,7500 +73983,both interview and exam,female,18,NA,black,1,221,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 +73984,both interview and exam,male,5,NA,white,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +73985,both interview and exam,female,43,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,no,TRUE,60000 +73986,both interview and exam,female,7,NA,black,1,87,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +73987,both interview and exam,male,56,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +73988,both interview and 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exam,male,45,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +74026,both interview and exam,male,11,NA,other hispanic,1,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,NA +74027,both interview and exam,male,42,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,70000 +74028,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +74029,both interview and exam,male,22,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +74030,both interview and exam,male,0,9,white,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74031,both interview and exam,female,19,NA,black,1,230,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,50000 +74032,both interview and exam,female,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74033,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,70000 +74034,both interview and exam,female,0,6,mexican 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american,2,177,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,7500 +74044,both interview and exam,male,73,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +74045,both interview and exam,male,38,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,never_married,NA,FALSE,50000 +74046,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,unable to ascertain,TRUE,100000 +74047,both interview and exam,female,40,NA,mexican american,1,NA,FALSE,NA,FALSE,NA,NA,NA,2,living_with_partner,no,FALSE,22500 +74048,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +74049,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,NA,TRUE,40000 +74050,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +74051,both interview and exam,female,20,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +74052,both interview and exam,female,19,NA,black,2,239,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 +74053,both interview and exam,female,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +74054,both interview and exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,70000 +74055,both interview and exam,male,57,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,50000 +74056,both interview and exam,male,38,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,22500 +74057,both interview and exam,female,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +74058,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,30000 +74059,both interview and exam,male,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74060,both interview and exam,female,8,NA,white,2,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +74061,both interview and exam,female,12,NA,black,1,148,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +74062,both interview and exam,female,67,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,45,NA,2,never_married,NA,TRUE,17500 +74063,interview only,male,49,NA,asian,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,100000 +74064,both interview and exam,male,17,NA,asian,2,207,FALSE,NA,FALSE,FALSE,3,9,NA,NA,NA,TRUE,17500 +74065,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,50000 +74066,both interview and exam,male,56,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,FALSE,17500 +74067,both interview and exam,female,2,NA,white,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74068,both interview and exam,female,5,NA,white,2,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74069,both interview and exam,female,0,11,white,1,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74070,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 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exam,female,5,NA,white,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74081,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +74082,both interview and exam,male,4,NA,other,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74083,both interview and exam,female,67,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +74084,both interview and exam,male,1,15,other,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74085,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +74086,both interview and exam,male,6,NA,black,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74087,both interview and exam,female,59,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,100000 +74088,both interview and exam,male,12,NA,mexican american,2,147,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,22500 +74089,both interview and exam,male,11,NA,black,2,143,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +74090,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,30000 +74091,both interview and exam,female,19,NA,other,2,237,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,70000 +74092,both interview and exam,female,6,NA,black,1,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74093,both interview and exam,male,4,NA,mexican american,2,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,100000 +74094,both interview and exam,male,7,NA,black,2,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +74095,both interview and exam,female,12,NA,other hispanic,1,150,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +74096,both interview and exam,male,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,7500 +74097,both interview and exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +74098,both interview and exam,male,0,4,mexican american,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74099,both interview and exam,male,44,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,FALSE,22500 +74100,both interview and exam,male,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,17500 +74101,both interview and exam,female,34,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +74102,both interview and exam,female,18,NA,black,2,217,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,40000 +74103,both interview and exam,female,17,NA,other hispanic,1,211,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,22500 +74104,both interview and exam,female,8,NA,other,1,102,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +74105,both interview and exam,female,0,1,black,2,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74106,both interview and exam,female,10,NA,black,2,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +74107,both interview and exam,male,4,NA,white,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74108,both interview and exam,female,1,19,black,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74109,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,FALSE,FALSE,35,NA,3,divorced,NA,TRUE,40000 +74110,both interview and exam,male,60,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,30000 +74111,both interview and exam,female,61,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,widowed,NA,TRUE,100000 +74112,both interview and exam,female,28,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,17500 +74113,both interview and exam,male,17,NA,white,1,212,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +74114,both interview and exam,female,9,NA,black,1,112,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +74115,both interview and exam,male,27,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,living_with_partner,NA,FALSE,17500 +74116,both interview and exam,male,25,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,50000 +74117,both interview and exam,female,8,NA,black,1,104,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +74118,both interview and exam,female,35,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,no,FALSE,87500 +74119,both interview and exam,female,32,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,1,married,no,FALSE,40000 +74120,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +74121,both interview and exam,female,9,NA,white,2,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +74122,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,FALSE,FALSE,55,NA,4,divorced,NA,TRUE,30000 +74123,both interview and exam,female,21,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,yes,TRUE,12500 +74124,both interview and exam,female,28,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,separated,no,TRUE,22500 +74125,both interview and exam,female,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,NA +74126,both interview and exam,female,53,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +74127,both interview and exam,female,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +74128,both interview and exam,female,71,NA,black,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,married,NA,TRUE,40000 +74129,both interview and exam,male,56,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,NA,TRUE,50000 +74130,both interview and exam,male,12,NA,black,1,149,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +74131,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,70000 +74132,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,70000 +74133,both interview and exam,female,14,NA,mexican american,2,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,30000 +74134,both interview and exam,female,51,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,NA,TRUE,60000 +74135,both interview and exam,female,6,NA,white,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74136,both interview and exam,male,9,NA,asian,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +74137,both interview and exam,male,17,NA,mexican american,1,212,FALSE,NA,FALSE,FALSE,12.5,12,NA,NA,NA,FALSE,50000 +74138,both interview and exam,male,69,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,FALSE,30000 +74139,both interview and exam,female,63,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,2500 +74140,both interview and exam,female,8,NA,mexican american,1,100,NA,NA,FALSE,FALSE,7.5,2,NA,NA,NA,FALSE,12500 +74141,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,60000 +74142,both interview and exam,male,61,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +74143,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74144,both interview and exam,male,51,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,87500 +74145,both interview and exam,male,6,NA,black,2,79,NA,NA,FALSE,FALSE,7.5,0,NA,NA,NA,TRUE,40000 +74146,both interview and exam,male,50,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,TRUE,7500 +74147,both interview and exam,female,79,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +74148,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,22500 +74149,both interview and exam,female,54,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +74150,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,87500 +74151,interview only,male,1,21,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +74152,both interview and exam,female,74,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,7500 +74153,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +74154,both interview and exam,female,52,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +74155,interview only,female,20,NA,other hispanic,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,unable to ascertain,TRUE,17500 +74156,both interview and exam,female,3,NA,other hispanic,2,37,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74157,both interview and exam,female,7,NA,other,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74158,both interview and exam,female,19,NA,black,1,232,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +74159,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +74160,both interview and exam,female,66,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +74161,both interview and exam,female,16,NA,other,2,202,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +74162,interview only,female,19,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,NA +74163,both interview and exam,female,11,NA,mexican american,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +74164,both interview and exam,female,38,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +74165,both interview and exam,male,3,NA,mexican american,1,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +74166,both interview and exam,female,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,7500 +74167,both interview and exam,male,0,4,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74168,both interview and exam,male,14,NA,mexican american,2,174,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +74169,both interview and exam,male,22,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +74170,both interview and exam,male,56,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74171,both interview and exam,male,17,NA,asian,2,205,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,60000 +74172,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,30000 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american,2,151,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +74183,both interview and exam,female,11,NA,other hispanic,2,143,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +74184,both interview and exam,female,55,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,100000 +74185,both interview and exam,female,11,NA,white,1,143,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +74186,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,40000 +74187,both interview and exam,female,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,NA +74188,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,NA +74189,both interview and exam,female,0,1,mexican american,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74190,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +74191,both interview and exam,female,39,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,2500 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exam,female,17,NA,black,2,206,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +74361,both interview and exam,female,10,NA,white,1,125,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +74362,both interview and exam,female,2,NA,white,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74363,both interview and exam,male,2,NA,white,2,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74364,both interview and exam,female,5,NA,mexican american,1,72,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74365,both interview and exam,male,3,NA,white,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +74366,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +74367,both interview and exam,male,74,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,NA +74368,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +74369,both interview and exam,male,7,NA,mexican american,1,95,NA,NA,FALSE,FALSE,7.5,1,NA,NA,NA,FALSE,22500 +74370,both interview and exam,male,6,NA,black,1,77,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +74371,both interview and exam,male,1,22,other hispanic,1,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74372,both interview and exam,male,4,NA,black,1,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74373,both interview and exam,male,7,NA,mexican american,1,87,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,NA +74374,both interview and exam,female,70,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,50000 +74375,both interview and exam,female,63,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,2500 +74376,both interview and exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +74377,both interview and exam,male,3,NA,black,1,46,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +74378,both interview and exam,male,24,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,FALSE,30000 +74379,both interview and exam,male,43,NA,black,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,living_with_partner,NA,TRUE,50000 +74380,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +74381,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,70000 +74382,both interview and exam,male,4,NA,black,1,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74383,both interview and exam,male,64,NA,other hispanic,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,100000 +74384,both interview and exam,female,25,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +74385,both interview and exam,male,73,NA,white,2,NA,TRUE,FALSE,FALSE,TRUE,55,NA,5,married,NA,TRUE,60000 +74386,both interview and exam,male,24,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +74387,both interview and exam,female,2,NA,black,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74388,both interview and exam,male,57,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,NA,TRUE,70000 +74389,both interview and exam,female,4,NA,black,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +74390,both interview and exam,male,5,NA,black,1,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74391,both interview and exam,female,0,6,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74392,both interview and exam,male,14,NA,white,2,169,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,NA +74393,both interview and exam,male,26,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,never_married,NA,TRUE,30000 +74394,both interview and exam,female,51,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +74395,both interview and exam,male,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +74396,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +74397,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +74398,both interview and exam,male,27,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +74399,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +74400,both interview and exam,male,23,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +74401,both interview and exam,female,19,NA,white,2,234,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,22500 +74402,both interview and exam,female,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +74403,both interview and exam,female,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +74404,both interview and exam,female,0,11,white,1,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74405,both interview and exam,female,5,NA,black,1,73,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74406,both interview and exam,female,0,5,other hispanic,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74407,both interview and exam,female,8,NA,white,1,102,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +74408,both interview and exam,male,29,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +74409,interview only,female,6,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +74410,both interview and exam,male,9,NA,white,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +74411,both interview and exam,male,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,70000 +74412,both interview and exam,male,37,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,NA,TRUE,50000 +74413,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +74414,both interview and exam,female,0,9,white,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74415,both interview and exam,female,17,NA,mexican american,2,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +74416,both interview and exam,male,3,NA,asian,1,47,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,TRUE,50000 +74417,both interview and exam,female,56,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +74418,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +74419,both interview and exam,female,76,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +74420,both interview and exam,female,5,NA,black,2,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74421,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +74422,both interview and exam,male,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,7500 +74423,both interview and exam,male,16,NA,asian,2,193,NA,NA,FALSE,FALSE,3,9,NA,NA,NA,TRUE,NA +74424,both interview and exam,female,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,87500 +74425,both interview and exam,female,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +74426,both interview and exam,male,2,NA,white,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74427,both interview and exam,male,14,NA,black,1,172,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,22500 +74428,both interview and exam,male,0,9,white,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74429,both interview and exam,male,1,13,white,2,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +74430,both interview and exam,male,11,NA,white,2,133,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +74431,both interview and exam,female,5,NA,other hispanic,2,63,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74432,both interview and exam,male,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +74433,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,100000 +74434,both interview and exam,female,36,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,17500 +74435,both interview and exam,male,19,NA,black,2,239,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,50000 +74436,both interview and exam,male,55,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,87500 +74437,both interview and exam,male,35,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,never_married,NA,FALSE,40000 +74438,both interview and exam,male,0,5,white,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74439,both interview and exam,female,0,1,mexican american,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,40000 +74440,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +74441,both interview and exam,female,38,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,yes,TRUE,17500 +74442,both interview and exam,male,63,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +74443,both interview and exam,female,11,NA,other hispanic,1,138,NA,NA,FALSE,TRUE,12.5,5,NA,NA,NA,FALSE,50000 +74444,both interview and exam,male,10,NA,black,1,128,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,60000 +74445,both interview and exam,male,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +74446,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +74447,both interview and exam,male,0,10,other hispanic,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74448,both interview and exam,female,5,NA,asian,2,62,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74449,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74450,both interview and exam,male,16,NA,mexican american,2,196,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,30000 +74451,both interview and exam,female,77,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +74452,both interview and exam,female,11,NA,mexican american,2,139,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +74453,both interview and exam,male,0,8,white,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 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exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,87500 +74464,both interview and exam,male,45,NA,other,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,2500 +74465,both interview and exam,male,80,NA,mexican american,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +74466,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +74467,both interview and exam,male,1,18,black,2,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74468,both interview and exam,female,5,NA,asian,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74469,both interview and exam,male,1,15,black,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74470,both interview and exam,male,4,NA,white,2,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74471,both interview and exam,female,16,NA,mexican american,1,204,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +74472,both interview and exam,female,2,NA,white,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74473,both interview 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exam,female,10,NA,white,2,132,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,60000 +74493,both interview and exam,male,40,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,3,living_with_partner,NA,FALSE,50000 +74494,both interview and exam,male,2,NA,black,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74495,both interview and exam,male,8,NA,asian,1,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,60000 +74496,both interview and exam,male,4,NA,white,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74497,both interview and exam,male,2,NA,other hispanic,1,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +74498,both interview and exam,male,29,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,TRUE,50000 +74499,both interview and exam,male,59,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +74500,both interview and exam,male,6,NA,mexican american,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,12500 +74501,both interview and exam,female,10,NA,white,1,131,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +74502,both interview and exam,male,27,NA,black,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,NA,TRUE,7500 +74503,both interview and exam,female,47,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,30000 +74504,both interview and exam,female,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,22500 +74505,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,100000 +74506,both interview and exam,female,4,NA,mexican american,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +74507,both interview and exam,male,14,NA,mexican american,2,176,NA,NA,FALSE,FALSE,3,8,NA,NA,NA,FALSE,22500 +74508,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74509,both interview and exam,female,48,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +74510,both interview and exam,male,64,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +74511,both interview and exam,male,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74512,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,1,married,NA,TRUE,40000 +74513,both interview and exam,male,15,NA,white,2,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,NA +74514,both interview and exam,female,0,5,other hispanic,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74515,both interview and exam,female,0,9,mexican american,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74516,both interview and exam,female,16,NA,mexican american,2,202,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +74517,both interview and exam,male,1,14,black,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74518,both interview and exam,male,0,9,other,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +74519,both interview and exam,female,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,7500 +74520,both interview and exam,male,6,NA,asian,1,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +74521,both interview and exam,female,21,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,2500 +74522,both interview and exam,male,2,NA,mexican american,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74523,both interview and exam,female,61,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +74524,both interview and exam,male,47,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,FALSE,17500 +74525,both interview and exam,male,11,NA,other,2,137,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +74526,both interview and exam,female,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +74527,both interview and exam,male,0,5,black,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74528,both interview and exam,female,1,15,mexican american,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +74529,both interview and exam,male,51,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,30000 +74530,both interview and exam,female,45,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,3,married,NA,FALSE,22500 +74531,both interview and exam,male,72,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,17500 +74532,both interview and exam,male,25,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,17500 +74533,both interview and exam,female,0,8,white,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74534,both interview and exam,male,65,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +74535,both interview and exam,male,1,22,other hispanic,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +74536,both interview and exam,male,65,NA,other hispanic,1,NA,TRUE,TRUE,FALSE,TRUE,55,NA,4,married,NA,TRUE,30000 +74537,both interview and exam,female,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,12500 +74538,both interview and exam,female,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +74539,both interview and exam,male,55,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +74540,both interview and exam,female,11,NA,other hispanic,2,134,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +74541,both interview and exam,female,5,NA,black,1,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74542,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,2500 +74543,both interview and exam,male,40,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +74544,both interview and exam,male,10,NA,black,1,126,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +74545,both interview and exam,female,8,NA,white,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +74546,both interview and exam,female,27,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,2,never_married,no,FALSE,30000 +74547,both interview and exam,male,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +74548,both interview and exam,female,63,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,4,divorced,NA,FALSE,17500 +74549,both interview and exam,female,55,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,NA,TRUE,70000 +74550,both interview and exam,female,4,NA,black,1,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74551,both interview and exam,female,32,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +74552,both interview and exam,female,44,NA,black,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,never_married,no,TRUE,22500 +74553,both interview and exam,male,6,NA,white,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +74554,both interview and exam,female,35,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +74555,interview only,female,2,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74556,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +74557,both interview and exam,female,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,30000 +74558,both interview and exam,female,1,12,black,2,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74559,both interview and exam,female,19,NA,other hispanic,1,234,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,70000 +74560,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +74561,both interview and exam,male,1,18,mexican american,2,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74562,both interview and exam,male,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +74563,both interview and exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +74564,both interview and exam,female,26,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,unable to ascertain,TRUE,30000 +74565,both interview and exam,male,66,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,NA,FALSE,NA +74566,both interview and exam,female,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,12500 +74567,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +74568,both interview and exam,male,8,NA,other hispanic,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +74569,both interview and exam,male,19,NA,white,1,233,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,40000 +74570,both interview and exam,female,63,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +74571,both interview and exam,male,53,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74572,both interview and exam,female,2,NA,black,1,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74573,both interview and exam,female,4,NA,black,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74574,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +74575,both interview and exam,female,16,NA,other hispanic,2,198,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +74576,both interview and exam,female,73,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +74577,interview only,female,3,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74578,both interview and exam,male,4,NA,other hispanic,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74579,both interview and exam,male,51,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,living_with_partner,NA,TRUE,12500 +74580,both interview and exam,female,13,NA,other hispanic,2,160,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,22500 +74581,both interview and exam,male,75,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +74582,both interview and exam,female,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +74583,both interview and exam,female,60,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +74584,both interview and exam,male,10,NA,black,2,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +74585,interview only,female,0,1,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74586,both interview and exam,male,24,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,30000 +74587,both interview and exam,male,66,NA,mexican american,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +74588,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +74589,both interview and exam,male,67,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,22500 +74590,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +74591,both interview and exam,male,73,NA,black,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,22500 +74592,both interview and exam,male,1,15,black,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74593,both interview and exam,male,0,1,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74594,both interview and exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,50000 +74595,both interview and exam,male,5,NA,mexican american,1,62,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +74596,both interview and exam,female,45,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +74597,both interview and exam,male,0,6,mexican american,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +74598,both interview and exam,male,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +74599,interview only,male,6,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +74600,both interview and exam,female,66,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +74601,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +74602,both interview and exam,female,18,NA,black,1,218,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,70000 +74603,both interview and exam,male,12,NA,asian,1,149,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +74604,interview only,male,3,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74605,both interview and exam,female,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74606,both interview and exam,male,9,NA,mexican american,1,112,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,NA +74607,both interview and exam,male,68,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,NA +74608,both interview and exam,male,14,NA,mexican american,2,177,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +74609,both interview and exam,female,46,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,87500 +74610,both interview and exam,female,0,3,white,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74611,both interview and exam,male,64,NA,mexican american,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +74612,both interview and exam,female,47,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +74613,both interview and exam,female,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,17500 +74614,both interview and exam,female,12,NA,mexican american,2,147,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +74615,both interview and exam,female,4,NA,black,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74616,both interview and exam,male,19,NA,mexican american,2,239,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +74617,both interview and exam,male,17,NA,black,1,211,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +74618,both interview and exam,female,0,9,mexican american,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74619,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +74620,both interview and exam,female,14,NA,black,1,175,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +74621,both interview and exam,female,1,16,asian,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 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hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,22500 +74632,both interview and exam,male,46,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74633,both interview and exam,female,56,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,living_with_partner,NA,TRUE,60000 +74634,both interview and exam,female,0,9,black,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74635,both interview and exam,female,2,NA,white,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +74636,both interview and exam,female,60,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,divorced,NA,TRUE,100000 +74637,both interview and exam,male,11,NA,white,1,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +74638,both interview and exam,male,34,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,living_with_partner,NA,TRUE,87500 +74639,both interview and exam,male,51,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +74640,both interview and exam,male,14,NA,white,1,181,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +74641,both interview and exam,male,33,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +74642,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +74643,both interview and exam,male,2,NA,black,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74644,both interview and exam,female,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,NA +74645,both interview and exam,female,68,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +74646,both interview and exam,male,49,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +74647,both interview and exam,female,15,NA,white,2,191,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +74648,both interview and exam,female,18,NA,black,2,221,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,17500 +74649,both interview and exam,female,4,NA,black,2,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74650,both interview and exam,male,56,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,4,married,NA,FALSE,30000 +74651,both interview and exam,male,8,NA,white,2,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,7500 +74652,both interview and exam,female,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,no,FALSE,30000 +74653,both interview and exam,female,29,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,17500 +74654,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +74655,both interview and exam,female,36,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,never_married,no,TRUE,100000 +74656,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74657,both interview and exam,male,3,NA,white,2,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74658,both interview and exam,female,12,NA,mexican american,1,155,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,NA +74659,both interview and exam,male,12,NA,white,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +74660,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +74661,both interview and exam,male,65,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +74662,both interview and exam,female,5,NA,other hispanic,2,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74663,both interview and exam,male,52,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,30000 +74664,interview only,female,8,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +74665,both interview and exam,male,16,NA,mexican american,1,198,NA,NA,FALSE,FALSE,12.5,11,NA,NA,NA,TRUE,30000 +74666,both interview and exam,male,13,NA,asian,1,161,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +74667,both interview and exam,male,6,NA,black,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +74668,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,22500 +74669,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,100000 +74670,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,17500 +74671,both interview and exam,female,12,NA,other hispanic,2,155,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,50000 +74672,both interview and exam,male,17,NA,mexican american,2,213,FALSE,NA,FALSE,FALSE,17.5,10,NA,NA,NA,TRUE,30000 +74673,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +74674,both interview and exam,female,67,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,widowed,NA,FALSE,17500 +74675,both interview and exam,female,18,NA,white,1,220,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +74676,both interview and exam,male,75,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,married,NA,TRUE,100000 +74677,both interview and 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and exam,male,1,17,mexican american,2,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74820,both interview and exam,male,1,18,black,1,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74821,both interview and exam,female,4,NA,black,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74822,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,100000 +74823,both interview and exam,male,67,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +74824,both interview and exam,female,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +74825,both interview and exam,male,16,NA,mexican american,2,203,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +74826,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74827,both interview and exam,female,0,11,white,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74828,both interview and exam,male,8,NA,other,1,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +74829,both interview and exam,female,27,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,yes,TRUE,7500 +74830,both interview and exam,male,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +74831,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74832,both interview and exam,male,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,87500 +74833,both interview and exam,male,16,NA,white,2,196,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +74834,both interview and exam,male,48,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,living_with_partner,NA,FALSE,NA +74835,both interview and exam,male,7,NA,white,1,95,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,70000 +74836,both interview and exam,female,4,NA,black,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74837,both interview and exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +74838,both interview and exam,female,8,NA,other hispanic,1,97,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +74839,both interview and exam,male,47,NA,white,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +74840,both interview and exam,male,10,NA,mexican american,1,121,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +74841,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,widowed,NA,TRUE,NA +74842,both interview and exam,female,2,NA,white,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +74843,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,no,FALSE,7500 +74844,both interview and exam,male,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +74845,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +74846,both interview and exam,female,2,NA,mexican american,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74847,both interview and exam,female,1,20,asian,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74848,both interview and exam,female,5,NA,white,2,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74849,both interview and exam,male,9,NA,other hispanic,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +74850,both interview and exam,female,2,NA,white,2,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74851,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,NA +74852,both interview and exam,female,12,NA,black,1,148,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +74853,interview only,female,80,NA,asian,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +74854,both interview and exam,female,18,NA,other hispanic,2,225,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,22500 +74855,both interview and exam,male,16,NA,black,2,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +74856,both interview and exam,male,5,NA,black,1,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74857,both interview and exam,female,9,NA,other hispanic,2,109,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +74858,both interview and exam,male,2,NA,mexican american,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +74859,both interview and exam,female,55,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +74860,both interview and exam,male,40,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,70000 +74861,both interview and exam,male,60,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,7500 +74862,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +74863,both interview and exam,male,1,20,white,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74864,both interview and exam,female,11,NA,mexican american,2,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,30000 +74865,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +74866,both interview and exam,male,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +74867,both interview and exam,female,53,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +74868,both interview and exam,female,9,NA,mexican american,1,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,22500 +74869,both interview and exam,female,66,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,30000 +74870,both interview and exam,female,11,NA,black,1,137,NA,NA,FALSE,FALSE,7.5,5,NA,NA,NA,TRUE,22500 +74871,both interview and exam,male,8,NA,black,1,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,2500 +74872,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +74873,both interview and exam,female,1,17,black,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74874,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74875,both interview and exam,female,5,NA,black,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74876,both interview and exam,male,2,NA,other hispanic,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74877,both interview and exam,female,14,NA,mexican american,1,179,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,NA +74878,both interview and exam,female,69,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,87500 +74879,both interview and exam,female,43,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,no,TRUE,100000 +74880,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +74881,both interview and exam,female,14,NA,white,1,180,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +74882,both interview and exam,male,25,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,married,NA,FALSE,50000 +74883,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +74884,both interview and exam,male,0,7,white,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +74885,both interview and exam,female,57,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +74886,both interview and exam,female,18,NA,black,1,223,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,30000 +74887,both interview and exam,male,13,NA,black,1,164,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +74888,interview only,male,21,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +74889,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +74890,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +74891,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,70000 +74892,both interview and exam,female,0,0,other,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74893,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74894,both interview and exam,female,6,NA,asian,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +74895,both interview and exam,female,15,NA,white,2,191,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,70000 +74896,both interview and exam,male,6,NA,black,1,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +74897,both interview and exam,female,46,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,FALSE,22500 +74898,both interview and exam,female,2,NA,mexican american,1,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +74899,both interview and exam,female,0,7,other hispanic,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74900,both interview and exam,female,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +74901,both interview and exam,male,55,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +74902,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +74903,both interview and exam,male,11,NA,black,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,NA +74904,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +74905,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74906,both interview and exam,male,0,6,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +74907,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +74908,both interview and exam,male,0,4,black,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +74909,both interview and exam,male,64,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,FALSE,50000 +74910,both interview and exam,female,19,NA,black,1,231,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,7500 +74911,both interview and exam,female,13,NA,mexican american,2,166,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,NA +74912,both interview and exam,male,12,NA,asian,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,NA +74913,both interview and exam,female,14,NA,black,2,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +74914,both interview and exam,male,9,NA,mexican american,2,118,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +74915,both interview and exam,female,4,NA,asian,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +74916,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +74917,both interview and exam,female,11,NA,white,2,137,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +74918,both interview and exam,female,49,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,NA,FALSE,40000 +74919,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +74920,both interview and exam,female,6,NA,black,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +74921,both interview and exam,male,0,10,mexican american,1,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74922,both interview and exam,male,3,NA,black,2,46,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74923,both interview and exam,male,24,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +74924,both interview and exam,male,1,17,white,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74925,both interview and exam,female,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,30000 +74926,both interview and exam,female,6,NA,black,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +74927,both interview and exam,male,17,NA,black,1,209,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +74928,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,60000 +74929,both interview and exam,female,66,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +74930,both interview and exam,female,11,NA,white,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +74931,both interview and exam,male,53,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +74932,both interview and exam,male,32,NA,other,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +74933,both interview and exam,female,57,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +74934,both interview and exam,male,14,NA,black,1,169,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +74935,both interview and exam,male,20,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,never_married,NA,TRUE,NA +74936,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +74937,both interview and exam,male,74,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +74938,both interview and exam,female,52,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +74939,both interview and exam,male,13,NA,asian,1,156,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +74940,both interview and exam,male,80,NA,black,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,TRUE,40000 +74941,both interview and exam,female,59,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +74942,both interview and exam,female,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +74943,both interview and exam,male,19,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,40000 +74944,both interview and exam,female,2,NA,black,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +74945,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +74946,both interview and exam,male,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,2500 +74947,both interview and exam,female,3,NA,other,1,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74948,both interview and exam,female,33,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +74949,both interview and exam,male,8,NA,white,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 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exam,male,7,NA,black,1,91,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,2500 +74960,both interview and exam,female,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +74961,both interview and exam,male,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +74962,both interview and exam,male,15,NA,mexican american,1,181,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,NA +74963,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +74964,both interview and exam,female,2,NA,mexican american,2,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +74965,both interview and exam,male,26,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +74966,both interview and exam,male,3,NA,other,1,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +74967,both interview and exam,female,0,6,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +74968,both interview and exam,female,10,NA,black,1,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +74969,both interview and exam,male,22,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,never_married,NA,TRUE,22500 +74970,both interview and exam,male,1,16,other,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74971,both interview and exam,female,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +74972,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74973,both interview and exam,female,11,NA,mexican american,2,143,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +74974,both interview and exam,male,48,NA,white,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +74975,interview only,male,17,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +74976,both interview and exam,female,1,16,other,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +74977,both interview and exam,female,20,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,never_married,no,TRUE,100000 +74978,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +74979,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,22500 +74980,both interview and exam,male,14,NA,white,1,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +74981,both interview and exam,male,33,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,12500 +74982,both interview and exam,male,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +74983,both interview and exam,female,63,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,2,married,NA,TRUE,30000 +74984,both interview and exam,male,64,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,never_married,NA,FALSE,NA +74985,both interview and exam,female,66,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,widowed,NA,FALSE,12500 +74986,both interview and exam,female,17,NA,mexican american,2,214,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,FALSE,22500 +74987,both interview and exam,female,10,NA,black,2,132,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +74988,both interview and exam,female,8,NA,white,1,103,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +74989,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,NA +74990,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +74991,both interview and exam,male,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,17500 +74992,both interview and exam,female,14,NA,white,2,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +74993,both interview and exam,male,5,NA,white,2,62,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74994,interview only,female,7,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +74995,both interview and exam,male,0,6,other hispanic,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +74996,both interview and exam,male,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +74997,both interview and 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exam,female,19,NA,asian,2,233,FALSE,NA,FALSE,TRUE,17.5,14,NA,NA,NA,TRUE,100000 +75179,both interview and exam,female,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,12500 +75180,both interview and exam,male,4,NA,other,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +75181,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +75182,both interview and exam,male,8,NA,mexican american,2,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +75183,both interview and exam,male,2,NA,black,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75184,both interview and exam,male,8,NA,asian,2,100,NA,NA,FALSE,FALSE,7.5,2,NA,NA,NA,TRUE,100000 +75185,both interview and exam,male,18,NA,black,2,219,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +75186,both interview and exam,male,11,NA,black,1,141,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +75187,both interview and exam,female,40,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,separated,no,TRUE,87500 +75188,both interview and exam,female,35,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,40000 +75189,both interview and exam,male,59,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +75190,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +75191,both interview and exam,female,79,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,55,NA,1,widowed,NA,FALSE,70000 +75192,both interview and exam,female,2,NA,asian,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75193,both interview and exam,female,57,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,divorced,NA,TRUE,12500 +75194,both interview and exam,male,11,NA,other hispanic,2,142,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,7500 +75195,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +75196,both interview and exam,female,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,100000 +75197,interview 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exam,male,65,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +75208,both interview and exam,male,9,NA,black,2,117,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +75209,both interview and exam,female,18,NA,asian,1,222,FALSE,NA,FALSE,TRUE,17.5,13,NA,NA,NA,TRUE,7500 +75210,both interview and exam,female,7,NA,mexican american,2,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,22500 +75211,both interview and exam,male,37,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +75212,both interview and exam,male,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +75213,both interview and exam,female,40,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,17500 +75214,interview only,male,72,NA,white,NA,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,2500 +75215,both interview and exam,female,8,NA,black,1,103,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +75216,both interview and exam,male,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,30000 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exam,female,29,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,no,TRUE,87500 +75284,both interview and exam,female,13,NA,white,2,167,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +75285,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,12500 +75286,both interview and exam,male,13,NA,white,2,163,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +75287,both interview and exam,male,75,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +75288,both interview and exam,male,19,NA,white,1,237,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,40000 +75289,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +75290,both interview and exam,male,21,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +75291,both interview and exam,female,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,yes,TRUE,17500 +75292,both interview and exam,male,15,NA,mexican 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exam,female,77,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +75339,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +75340,both interview and exam,female,22,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,60000 +75341,both interview and exam,female,14,NA,white,2,176,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +75342,both interview and exam,male,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +75343,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +75344,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +75345,both interview and exam,female,54,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +75346,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75347,both interview and exam,female,62,NA,mexican 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exam,male,8,NA,black,2,108,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +75395,both interview and exam,male,53,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +75396,both interview and exam,male,2,NA,white,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75397,both interview and exam,female,62,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,55,NA,3,widowed,NA,TRUE,22500 +75398,both interview and exam,female,9,NA,black,1,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +75399,both interview and exam,female,27,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,no,TRUE,87500 +75400,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,100000 +75401,both interview and exam,female,0,8,black,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +75402,both interview and exam,female,1,14,white,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +75403,both interview and exam,female,27,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,30000 +75404,both 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exam,female,18,NA,black,2,221,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,87500 +75414,both interview and exam,male,56,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +75415,both interview and exam,female,24,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,no,TRUE,30000 +75416,both interview and exam,male,61,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +75417,both interview and exam,female,41,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,87500 +75418,both interview and exam,male,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +75419,both interview and exam,female,28,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,never_married,no,FALSE,17500 +75420,both interview and exam,male,6,NA,black,1,85,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +75421,both interview and exam,male,7,NA,asian,2,85,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +75422,both interview and 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exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +75617,both interview and exam,male,2,NA,white,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75618,both interview and exam,male,13,NA,mexican american,2,159,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,40000 +75619,both interview and exam,male,36,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,100000 +75620,both interview and exam,female,52,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +75621,both interview and exam,female,59,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +75622,both interview and exam,female,8,NA,white,1,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +75623,both interview and exam,male,9,NA,white,2,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +75624,both interview and exam,female,21,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,never_married,no,TRUE,50000 +75625,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +75626,both interview and exam,female,5,NA,other hispanic,2,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +75627,both interview and exam,male,1,15,black,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75628,both interview and exam,female,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +75629,both interview and exam,female,9,NA,other hispanic,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +75630,both interview and exam,female,59,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +75631,both interview and exam,female,72,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +75632,both interview and exam,female,3,NA,asian,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +75633,both interview and exam,male,10,NA,mexican american,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,NA +75634,both interview and exam,male,13,NA,black,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +75635,both interview and exam,female,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +75636,both interview and exam,female,35,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +75637,both interview and exam,female,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,100000 +75638,both interview and exam,female,16,NA,black,2,197,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +75639,both interview and exam,male,15,NA,black,1,184,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +75640,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +75641,both interview and exam,female,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75642,both interview and exam,male,1,22,mexican american,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +75643,both interview and exam,female,43,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,FALSE,7500 +75644,both interview and exam,male,69,NA,asian,1,NA,TRUE,TRUE,FALSE,TRUE,45,NA,2,married,NA,TRUE,NA +75645,both interview and exam,male,6,NA,black,1,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +75646,both interview and exam,male,20,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +75647,both interview and exam,male,28,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +75648,both interview and exam,female,18,NA,other hispanic,1,219,FALSE,NA,FALSE,FALSE,0.5,9,NA,NA,NA,FALSE,22500 +75649,both interview and exam,male,11,NA,white,1,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +75650,both interview and exam,female,13,NA,mexican american,2,159,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +75651,both interview and exam,male,1,21,asian,2,21,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,100000 +75652,both interview and exam,male,4,NA,mexican american,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +75653,both interview and exam,male,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +75654,both interview and exam,female,49,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +75655,both interview and exam,male,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +75656,both interview and exam,female,1,12,white,2,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +75657,both interview and exam,female,12,NA,white,2,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +75658,both interview and exam,male,8,NA,black,2,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +75659,both interview and exam,male,15,NA,black,2,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +75660,both interview and exam,female,59,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +75661,both interview and exam,male,4,NA,asian,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +75662,both interview and exam,female,44,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +75663,both interview and exam,female,54,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +75664,both interview and exam,female,31,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,7500 +75665,both interview and exam,female,12,NA,other hispanic,2,152,NA,NA,FALSE,FALSE,3,7,NA,NA,NA,FALSE,22500 +75666,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75667,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +75668,both interview and exam,male,10,NA,mexican american,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +75669,both interview and exam,male,64,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,divorced,NA,TRUE,100000 +75670,both interview and exam,female,27,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,50000 +75671,both interview and exam,male,11,NA,asian,1,144,NA,NA,FALSE,FALSE,3,6,NA,NA,NA,TRUE,60000 +75672,interview only,male,1,13,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +75673,interview only,female,6,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +75674,both interview and exam,male,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,17500 +75675,both interview and exam,female,17,NA,black,1,208,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,NA +75676,both interview and exam,female,6,NA,asian,1,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +75677,both interview and exam,female,10,NA,black,2,125,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +75678,both interview and exam,male,10,NA,other hispanic,2,126,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +75679,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +75680,both interview and exam,female,15,NA,white,2,181,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +75681,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,40000 +75682,both interview and exam,male,29,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +75683,both interview and exam,male,23,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,NA +75684,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +75685,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,2500 +75686,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +75687,interview only,female,20,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,100000 +75688,both interview and exam,female,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,2,divorced,NA,FALSE,7500 +75689,both interview and exam,male,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +75690,both interview and exam,male,34,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,40000 +75691,both interview and exam,female,70,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +75692,both interview and exam,male,18,NA,white,2,218,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +75693,both interview and exam,male,0,2,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +75694,both interview and exam,male,9,NA,other hispanic,2,112,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +75695,both interview and exam,female,74,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,widowed,NA,FALSE,30000 +75696,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,widowed,NA,TRUE,12500 +75697,both interview and exam,female,10,NA,white,1,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,60000 +75698,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +75699,both interview and exam,female,62,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,1,never_married,NA,FALSE,17500 +75700,both interview and exam,male,68,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,divorced,NA,FALSE,17500 +75701,both interview and exam,female,2,NA,white,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75702,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,divorced,NA,TRUE,50000 +75703,both interview and exam,male,3,NA,black,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +75704,both interview and exam,male,24,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +75705,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +75706,both interview and exam,female,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +75707,both interview and exam,female,14,NA,other hispanic,2,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,17500 +75708,both interview and exam,female,5,NA,black,1,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +75709,both interview and exam,female,30,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,no,TRUE,60000 +75710,both interview and exam,male,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75711,both interview and exam,male,12,NA,mexican american,1,150,NA,NA,FALSE,FALSE,3,5,NA,NA,NA,TRUE,87500 +75712,both interview and exam,male,11,NA,white,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +75713,both interview and exam,female,12,NA,asian,1,145,NA,NA,FALSE,FALSE,7.5,6,NA,NA,NA,TRUE,7500 +75714,both interview and exam,male,54,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +75715,both interview and exam,male,12,NA,other hispanic,2,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,NA +75716,both interview and exam,male,2,NA,mexican american,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +75717,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +75718,both interview and exam,male,0,11,other,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75719,both interview and exam,male,2,NA,other,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +75720,both interview and exam,male,6,NA,mexican american,2,72,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,60000 +75721,both interview and exam,male,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +75722,both interview and exam,male,15,NA,black,1,188,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +75723,both interview and exam,female,55,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,never_married,NA,TRUE,17500 +75724,both interview and exam,male,66,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,50000 +75725,both interview and exam,male,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +75726,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +75727,both interview and exam,male,0,0,white,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +75728,both interview and exam,male,10,NA,white,2,131,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +75729,both interview and exam,female,11,NA,mexican american,1,137,NA,NA,FALSE,FALSE,12.5,4,NA,NA,NA,FALSE,50000 +75730,both interview and exam,male,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +75731,both interview and exam,male,8,NA,other hispanic,1,106,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,2500 +75732,both interview and exam,male,15,NA,mexican american,2,190,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +75733,both interview and exam,male,56,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +75734,both interview and exam,male,18,NA,black,1,223,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,87500 +75735,both interview and exam,male,19,NA,asian,2,237,TRUE,FALSE,FALSE,TRUE,17.5,13,NA,NA,NA,TRUE,100000 +75736,both interview and exam,male,0,5,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75737,both interview and exam,female,20,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +75738,both interview and exam,male,47,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,87500 +75739,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +75740,both interview and exam,female,5,NA,black,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +75741,both interview and exam,female,11,NA,white,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +75742,both interview and exam,male,37,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,70000 +75743,both interview and exam,female,36,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,no,TRUE,7500 +75744,both interview and exam,female,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +75745,both interview and exam,female,44,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,no,TRUE,40000 +75746,both interview and exam,female,2,NA,other,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +75747,both interview and exam,male,18,NA,asian,2,221,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,87500 +75748,both interview and exam,female,80,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,60000 +75749,both interview and exam,male,69,NA,other hispanic,2,NA,TRUE,FALSE,FALSE,TRUE,45,NA,3,divorced,NA,TRUE,7500 +75750,both interview and exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75751,both interview and exam,male,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75752,both interview and exam,female,11,NA,white,2,141,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +75753,both interview and exam,male,19,NA,mexican american,1,238,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +75754,both interview and exam,male,55,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +75755,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +75756,both interview and exam,female,5,NA,white,2,70,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,NA +75757,both interview and exam,female,7,NA,mexican american,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +75758,both interview and exam,male,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +75759,both interview and exam,male,11,NA,other hispanic,2,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +75760,both interview and exam,female,12,NA,asian,1,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +75761,both interview and exam,female,6,NA,black,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +75762,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,70000 +75763,both interview and exam,male,32,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,30000 +75764,both interview and exam,female,2,NA,other hispanic,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +75765,both interview and exam,female,7,NA,black,1,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +75766,both interview and exam,female,16,NA,white,2,195,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +75767,both interview and exam,female,9,NA,mexican american,2,113,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,40000 +75768,both interview and exam,male,46,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,35,NA,3,married,NA,TRUE,70000 +75769,both interview and exam,male,72,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +75770,both interview and exam,female,10,NA,white,2,127,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +75771,both interview and exam,male,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +75772,both interview and exam,female,15,NA,white,1,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 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exam,male,71,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +75979,both interview and exam,female,6,NA,black,1,82,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +75980,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +75981,both interview and exam,female,5,NA,white,2,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +75982,both interview and exam,female,75,NA,white,2,NA,FALSE,NA,FALSE,FALSE,45,NA,2,widowed,NA,TRUE,12500 +75983,both interview and exam,male,6,NA,other,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +75984,both interview and exam,male,15,NA,black,2,180,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +75985,both interview and exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,17500 +75986,both interview and exam,male,55,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,NA,FALSE,50000 +75987,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,NA +75988,both interview and exam,male,18,NA,black,1,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +75989,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +75990,interview only,male,9,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +75991,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +75992,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +75993,both interview and exam,male,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +75994,both interview and exam,female,0,9,mexican american,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +75995,both interview and exam,male,6,NA,white,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +75996,both interview and exam,male,61,NA,black,2,NA,FALSE,NA,FALSE,FALSE,35,NA,3,living_with_partner,NA,TRUE,NA +75997,both interview and exam,female,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +75998,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +75999,both interview and exam,male,19,NA,asian,2,238,FALSE,NA,FALSE,FALSE,3,14,NA,NA,NA,TRUE,7500 +76000,both interview and exam,female,0,2,other hispanic,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76001,both interview and exam,male,16,NA,black,2,204,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +76002,both interview and exam,female,0,5,mexican american,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76003,both interview and exam,female,10,NA,white,2,129,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +76004,both interview and exam,female,58,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,2500 +76005,both interview and exam,female,14,NA,mexican american,1,176,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,NA +76006,both interview and exam,female,32,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,7500 +76007,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76008,both interview and exam,female,31,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,40000 +76009,both interview and exam,female,11,NA,black,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +76010,both interview and exam,male,68,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,22500 +76011,both interview and exam,female,32,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,17500 +76012,both interview and exam,male,59,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,1,married,NA,TRUE,60000 +76013,both interview and exam,male,1,15,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +76014,both interview and exam,female,16,NA,other hispanic,2,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +76015,both interview and exam,female,30,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,100000 +76016,both interview and exam,male,79,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +76017,both interview and exam,male,2,NA,asian,1,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76018,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,30000 +76019,both interview and exam,male,29,NA,other hispanic,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,2500 +76020,both interview and exam,male,32,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +76021,both interview and exam,female,0,5,mexican american,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76022,both interview and exam,male,3,NA,white,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +76023,both interview and exam,male,67,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76024,both interview and exam,female,40,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +76025,both interview and exam,male,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +76026,both interview and exam,female,9,NA,white,2,114,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +76027,both interview and exam,female,5,NA,asian,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +76028,both interview and exam,female,57,NA,black,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,never_married,NA,TRUE,22500 +76029,both interview and exam,male,3,NA,asian,2,46,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76030,both interview and exam,male,32,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76031,both interview and exam,male,4,NA,white,2,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76032,both interview and exam,male,18,NA,mexican american,1,220,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,50000 +76033,both interview and exam,female,69,NA,other 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exam,female,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,40000 +76043,both interview and exam,female,64,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +76044,both interview and exam,male,11,NA,mexican american,1,140,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,17500 +76045,both interview and exam,female,12,NA,mexican american,2,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +76046,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +76047,both interview and exam,male,9,NA,white,2,114,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +76048,both interview and exam,male,49,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +76049,both interview and exam,male,54,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,60000 +76050,both interview and exam,male,7,NA,black,2,88,NA,NA,FALSE,FALSE,7.5,1,NA,NA,NA,TRUE,12500 +76051,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,NA +76052,both interview and exam,female,10,NA,mexican american,1,121,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,22500 +76053,both interview and exam,female,5,NA,other hispanic,1,66,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,TRUE,100000 +76054,both interview and exam,female,22,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,no,TRUE,17500 +76055,both interview and exam,female,18,NA,black,1,224,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,7500 +76056,both interview and exam,male,17,NA,black,1,204,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,7500 +76057,both interview and exam,male,18,NA,white,1,221,FALSE,NA,FALSE,TRUE,12.5,13,NA,NA,NA,TRUE,40000 +76058,both interview and exam,female,0,10,other hispanic,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +76059,both interview and exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,70000 +76060,both interview and exam,female,32,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76061,both interview and exam,female,10,NA,black,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +76062,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,40000 +76063,both interview and exam,female,0,3,asian,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +76064,both interview and exam,male,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,70000 +76065,both interview and exam,male,1,21,asian,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76066,both interview and exam,male,17,NA,other hispanic,1,216,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +76067,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +76068,both interview and exam,female,13,NA,black,1,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +76069,both interview and exam,male,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 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interview and exam,male,25,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,22500 +76416,both interview and exam,male,6,NA,mexican american,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +76417,both interview and exam,male,4,NA,black,1,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76418,both interview and exam,male,40,NA,black,1,NA,TRUE,TRUE,FALSE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76419,both interview and exam,male,7,NA,black,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +76420,both interview and exam,female,2,NA,white,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76421,both interview and exam,female,0,3,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76422,both interview and exam,male,69,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +76423,both interview and exam,female,74,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +76424,both interview and exam,male,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +76425,both interview and exam,male,29,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,87500 +76426,both interview and exam,female,3,NA,black,1,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76427,both interview and exam,male,37,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,50000 +76428,interview only,male,6,NA,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +76429,both interview and exam,male,63,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,NA +76430,interview only,male,1,17,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76431,both interview and exam,male,13,NA,mexican american,2,166,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +76432,both interview and exam,male,18,NA,white,1,220,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +76433,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +76434,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,NA +76435,both interview and exam,female,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76436,both interview and exam,male,78,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +76437,both interview and exam,male,64,NA,other hispanic,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +76438,interview only,female,59,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +76439,both interview and exam,male,28,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,30000 +76440,both interview and exam,female,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +76441,both interview and exam,female,7,NA,mexican american,1,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +76442,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +76443,both interview and exam,male,63,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,7500 +76444,both interview and exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76445,both interview and exam,male,5,NA,other,2,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +76446,both interview and exam,female,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,30000 +76447,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +76448,interview only,male,15,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,17500 +76449,both interview and exam,male,0,1,mexican american,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76450,both interview and exam,male,6,NA,white,2,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +76451,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +76452,both interview and exam,male,2,NA,white,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76453,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76454,both interview and exam,male,16,NA,asian,1,195,NA,NA,FALSE,FALSE,12.5,8,NA,NA,NA,TRUE,100000 +76455,both interview and exam,female,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +76456,both interview and exam,male,7,NA,white,2,87,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +76457,both interview and exam,female,4,NA,white,1,54,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,100000 +76458,both interview and exam,male,17,NA,black,1,216,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +76459,both interview and exam,male,33,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +76460,interview only,female,2,NA,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76461,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +76462,both interview and exam,female,0,0,mexican american,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76463,both interview and exam,male,6,NA,white,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +76464,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76465,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +76466,both interview and exam,female,39,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,30000 +76467,both interview and exam,female,5,NA,black,1,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76468,both interview and exam,male,73,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,70000 +76469,both interview and exam,male,72,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +76470,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,NA +76471,both interview and exam,female,2,NA,other,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +76472,both interview and exam,female,52,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +76473,both interview and exam,male,4,NA,mexican american,1,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +76474,both interview and exam,female,17,NA,asian,2,205,FALSE,NA,FALSE,TRUE,3,11,NA,NA,NA,TRUE,NA +76475,interview only,female,72,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +76476,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,50000 +76477,both interview and exam,female,73,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,separated,NA,FALSE,50000 +76478,both interview and exam,male,4,NA,other,2,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76479,both interview and exam,male,14,NA,white,2,176,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +76480,both interview and exam,female,24,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +76481,both interview and exam,female,67,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,TRUE,100000 +76482,both interview and exam,female,42,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +76483,both interview and exam,male,12,NA,mexican american,2,147,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +76484,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,40000 +76485,both interview and exam,female,12,NA,mexican american,2,155,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,12500 +76486,both interview and exam,female,24,NA,black,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,never_married,no,TRUE,30000 +76487,both interview and exam,female,23,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,never_married,no,TRUE,30000 +76488,both interview and exam,male,41,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,NA,FALSE,22500 +76489,both interview and exam,male,39,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,70000 +76490,both interview and exam,female,68,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +76491,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,yes,TRUE,40000 +76492,interview only,female,55,NA,white,NA,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,100000 +76493,both interview and exam,male,38,NA,black,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,living_with_partner,NA,TRUE,NA +76494,both interview and exam,male,29,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,divorced,NA,TRUE,22500 +76495,both interview and exam,male,3,NA,asian,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76496,both interview and exam,female,23,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,separated,no,FALSE,7500 +76497,both interview and exam,female,7,NA,mexican american,1,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +76498,both interview and exam,male,6,NA,asian,2,81,NA,NA,FALSE,FALSE,7.5,1,NA,NA,NA,TRUE,40000 +76499,both interview and exam,female,7,NA,black,1,95,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +76500,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +76501,both interview and exam,female,9,NA,other hispanic,2,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,40000 +76502,both interview and exam,male,10,NA,asian,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,NA +76503,both interview and exam,female,15,NA,other,2,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +76504,both interview and exam,male,3,NA,asian,2,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76505,both interview and exam,male,14,NA,black,2,169,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,22500 +76506,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +76507,both interview and exam,female,2,NA,black,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76508,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +76509,both interview and exam,male,24,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,NA +76510,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,12500 +76511,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +76512,both interview and exam,male,13,NA,other hispanic,1,161,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,22500 +76513,both interview and exam,male,15,NA,mexican american,2,186,NA,NA,FALSE,FALSE,12.5,9,NA,NA,NA,FALSE,NA +76514,both interview and exam,female,26,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,no,TRUE,60000 +76515,both interview and exam,female,72,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,1,never_married,NA,FALSE,12500 +76516,interview only,female,2,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76517,interview only,female,11,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,2500 +76518,both interview and exam,male,47,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +76519,both interview and exam,male,17,NA,black,1,209,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,2500 +76520,both interview and exam,male,9,NA,mexican american,1,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,60000 +76521,both interview and exam,female,14,NA,other hispanic,2,180,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,70000 +76522,both interview and exam,female,13,NA,other hispanic,2,167,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,2500 +76523,both interview and exam,female,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,yes,TRUE,NA +76524,both interview and exam,male,18,NA,other hispanic,2,219,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +76525,both interview and exam,female,17,NA,asian,2,213,FALSE,NA,FALSE,FALSE,7.5,11,NA,NA,NA,TRUE,40000 +76526,both interview and exam,male,7,NA,black,1,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +76527,both interview and exam,male,68,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 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exam,male,15,NA,mexican american,1,187,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,7500 +76538,both interview and exam,female,1,23,other hispanic,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76539,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76540,both interview and exam,male,69,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +76541,both interview and exam,male,26,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,2,married,NA,TRUE,30000 +76542,both interview and exam,female,64,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +76543,both interview and exam,male,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +76544,both interview and exam,male,10,NA,mexican american,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,NA +76545,both interview and exam,female,2,NA,black,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +76546,both interview and exam,female,7,NA,black,2,95,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +76547,both interview and exam,male,16,NA,asian,2,197,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +76548,both interview and exam,male,62,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +76549,both interview and exam,male,74,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,7500 +76550,both interview and exam,male,70,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,30000 +76551,both interview and exam,female,56,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,100000 +76552,both interview and exam,female,31,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,yes,TRUE,17500 +76553,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +76554,both interview and exam,female,10,NA,other,2,123,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +76555,both interview and exam,female,2,NA,white,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +76556,both interview and exam,male,45,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,FALSE,60000 +76557,both interview and exam,male,54,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,NA,FALSE,22500 +76558,both interview and exam,female,64,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,87500 +76559,both interview and exam,female,15,NA,white,2,184,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +76560,both interview and exam,male,57,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,50000 +76561,both interview and exam,male,61,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +76562,both interview and exam,female,2,NA,other hispanic,2,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +76563,both interview and exam,female,16,NA,other,2,204,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +76564,both interview and exam,female,2,NA,other hispanic,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +76565,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,87500 +76566,both interview and exam,female,4,NA,mexican american,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +76567,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +76568,both interview and exam,female,64,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,70000 +76569,both interview and exam,male,45,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,17500 +76570,both interview and exam,male,3,NA,black,2,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76571,both interview and exam,male,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,87500 +76572,both interview and exam,female,6,NA,white,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,70000 +76573,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,87500 +76574,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +76575,both interview and exam,female,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76576,both interview and exam,female,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,87500 +76577,both interview and exam,female,23,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,30000 +76578,both interview and exam,male,43,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,living_with_partner,NA,FALSE,50000 +76579,both interview and exam,female,16,NA,mexican american,2,193,NA,NA,FALSE,FALSE,12.5,8,NA,NA,NA,FALSE,12500 +76580,both interview and exam,female,71,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,40000 +76581,both interview and exam,female,13,NA,white,1,161,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,70000 +76582,both interview and exam,male,3,NA,black,2,46,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +76583,both interview and exam,male,15,NA,black,1,192,NA,NA,FALSE,FALSE,7.5,9,NA,NA,NA,TRUE,22500 +76584,both interview and exam,female,49,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76585,both interview and exam,female,6,NA,black,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,60000 +76586,both interview and exam,female,45,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,7500 +76587,both interview and exam,male,62,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,100000 +76588,both interview and exam,female,13,NA,mexican american,2,165,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,22500 +76589,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +76590,both interview and exam,female,67,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,50000 +76591,both interview and exam,female,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +76592,both interview and exam,male,5,NA,mexican american,1,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76593,both interview and exam,male,76,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,widowed,NA,TRUE,7500 +76594,both interview and exam,male,10,NA,white,2,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +76595,both interview and exam,female,11,NA,asian,1,143,NA,NA,FALSE,FALSE,3,6,NA,NA,NA,TRUE,7500 +76596,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +76597,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +76598,both interview and exam,male,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,4,divorced,NA,TRUE,60000 +76599,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +76600,both interview and exam,female,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,yes,TRUE,2500 +76601,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +76602,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +76603,both interview and exam,male,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,2500 +76604,both interview and exam,male,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,22500 +76605,both interview and exam,male,12,NA,other hispanic,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,17500 +76606,both interview and exam,female,57,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,NA,TRUE,100000 +76607,both interview and exam,male,2,NA,other hispanic,1,31,NA,NA,FALSE,TRUE,0.5,NA,NA,NA,NA,TRUE,7500 +76608,both interview and exam,female,38,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,12500 +76609,both interview and exam,female,21,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,never_married,no,TRUE,17500 +76610,both interview and exam,male,7,NA,black,2,90,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +76611,both interview and exam,male,16,NA,mexican american,1,201,NA,NA,FALSE,FALSE,12.5,10,NA,NA,NA,TRUE,22500 +76612,both interview and exam,male,62,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,FALSE,100000 +76613,both interview and exam,male,32,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,100000 +76614,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +76615,both interview and exam,male,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +76616,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +76617,both interview and exam,male,18,NA,black,1,219,FALSE,NA,FALSE,FALSE,12.5,12,NA,NA,NA,TRUE,22500 +76618,both interview and exam,male,9,NA,black,1,121,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +76619,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,12500 +76620,both interview and exam,female,3,NA,asian,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76621,both interview and exam,female,1,21,other,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76622,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +76623,both interview and exam,male,41,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +76624,both interview and exam,male,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +76625,both interview and exam,male,10,NA,black,1,128,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +76626,both interview and exam,female,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76627,both interview and exam,female,76,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +76628,both interview and exam,male,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76629,both interview and exam,male,25,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +76630,both interview and exam,female,39,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,divorced,no,TRUE,7500 +76631,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,17500 +76632,both interview and exam,male,49,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,TRUE,70000 +76633,both interview and exam,male,48,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +76634,both interview and exam,female,43,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,no,TRUE,40000 +76635,both interview and exam,male,59,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +76636,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,yes,TRUE,30000 +76637,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +76638,both interview and exam,female,63,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +76639,both interview and exam,male,43,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,2500 +76640,both interview and exam,female,6,NA,white,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +76641,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,22500 +76642,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,no,TRUE,60000 +76643,both interview and exam,female,41,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,87500 +76644,both interview and exam,male,10,NA,mexican american,1,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +76645,both interview and exam,male,52,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +76646,both interview and exam,female,1,23,mexican american,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +76647,both interview and exam,female,8,NA,white,2,107,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +76648,both interview and exam,female,74,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,NA +76649,both interview and exam,male,59,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,NA,TRUE,12500 +76650,both interview and exam,female,8,NA,white,1,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +76651,both interview and exam,female,0,8,asian,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76652,both interview and exam,male,3,NA,other hispanic,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76653,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +76654,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +76655,both interview and exam,female,64,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,divorced,NA,FALSE,7500 +76656,both interview and exam,female,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,40000 +76657,both interview and exam,female,49,NA,black,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,never_married,NA,TRUE,NA +76658,both interview and exam,female,9,NA,white,2,111,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +76659,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,NA +76660,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,FALSE,FALSE,45,NA,3,widowed,NA,TRUE,12500 +76661,both interview and exam,female,9,NA,black,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +76662,both interview and exam,male,12,NA,mexican american,2,156,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +76663,both interview and exam,male,71,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,NA +76664,both interview and exam,female,0,6,white,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76665,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76666,both interview and exam,female,65,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,widowed,NA,TRUE,12500 +76667,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76668,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76669,both interview and exam,male,63,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,never_married,NA,FALSE,60000 +76670,both interview and exam,male,49,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,70000 +76671,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76672,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +76673,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76674,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,living_with_partner,no,TRUE,22500 +76675,both interview and exam,male,48,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +76676,both interview and exam,male,41,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,50000 +76677,both interview and exam,female,18,NA,mexican american,1,220,FALSE,NA,FALSE,FALSE,12.5,14,NA,NA,NA,TRUE,30000 +76678,both interview and exam,male,10,NA,white,1,123,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +76679,both interview and exam,female,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +76680,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76681,both interview and exam,male,1,16,black,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76682,both interview and exam,female,13,NA,black,1,167,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +76683,both interview and exam,male,15,NA,other hispanic,1,192,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +76684,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +76685,both interview and exam,female,4,NA,mexican american,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76686,both interview and exam,male,34,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,married,NA,FALSE,NA +76687,both interview and exam,male,79,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,22500 +76688,both interview and exam,male,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,40000 +76689,interview only,female,69,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +76690,both interview and exam,female,14,NA,black,2,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,NA +76691,both interview and exam,male,38,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,4,never_married,NA,TRUE,NA +76692,both interview and exam,female,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +76693,both interview and exam,male,7,NA,black,1,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +76694,both interview and exam,male,8,NA,white,2,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +76695,interview only,female,80,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +76696,both interview and exam,female,7,NA,other,1,92,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,2500 +76697,both interview and exam,male,24,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,30000 +76698,both interview and exam,female,66,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,50000 +76699,both interview and exam,female,16,NA,black,1,201,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +76700,both interview and exam,male,53,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,FALSE,17500 +76701,both interview and exam,female,3,NA,black,2,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76702,both interview and exam,male,62,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +76703,both interview and exam,male,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +76704,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +76705,both interview and exam,female,50,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +76706,both interview and exam,male,60,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +76707,both interview and exam,female,46,NA,black,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,never_married,NA,TRUE,22500 +76708,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,2500 +76709,both interview and exam,male,74,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +76710,both interview and exam,male,1,13,asian,2,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76711,both interview and exam,male,11,NA,black,2,134,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,60000 +76712,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76713,both interview and exam,female,2,NA,other,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +76714,both interview and exam,female,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +76715,both interview and exam,male,74,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +76716,both interview and exam,female,18,NA,white,2,221,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +76717,both interview and exam,female,0,5,black,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76718,both interview and exam,female,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +76719,both interview and exam,female,39,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,50000 +76720,both interview and exam,female,15,NA,mexican american,2,191,NA,NA,FALSE,FALSE,3,10,NA,NA,NA,FALSE,30000 +76721,both interview and exam,female,9,NA,white,2,117,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +76722,both interview and exam,male,73,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76723,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +76724,both interview and exam,female,13,NA,asian,2,165,NA,NA,FALSE,FALSE,7.5,8,NA,NA,NA,TRUE,30000 +76725,both interview and exam,male,14,NA,white,2,170,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +76726,both interview and exam,female,0,0,asian,1,0,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76727,both interview and exam,female,7,NA,mexican american,1,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,60000 +76728,both interview and exam,male,8,NA,black,1,104,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +76729,both interview and exam,female,0,7,asian,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76730,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +76731,both interview and exam,male,41,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,FALSE,70000 +76732,both interview and exam,female,19,NA,mexican american,2,231,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,87500 +76733,both interview and exam,male,77,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +76734,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +76735,both interview and exam,female,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +76736,both interview and exam,female,30,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,yes,TRUE,100000 +76737,both interview and exam,female,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +76738,both interview and exam,female,63,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,divorced,NA,TRUE,100000 +76739,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,17500 +76740,both interview and exam,female,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76741,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +76742,both interview and exam,male,40,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +76743,both interview and exam,male,2,NA,white,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +76744,both interview and exam,female,5,NA,asian,1,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +76745,both interview and exam,male,70,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,widowed,NA,FALSE,87500 +76746,both interview and exam,male,55,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,25,NA,5,never_married,NA,TRUE,NA +76747,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +76748,both interview and exam,male,1,13,white,1,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76749,both interview and exam,male,7,NA,mexican american,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,30000 +76750,both interview and exam,female,9,NA,mexican american,1,116,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,17500 +76751,both interview and exam,female,36,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,unable to ascertain,FALSE,70000 +76752,both interview and exam,male,4,NA,other hispanic,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76753,both interview and exam,male,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,70000 +76754,both interview and exam,male,76,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76755,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +76756,both interview and exam,male,44,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,TRUE,17500 +76757,both interview and exam,male,79,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,separated,NA,TRUE,40000 +76758,both interview and exam,male,15,NA,other,2,187,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +76759,both interview and exam,male,0,1,black,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76760,both interview and exam,female,16,NA,mexican american,1,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +76761,both interview and exam,female,0,10,mexican american,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +76762,both interview and exam,female,3,NA,mexican american,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76763,both interview and exam,female,12,NA,mexican american,1,146,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,60000 +76764,both interview and exam,female,61,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +76765,both interview and exam,female,13,NA,black,2,166,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +76766,both interview and exam,female,11,NA,black,1,135,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 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exam,male,5,NA,asian,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76777,both interview and exam,male,29,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +76778,both interview and exam,male,18,NA,mexican american,2,218,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +76779,both interview and exam,female,71,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,widowed,NA,FALSE,22500 +76780,both interview and exam,female,7,NA,white,2,92,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +76781,both interview and exam,male,1,22,white,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +76782,interview only,female,2,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +76783,both interview and exam,female,9,NA,black,1,113,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +76784,both interview and exam,female,11,NA,white,2,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,7500 +76785,both interview and exam,male,22,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +76786,both interview and exam,female,9,NA,white,1,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +76787,both interview and exam,male,11,NA,mexican american,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +76788,both interview and exam,male,4,NA,mexican american,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +76789,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76790,both interview and exam,female,6,NA,black,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +76791,both interview and exam,female,15,NA,mexican american,1,189,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +76792,both interview and exam,female,38,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,40000 +76793,both interview and exam,female,45,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +76794,both interview and exam,female,12,NA,black,2,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +76795,both interview and exam,male,11,NA,black,1,144,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +76796,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +76797,both interview and exam,female,60,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,12500 +76798,both interview and exam,female,5,NA,other hispanic,2,62,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +76799,both interview and exam,male,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +76800,both interview and exam,male,18,NA,white,2,225,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,12500 +76801,both interview and exam,male,0,4,other hispanic,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76802,both interview and exam,male,57,NA,black,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,TRUE,17500 +76803,both interview and exam,male,12,NA,mexican american,2,146,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +76804,both interview and exam,male,10,NA,white,1,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 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exam,male,62,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76815,both interview and exam,male,44,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,NA +76816,interview only,female,30,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,unable to ascertain,TRUE,7500 +76817,both interview and exam,male,54,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +76818,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +76819,both interview and exam,female,54,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,35,NA,5,married,NA,TRUE,100000 +76820,both interview and exam,male,46,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +76821,both interview and exam,male,18,NA,mexican american,1,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +76822,both interview and exam,female,16,NA,mexican american,2,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,30000 +76823,both interview and exam,female,6,NA,other,2,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +76824,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +76825,both interview and exam,male,28,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,30000 +76826,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +76827,both interview and exam,female,72,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,widowed,NA,FALSE,12500 +76828,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,no,TRUE,22500 +76829,both interview and exam,male,12,NA,black,2,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,22500 +76830,both interview and exam,male,10,NA,white,2,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +76831,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,40000 +76832,both interview and exam,female,5,NA,white,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76833,both interview and exam,female,7,NA,mexican american,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,70000 +76834,both interview and exam,female,16,NA,mexican american,2,194,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,30000 +76835,both interview and exam,female,40,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,12500 +76836,interview only,female,3,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +76837,both interview and exam,male,40,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,TRUE,100000 +76838,both interview and exam,female,2,NA,asian,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +76839,both interview and exam,female,6,NA,mexican american,2,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,22500 +76840,both interview and exam,female,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +76841,both interview and exam,male,6,NA,white,1,79,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 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exam,female,73,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,1,living_with_partner,NA,FALSE,NA +76852,both interview and exam,male,0,2,white,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +76853,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76854,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76855,both interview and exam,female,0,8,mexican american,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +76856,both interview and exam,male,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +76857,both interview and exam,male,13,NA,white,2,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,70000 +76858,both interview and exam,female,8,NA,other,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +76859,both interview and exam,male,32,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,100000 +76860,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,40000 +76861,both interview and exam,female,3,NA,mexican american,1,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +76862,interview only,female,9,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +76863,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +76864,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,22500 +76865,both interview and exam,male,18,NA,black,1,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +76866,both interview and exam,male,11,NA,black,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +76867,both interview and exam,male,51,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +76868,both interview and exam,male,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +76869,both interview and exam,female,16,NA,mexican american,2,205,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,12500 +76870,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +76871,both interview and exam,female,70,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +76872,both interview and exam,male,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +76873,both interview and exam,female,5,NA,black,1,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76874,both interview and exam,male,10,NA,asian,1,121,NA,NA,FALSE,FALSE,7.5,3,NA,NA,NA,TRUE,7500 +76875,both interview and exam,male,4,NA,white,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +76876,both interview and exam,male,1,18,mexican american,1,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76877,both interview and exam,female,52,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +76878,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +76879,both interview and exam,female,17,NA,black,1,215,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +76880,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +76881,both interview and exam,female,11,NA,other,2,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,NA +76882,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +76883,both interview and exam,male,7,NA,other hispanic,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +76884,both interview and exam,female,55,NA,black,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +76885,both interview and exam,male,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76886,both interview and exam,male,54,NA,other hispanic,2,NA,TRUE,FALSE,FALSE,TRUE,35,NA,2,married,NA,TRUE,NA +76887,interview only,male,11,NA,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +76888,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 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exam,male,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +76908,both interview and exam,female,22,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,NA +76909,both interview and exam,female,18,NA,white,1,222,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +76910,both interview and exam,female,10,NA,black,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +76911,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +76912,both interview and exam,male,74,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,17500 +76913,both interview and exam,female,0,3,black,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76914,both interview and exam,female,34,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,unable to ascertain,TRUE,NA +76915,both interview and exam,male,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76916,both interview and exam,male,15,NA,mexican american,1,182,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +76917,both interview and exam,male,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +76918,both interview and exam,male,17,NA,white,2,216,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +76919,both interview and exam,male,37,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76920,both interview and exam,female,23,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,17500 +76921,both interview and exam,male,64,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,55,NA,1,never_married,NA,FALSE,12500 +76922,both interview and exam,male,1,15,white,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76923,interview only,male,33,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +76924,both interview and exam,male,19,NA,black,2,233,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +76925,both interview and exam,female,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,7500 +76926,both interview and exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +76927,both interview and exam,female,11,NA,black,1,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +76928,both interview and exam,male,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +76929,both interview and exam,male,19,NA,other,2,237,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +76930,both interview and exam,male,5,NA,mexican american,2,63,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,2500 +76931,both interview and exam,male,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +76932,both interview and exam,male,73,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +76933,both interview and exam,female,4,NA,other,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76934,both interview and exam,male,41,NA,other,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76935,both interview and exam,male,43,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,married,NA,FALSE,70000 +76936,both interview and exam,female,12,NA,other hispanic,1,148,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,7500 +76937,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,60000 +76938,both interview and exam,female,16,NA,mexican american,1,202,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +76939,both interview and exam,female,8,NA,asian,1,103,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +76940,both interview and exam,male,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +76941,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +76942,interview only,female,39,NA,mexican american,NA,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,unable to ascertain,FALSE,30000 +76943,both interview and exam,female,10,NA,white,1,131,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +76944,both interview and exam,male,64,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,separated,NA,FALSE,7500 +76945,both interview and exam,female,53,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +76946,both interview and exam,male,3,NA,black,1,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76947,interview only,male,35,NA,mexican american,NA,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,NA,FALSE,2500 +76948,both interview and exam,female,11,NA,white,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +76949,both interview and exam,female,14,NA,other hispanic,1,177,NA,NA,FALSE,FALSE,12.5,8,NA,NA,NA,FALSE,17500 +76950,both interview and exam,female,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +76951,both interview and exam,female,80,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,1,widowed,NA,TRUE,22500 +76952,both interview and exam,male,1,18,white,2,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +76953,both interview and exam,male,41,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 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exam,male,39,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +76964,both interview and exam,male,16,NA,white,1,194,NA,NA,FALSE,TRUE,7.5,9,NA,NA,NA,TRUE,100000 +76965,both interview and exam,male,35,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +76966,both interview and exam,female,48,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +76967,both interview and exam,female,3,NA,white,1,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +76968,both interview and exam,male,34,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,30000 +76969,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +76970,both interview and exam,female,19,NA,asian,2,229,FALSE,NA,FALSE,TRUE,17.5,13,NA,NA,NA,TRUE,60000 +76971,both interview and exam,male,6,NA,asian,1,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +76972,both interview and exam,male,57,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,TRUE,50000 +76973,both interview and exam,female,65,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +76974,both interview and exam,female,38,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,60000 +76975,both interview and exam,male,53,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,NA +76976,both interview and exam,female,12,NA,black,1,145,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +76977,both interview and exam,male,69,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +76978,both interview and exam,female,18,NA,mexican american,2,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,NA +76979,both interview and exam,female,23,NA,other,1,NA,FALSE,NA,FALSE,TRUE,3,NA,4,never_married,unable to ascertain,TRUE,50000 +76980,both interview and exam,female,1,23,white,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +76981,both interview and exam,female,6,NA,black,1,72,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +76982,both interview and exam,female,8,NA,asian,2,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +76983,both interview and exam,male,11,NA,other,1,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +76984,both interview and exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +76985,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +76986,both interview and exam,male,2,NA,mexican american,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +76987,both interview and exam,female,33,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,3,living_with_partner,no,FALSE,17500 +76988,both interview and exam,male,67,NA,asian,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +76989,both interview and exam,female,9,NA,black,1,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +76990,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,100000 +76991,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,married,NA,TRUE,30000 +76992,both interview and exam,male,67,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,100000 +76993,both interview and exam,female,16,NA,black,2,204,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +76994,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,yes,TRUE,NA +76995,both interview and exam,female,15,NA,black,1,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +76996,both interview and exam,male,36,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,never_married,NA,FALSE,NA +76997,both interview and exam,male,18,NA,other hispanic,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +76998,both interview and exam,female,14,NA,mexican american,1,174,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,NA +76999,both interview and exam,male,19,NA,white,1,235,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +77000,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +77001,both interview and exam,female,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +77002,both interview and exam,male,16,NA,mexican american,1,196,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +77003,both interview and exam,male,42,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,NA +77004,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,100000 +77005,both interview and exam,male,4,NA,black,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77006,both interview and exam,female,34,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,30000 +77007,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,40000 +77008,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +77009,both interview and exam,male,10,NA,white,1,130,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77010,both interview and exam,male,44,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +77011,both interview and exam,female,63,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,60000 +77012,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77013,both interview and exam,male,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +77014,both interview and exam,female,52,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,50000 +77015,interview only,female,67,NA,other hispanic,NA,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,FALSE,100000 +77016,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +77017,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +77018,interview only,female,4,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77019,both interview and exam,female,28,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +77020,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +77021,both interview and exam,male,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77022,both interview and exam,male,54,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +77023,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,60000 +77024,both interview and exam,male,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +77025,both interview and exam,male,55,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,TRUE,60000 +77026,both interview and exam,female,14,NA,mexican 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exam,male,30,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +77046,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +77047,both interview and exam,male,28,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +77048,both interview and exam,female,1,19,white,2,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77049,both interview and exam,female,66,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,widowed,NA,TRUE,50000 +77050,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +77051,both interview and exam,female,21,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,living_with_partner,no,TRUE,12500 +77052,both interview and exam,female,12,NA,other,2,146,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,17500 +77053,both interview and exam,male,8,NA,white,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +77054,both interview and exam,male,54,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,100000 +77055,both interview and exam,female,45,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +77056,interview only,male,16,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +77057,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +77058,both interview and exam,female,17,NA,mexican american,2,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +77059,both interview and exam,female,6,NA,black,1,83,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +77060,both interview and exam,female,72,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +77061,both interview and exam,female,3,NA,mexican american,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +77062,both interview and exam,male,1,15,white,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77063,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +77064,both interview and exam,male,2,NA,white,2,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +77065,both interview and exam,male,6,NA,white,2,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,22500 +77066,both interview and exam,female,62,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,separated,NA,FALSE,NA +77067,both interview and exam,female,67,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +77068,both interview and exam,male,15,NA,mexican american,1,185,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,40000 +77069,interview only,female,0,2,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77070,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +77071,both interview and exam,male,14,NA,asian,2,181,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,70000 +77072,both interview and exam,male,70,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +77073,both interview and exam,female,67,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 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exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,50000 +77084,both interview and exam,female,3,NA,mexican american,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +77085,both interview and exam,female,0,2,asian,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77086,both interview and exam,female,12,NA,mexican american,2,156,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,7500 +77087,both interview and exam,male,10,NA,black,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +77088,both interview and exam,female,7,NA,mexican american,2,95,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +77089,both interview and exam,male,4,NA,black,1,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77090,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,unable to ascertain,TRUE,50000 +77091,both interview and exam,female,31,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,NA +77092,both interview and exam,male,3,NA,white,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77093,both interview and exam,female,2,NA,white,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77094,both interview and exam,female,57,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,60000 +77095,both interview and exam,male,46,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77096,both interview and exam,female,75,NA,white,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,widowed,NA,TRUE,12500 +77097,both interview and exam,male,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +77098,both interview and exam,male,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +77099,both interview and exam,male,14,NA,mexican american,1,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,17500 +77100,both interview and exam,male,63,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,2,married,NA,FALSE,70000 +77101,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77102,both interview and exam,male,12,NA,black,1,150,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +77103,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,FALSE,50000 +77104,both interview and exam,female,13,NA,black,2,162,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +77105,both interview and exam,male,76,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +77106,both interview and exam,male,6,NA,black,1,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +77107,both interview and exam,female,7,NA,white,1,93,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +77108,both interview and exam,male,19,NA,black,1,231,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,30000 +77109,both interview and exam,male,38,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,FALSE,40000 +77110,both interview and exam,male,3,NA,mexican american,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 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exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +77121,both interview and exam,female,42,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,87500 +77122,both interview and exam,female,14,NA,other hispanic,2,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,40000 +77123,both interview and exam,female,50,NA,other,1,NA,FALSE,NA,FALSE,TRUE,55,NA,4,divorced,NA,TRUE,50000 +77124,both interview and exam,female,9,NA,other hispanic,2,111,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +77125,both interview and exam,male,6,NA,mexican american,1,81,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,22500 +77126,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +77127,both interview and exam,female,41,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,2500 +77128,both interview and exam,male,19,NA,white,1,236,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +77129,both interview and exam,female,10,NA,black,1,132,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +77130,both interview and exam,male,16,NA,other hispanic,1,199,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +77131,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,100000 +77132,both interview and exam,male,25,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77133,both interview and exam,female,2,NA,black,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77134,both interview and exam,male,7,NA,black,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,17500 +77135,both interview and exam,male,10,NA,white,1,124,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +77136,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +77137,both interview and exam,female,5,NA,other,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77138,both interview and exam,female,15,NA,black,1,181,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +77139,both interview and exam,female,71,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,2,widowed,NA,TRUE,12500 +77140,both interview and exam,male,58,NA,mexican american,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +77141,both interview and exam,female,42,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,separated,no,FALSE,30000 +77142,both interview and exam,male,68,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +77143,both interview and exam,female,2,NA,black,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77144,both interview and exam,female,27,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +77145,interview only,male,43,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +77146,both interview and exam,male,2,NA,white,2,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77147,both interview and exam,male,45,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,married,NA,TRUE,60000 +77148,both interview and exam,male,4,NA,other hispanic,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77149,both interview and exam,male,11,NA,black,2,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +77150,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77151,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +77152,both interview and exam,male,10,NA,black,1,131,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +77153,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +77154,both interview and exam,female,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +77155,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +77156,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +77157,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77158,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +77159,both interview and exam,female,38,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,no,TRUE,50000 +77160,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +77161,interview only,female,28,NA,other hispanic,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,unable to ascertain,TRUE,87500 +77162,both interview and exam,female,72,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +77163,both interview and exam,female,66,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,widowed,NA,FALSE,40000 +77164,both interview and exam,female,56,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,TRUE,22500 +77165,both interview and exam,male,10,NA,other hispanic,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77166,both interview and exam,female,2,NA,white,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77167,both interview and exam,female,40,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,no,TRUE,7500 +77168,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +77169,both interview and exam,male,10,NA,black,2,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,17500 +77170,both interview and exam,female,58,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,FALSE,87500 +77171,both interview and exam,female,69,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,widowed,NA,TRUE,30000 +77172,both interview and exam,male,42,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,NA +77173,both interview and exam,female,16,NA,asian,2,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +77174,both interview and exam,male,22,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +77175,both interview and exam,female,4,NA,other hispanic,2,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +77176,both interview and exam,female,41,NA,mexican 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exam,male,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +77215,both interview and exam,male,38,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,40000 +77216,both interview and exam,male,1,19,other hispanic,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +77217,both interview and exam,female,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,70000 +77218,both interview and exam,female,5,NA,mexican american,1,69,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,TRUE,87500 +77219,both interview and exam,female,3,NA,black,1,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77220,both interview and exam,female,25,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +77221,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,17500 +77222,both interview and exam,male,7,NA,white,2,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +77223,both interview and exam,female,65,NA,other 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interview and exam,female,1,12,other,2,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77234,both interview and exam,female,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,30000 +77235,both interview and exam,female,32,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,no,TRUE,40000 +77236,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +77237,both interview and exam,female,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,2500 +77238,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,NA +77239,both interview and exam,female,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,unable to ascertain,TRUE,7500 +77240,both interview and exam,male,35,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,40000 +77241,both interview and exam,male,27,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,50000 +77242,both interview and 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exam,male,19,NA,other,1,239,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +77270,both interview and exam,male,11,NA,black,1,137,NA,NA,FALSE,FALSE,3,5,NA,NA,NA,TRUE,87500 +77271,both interview and exam,female,16,NA,white,2,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,2500 +77272,both interview and exam,male,3,NA,black,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77273,both interview and exam,female,5,NA,black,2,72,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77274,both interview and exam,male,8,NA,black,1,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +77275,both interview and exam,male,60,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,3,married,NA,FALSE,87500 +77276,both interview and exam,male,2,NA,white,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77277,both interview and exam,male,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +77278,both interview and exam,male,4,NA,white,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77279,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +77280,both interview and exam,male,42,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +77281,both interview and exam,female,13,NA,white,1,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,2500 +77282,both interview and exam,male,20,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,3,NA,2,never_married,NA,TRUE,NA +77283,interview only,female,46,NA,asian,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77284,both interview and exam,male,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +77285,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,12500 +77286,both interview and exam,female,4,NA,mexican american,1,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,2500 +77287,both interview and exam,female,53,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77288,both interview and 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exam,female,5,NA,black,1,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77298,both interview and exam,male,63,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,30000 +77299,both interview and exam,female,67,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,60000 +77300,both interview and exam,male,24,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +77301,both interview and exam,female,7,NA,mexican american,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +77302,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77303,both interview and exam,female,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +77304,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,yes,TRUE,7500 +77305,both interview and exam,female,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,7500 +77306,both interview and exam,male,73,NA,other 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interview and exam,female,8,NA,white,1,98,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +77364,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +77365,both interview and exam,male,23,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77366,both interview and exam,male,6,NA,other,1,80,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +77367,both interview and exam,female,48,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +77368,both interview and exam,female,43,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,no,FALSE,40000 +77369,both interview and exam,female,21,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +77370,both interview and exam,male,14,NA,black,1,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,2500 +77371,both interview and exam,female,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77372,both interview and exam,female,7,NA,white,2,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +77373,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +77374,both interview and exam,female,46,NA,black,1,NA,TRUE,FALSE,FALSE,TRUE,25,NA,5,divorced,NA,TRUE,40000 +77375,interview only,female,1,23,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +77376,both interview and exam,male,60,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,40000 +77377,both interview and exam,male,36,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +77378,both interview and exam,male,2,NA,mexican american,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77379,both interview and exam,male,12,NA,black,1,148,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +77380,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77381,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,30000 +77382,both interview and exam,male,1,13,mexican american,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +77383,both interview and exam,male,80,NA,black,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,60000 +77384,both interview and exam,female,14,NA,black,2,179,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,60000 +77385,both interview and exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +77386,both interview and exam,female,31,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,no,TRUE,70000 +77387,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +77388,both interview and exam,male,46,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +77389,both interview and exam,male,4,NA,white,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +77390,both interview and exam,male,3,NA,other,2,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 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exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +77401,both interview and exam,female,0,4,black,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77402,both interview and exam,female,5,NA,other hispanic,2,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77403,both interview and exam,male,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +77404,both interview and exam,female,8,NA,black,2,107,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,50000 +77405,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,70000 +77406,interview only,male,8,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +77407,both interview and exam,female,44,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,separated,no,TRUE,17500 +77408,both interview and exam,female,79,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,widowed,NA,TRUE,12500 +77409,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,no,TRUE,NA +77410,interview only,male,6,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +77411,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,22500 +77412,both interview and exam,female,9,NA,white,1,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +77413,both interview and exam,female,2,NA,white,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77414,both interview and exam,male,32,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,married,NA,FALSE,30000 +77415,both interview and exam,female,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +77416,interview only,female,14,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +77417,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +77418,both interview and exam,female,8,NA,black,2,103,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +77419,both interview and exam,male,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77420,both interview and exam,female,18,NA,mexican american,1,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +77421,interview only,female,5,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77422,both interview and exam,male,80,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77423,both interview and exam,male,74,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +77424,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,no,TRUE,30000 +77425,both interview and exam,male,66,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,NA +77426,both interview and exam,male,14,NA,other hispanic,1,176,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +77427,both interview and exam,female,0,4,white,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77428,both interview and exam,female,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,30000 +77429,both interview and exam,female,76,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +77430,both interview and exam,female,1,19,white,2,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77431,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,12500 +77432,both interview and exam,male,4,NA,other hispanic,2,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +77433,both interview and exam,female,58,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,widowed,NA,TRUE,70000 +77434,both interview and exam,male,5,NA,asian,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77435,both interview and exam,female,10,NA,other hispanic,2,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,22500 +77436,both interview and exam,female,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77437,both interview and exam,male,6,NA,black,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,70000 +77438,both interview and exam,female,41,NA,mexican 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exam,male,12,NA,white,1,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +77458,both interview and exam,male,50,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +77459,both interview and exam,male,29,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,never_married,NA,TRUE,40000 +77460,both interview and exam,male,45,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,divorced,NA,FALSE,40000 +77461,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,2500 +77462,both interview and exam,male,6,NA,black,2,75,NA,NA,FALSE,FALSE,3,1,NA,NA,NA,TRUE,22500 +77463,both interview and exam,female,50,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,60000 +77464,both interview and exam,female,36,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,22500 +77465,both interview and exam,female,21,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,100000 +77466,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,60000 +77467,both interview and exam,female,4,NA,mexican american,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +77468,both interview and exam,male,54,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +77469,both interview and exam,female,67,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +77470,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,87500 +77471,both interview and exam,male,62,NA,white,1,NA,TRUE,TRUE,FALSE,TRUE,25,NA,5,married,NA,TRUE,50000 +77472,both interview and exam,female,0,6,other hispanic,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +77473,both interview and exam,female,31,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +77474,both interview and exam,female,14,NA,white,2,180,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,87500 +77475,both interview and exam,male,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77476,both interview and exam,male,9,NA,black,2,112,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +77477,both interview and exam,male,59,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,NA,TRUE,100000 +77478,both interview and exam,male,4,NA,other hispanic,1,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +77479,both interview and exam,male,4,NA,black,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +77480,both interview and exam,male,11,NA,black,1,139,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +77481,both interview and exam,female,54,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,22500 +77482,both interview and exam,female,5,NA,mexican american,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77483,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +77484,both interview and exam,male,40,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,7500 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exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +77495,both interview and exam,male,10,NA,other,2,131,NA,NA,FALSE,TRUE,7.5,5,NA,NA,NA,TRUE,17500 +77496,both interview and exam,male,1,22,other hispanic,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +77497,both interview and exam,male,9,NA,black,2,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +77498,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77499,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77500,both interview and exam,female,3,NA,mexican american,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77501,both interview and exam,male,5,NA,other,2,73,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77502,both interview and exam,female,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77503,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,2500 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only,female,72,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +77524,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +77525,interview only,male,1,18,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77526,both interview and exam,female,0,5,mexican american,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77527,both interview and exam,male,47,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,NA,FALSE,NA +77528,both interview and exam,male,40,NA,asian,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77529,both interview and exam,male,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77530,both interview and exam,female,2,NA,black,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77531,both interview and exam,male,5,NA,black,1,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77532,both interview and exam,male,15,NA,other,2,187,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +77533,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +77534,both interview and exam,female,15,NA,white,1,186,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +77535,both interview and exam,male,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,40000 +77536,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,divorced,NA,TRUE,40000 +77537,both interview and exam,male,8,NA,black,1,103,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +77538,both interview and exam,male,23,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +77539,both interview and exam,female,38,NA,black,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,no,TRUE,100000 +77540,both interview and exam,male,43,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +77541,both interview and exam,male,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77542,both interview and exam,male,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,22500 +77543,both interview and exam,male,43,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +77544,both interview and exam,male,0,8,mexican american,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +77545,both interview and exam,male,1,17,other hispanic,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +77546,both interview and exam,male,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +77547,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +77548,both interview and exam,male,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +77549,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +77550,both interview and exam,male,26,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +77551,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +77552,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +77553,both interview and exam,female,2,NA,other hispanic,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +77554,both interview and exam,female,5,NA,mexican american,1,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77555,both interview and exam,male,9,NA,mexican american,2,120,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +77556,both interview and exam,male,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +77557,both interview and exam,female,8,NA,other hispanic,1,106,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +77558,both interview and exam,female,2,NA,white,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77559,both interview and exam,female,0,5,mexican american,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +77560,both interview and exam,female,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,87500 +77561,both interview and exam,female,7,NA,mexican american,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,40000 +77562,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,40000 +77563,both interview and exam,male,36,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +77564,both interview and exam,male,1,23,mexican american,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77565,both interview and exam,female,2,NA,black,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77566,both interview and exam,female,0,2,mexican american,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +77567,interview only,female,1,19,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +77568,both interview and exam,male,3,NA,black,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77569,both interview and exam,female,48,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,FALSE,7500 +77570,both interview and exam,female,9,NA,mexican american,2,116,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,2500 +77571,both interview and exam,female,18,NA,other,2,220,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +77572,both interview and exam,male,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77573,both interview and exam,male,9,NA,mexican american,2,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,30000 +77574,both interview and exam,male,10,NA,other hispanic,2,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +77575,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +77576,both interview and exam,female,0,4,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77577,both interview and exam,female,33,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +77578,both interview and exam,male,45,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,married,NA,FALSE,40000 +77579,both interview and exam,male,15,NA,other hispanic,1,190,NA,NA,FALSE,TRUE,12.5,9,NA,NA,NA,TRUE,22500 +77580,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +77581,both interview and exam,female,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +77582,both interview and exam,male,10,NA,asian,1,126,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77583,both interview and exam,female,7,NA,mexican american,1,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,17500 +77584,both interview and exam,female,35,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,50000 +77585,both interview and exam,male,36,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,living_with_partner,NA,FALSE,40000 +77586,both interview and exam,male,65,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +77587,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +77588,both interview and exam,female,6,NA,other,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +77589,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +77590,both interview and exam,male,9,NA,other hispanic,1,109,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,17500 +77591,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77592,both interview and exam,female,52,NA,black,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,divorced,NA,TRUE,40000 +77593,both interview and exam,female,3,NA,other,2,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +77594,both interview and exam,male,3,NA,other hispanic,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +77595,both interview and exam,female,13,NA,black,1,168,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +77596,both interview and exam,male,49,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,FALSE,NA +77597,both interview and exam,male,58,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,2,married,NA,FALSE,30000 +77598,both interview and exam,male,79,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,17500 +77599,both interview and exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +77600,both interview and exam,female,58,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,divorced,NA,TRUE,40000 +77601,both interview and exam,male,42,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77602,both interview and exam,male,14,NA,white,2,171,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +77603,both interview and exam,female,56,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,70000 +77604,both interview and exam,male,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +77605,both interview and exam,male,55,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,50000 +77606,both interview and exam,male,14,NA,white,1,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +77607,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,no,TRUE,40000 +77608,both interview and exam,male,7,NA,mexican american,2,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +77609,both interview and exam,female,61,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,60000 +77610,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +77611,both interview and exam,female,35,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,never_married,no,TRUE,100000 +77612,both interview and exam,male,22,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77613,both interview and exam,male,19,NA,other hispanic,2,234,FALSE,NA,FALSE,FALSE,3,9,NA,NA,NA,FALSE,22500 +77614,both interview and exam,female,9,NA,other,2,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +77615,both interview and exam,female,19,NA,other hispanic,2,230,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +77616,both interview and exam,female,35,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +77617,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,2500 +77618,both interview and exam,female,25,NA,other,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,never_married,no,TRUE,12500 +77619,both interview and exam,male,0,9,asian,1,9,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,70000 +77620,both interview and exam,female,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +77621,both interview and exam,female,68,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +77622,both interview and exam,female,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +77623,both interview and exam,female,79,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,60000 +77624,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +77625,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,30000 +77626,both interview and exam,female,18,NA,mexican american,2,224,FALSE,NA,FALSE,FALSE,7.5,12,NA,NA,NA,FALSE,30000 +77627,both interview and exam,female,3,NA,black,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77628,both interview and exam,male,7,NA,mexican american,2,95,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +77629,both interview and exam,male,17,NA,black,2,204,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +77630,both interview and exam,male,45,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77631,both interview and exam,female,59,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,divorced,NA,TRUE,30000 +77632,both interview and exam,male,39,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +77633,interview only,female,11,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +77634,both interview and exam,female,67,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,5,divorced,NA,FALSE,7500 +77635,both interview and exam,male,6,NA,other,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +77636,both interview and exam,male,6,NA,other hispanic,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +77637,both interview and exam,female,6,NA,other,1,76,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +77638,both interview and exam,female,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +77639,both interview and exam,female,28,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,never_married,no,FALSE,40000 +77640,both interview and exam,male,46,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +77641,both interview and exam,male,16,NA,asian,2,200,NA,NA,FALSE,FALSE,7.5,10,NA,NA,NA,TRUE,NA +77642,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,17500 +77643,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,no,FALSE,30000 +77644,both interview and exam,male,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +77645,both interview and exam,female,52,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,TRUE,87500 +77646,both interview and exam,male,18,NA,mexican american,1,221,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,100000 +77647,both interview and exam,male,68,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,55,NA,4,married,NA,TRUE,100000 +77648,both interview and exam,male,0,7,other hispanic,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +77649,both interview and exam,male,7,NA,white,1,90,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +77650,both interview and exam,female,0,3,mexican american,1,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +77651,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,17500 +77652,both interview and exam,female,6,NA,white,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +77653,both interview and exam,female,29,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,40000 +77654,both interview and exam,female,70,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,widowed,NA,FALSE,NA +77655,both interview and exam,female,55,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,divorced,NA,TRUE,30000 +77656,both interview and exam,male,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +77657,both interview and exam,female,12,NA,asian,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +77658,both interview and exam,male,4,NA,white,1,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +77659,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 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exam,female,16,NA,mexican american,1,201,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,70000 +77670,both interview and exam,male,25,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +77671,both interview and exam,female,18,NA,asian,1,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,12500 +77672,both interview and exam,female,7,NA,other,1,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,17500 +77673,both interview and exam,male,26,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +77674,both interview and exam,female,55,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +77675,both interview and exam,male,33,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,100000 +77676,interview only,male,12,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +77677,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +77678,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +77679,both interview and exam,male,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +77680,both interview and exam,male,22,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +77681,both interview and exam,male,5,NA,black,1,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +77682,both interview and exam,male,50,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +77683,both interview and exam,male,7,NA,white,2,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +77684,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,22500 +77685,both interview and exam,female,13,NA,asian,2,163,NA,NA,FALSE,FALSE,0.5,8,NA,NA,NA,TRUE,87500 +77686,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,no,TRUE,NA +77687,both interview and exam,male,7,NA,mexican 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exam,male,23,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,2500 +77856,both interview and exam,male,33,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,87500 +77857,both interview and exam,male,10,NA,mexican american,1,126,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,NA +77858,both interview and exam,female,37,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,12500 +77859,both interview and exam,female,0,6,mexican american,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +77860,both interview and exam,male,13,NA,black,1,164,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,17500 +77861,both interview and exam,female,68,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,NA,TRUE,22500 +77862,both interview and exam,male,18,NA,white,2,227,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,87500 +77863,both interview and exam,male,0,4,asian,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77864,both interview and exam,male,40,NA,black,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,NA,TRUE,40000 +77865,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,22500 +77866,both interview and exam,male,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +77867,both interview and exam,male,68,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,7500 +77868,both interview and exam,male,16,NA,mexican american,2,195,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +77869,both interview and exam,female,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,NA,FALSE,NA +77870,both interview and exam,male,76,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,17500 +77871,both interview and exam,male,16,NA,white,2,193,NA,NA,FALSE,FALSE,0.5,9,NA,NA,NA,TRUE,100000 +77872,both interview and exam,female,42,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,no,FALSE,40000 +77873,both interview and exam,female,0,1,mexican american,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +77874,both interview and exam,male,52,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,7500 +77875,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +77876,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +77877,both interview and exam,female,6,NA,white,2,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +77878,both interview and exam,female,47,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,2500 +77879,both interview and exam,male,1,14,white,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +77880,both interview and exam,male,63,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +77881,both interview and exam,female,19,NA,mexican american,2,238,FALSE,NA,FALSE,FALSE,NA,11,NA,NA,NA,TRUE,17500 +77882,both interview and exam,male,3,NA,black,1,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77883,both interview and exam,male,5,NA,white,2,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +77884,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,no,TRUE,NA +77885,both interview and exam,female,9,NA,asian,1,115,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +77886,both interview and exam,female,14,NA,white,2,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +77887,both interview and exam,female,27,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,2,married,yes,TRUE,22500 +77888,both interview and exam,male,75,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,40000 +77889,both interview and exam,male,38,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +77890,both interview and exam,male,9,NA,black,1,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,2500 +77891,both interview and exam,female,55,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,NA,TRUE,60000 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interview and exam,male,6,NA,other hispanic,2,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +77902,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,NA +77903,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +77904,both interview and exam,male,6,NA,other hispanic,2,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,50000 +77905,both interview and exam,female,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,7500 +77906,both interview and exam,male,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,7500 +77907,both interview and exam,female,26,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,60000 +77908,both interview and exam,female,17,NA,mexican american,1,211,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +77909,both interview and exam,female,78,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +77910,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +77911,both interview and exam,male,8,NA,white,2,102,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +77912,both interview and exam,female,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,no,TRUE,22500 +77913,both interview and exam,female,11,NA,white,2,134,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,22500 +77914,both interview and exam,male,13,NA,asian,2,157,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +77915,both interview and exam,female,57,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,40000 +77916,both interview and exam,female,2,NA,mexican american,2,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +77917,both interview and exam,female,68,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,widowed,NA,FALSE,NA +77918,both interview and exam,male,6,NA,other hispanic,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +77919,both interview and exam,female,17,NA,other 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exam,male,15,NA,other hispanic,1,186,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +77930,both interview and exam,male,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +77931,both interview and exam,male,36,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,3,married,NA,TRUE,12500 +77932,both interview and exam,male,28,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +77933,both interview and exam,female,18,NA,white,2,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +77934,both interview and exam,male,12,NA,white,1,152,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +77935,both interview and exam,female,48,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +77936,both interview and exam,female,43,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,NA +77937,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,12500 +77938,both interview and exam,male,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,50000 +77939,both interview and exam,female,55,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +77940,both interview and exam,male,16,NA,mexican american,1,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +77941,both interview and exam,male,50,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,12500 +77942,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,87500 +77943,both interview and exam,male,38,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +77944,both interview and exam,male,4,NA,other hispanic,2,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +77945,interview only,female,69,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,2500 +77946,interview only,female,9,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,60000 +77947,both interview and 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exam,male,5,NA,black,2,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77957,both interview and exam,female,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,70000 +77958,both interview and exam,male,1,23,black,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +77959,both interview and exam,male,44,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +77960,both interview and exam,female,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,60000 +77961,both interview and exam,female,11,NA,white,2,134,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +77962,both interview and exam,female,8,NA,black,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +77963,both interview and exam,male,32,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +77964,both interview and exam,female,3,NA,black,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +77965,both interview and exam,male,47,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 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exam,male,0,2,black,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78012,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +78013,both interview and exam,female,45,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,60000 +78014,both interview and exam,female,6,NA,other hispanic,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +78015,both interview and exam,male,47,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,separated,NA,FALSE,7500 +78016,both interview and exam,male,12,NA,white,2,152,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +78017,both interview and exam,male,7,NA,mexican american,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,22500 +78018,both interview and exam,female,47,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,separated,NA,FALSE,22500 +78019,both interview and exam,male,65,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,40000 +78020,both interview and exam,female,42,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,4,married,no,TRUE,40000 +78021,both interview and exam,female,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +78022,both interview and exam,female,2,NA,asian,2,31,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,TRUE,12500 +78023,both interview and exam,male,0,0,mexican american,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78024,both interview and exam,male,33,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +78025,both interview and exam,male,15,NA,white,1,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +78026,both interview and exam,male,4,NA,black,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78027,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +78028,both interview and exam,male,64,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +78029,both interview and exam,male,1,12,other 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exam,male,43,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,100000 +78049,both interview and exam,female,7,NA,asian,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +78050,both interview and exam,male,17,NA,mexican american,2,211,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +78051,both interview and exam,male,40,NA,other,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +78052,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78053,both interview and exam,male,4,NA,black,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78054,both interview and exam,female,23,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,living_with_partner,no,FALSE,NA +78055,both interview and exam,male,9,NA,white,2,120,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +78056,both interview and exam,male,75,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +78057,both interview and exam,male,14,NA,black,1,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +78058,interview only,male,50,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +78059,both interview and exam,male,4,NA,black,1,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78060,both interview and exam,female,2,NA,white,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78061,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78062,both interview and exam,female,0,4,black,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +78063,both interview and exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,22500 +78064,both interview and exam,female,12,NA,black,1,154,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,22500 +78065,both interview and exam,female,13,NA,mexican american,1,164,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,22500 +78066,both interview and exam,male,2,NA,mexican american,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +78067,both interview and exam,female,10,NA,white,2,129,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +78068,both interview and exam,male,19,NA,white,2,235,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +78069,both interview and exam,female,3,NA,black,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78070,both interview and exam,male,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +78071,both interview and exam,female,6,NA,mexican american,2,85,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,17500 +78072,both interview and exam,male,77,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,22500 +78073,both interview and exam,male,14,NA,white,2,176,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +78074,both interview and exam,male,51,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,divorced,NA,FALSE,NA +78075,both interview and exam,male,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +78076,both interview and exam,female,56,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +78077,both interview and exam,male,10,NA,mexican american,1,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,30000 +78078,both interview and exam,male,19,NA,mexican american,1,231,FALSE,NA,FALSE,FALSE,0.5,13,NA,NA,NA,FALSE,22500 +78079,both interview and exam,female,40,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,50000 +78080,both interview and exam,male,58,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,never_married,NA,TRUE,87500 +78081,both interview and exam,female,63,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,87500 +78082,both interview and exam,male,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +78083,both interview and exam,male,53,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +78084,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,12500 +78085,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,never_married,NA,TRUE,100000 +78086,both interview and exam,male,80,NA,black,1,NA,FALSE,NA,FALSE,TRUE,55,NA,1,married,NA,TRUE,17500 +78087,both interview and exam,male,16,NA,black,2,201,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +78088,both interview and exam,male,66,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +78089,both interview and exam,male,62,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,never_married,NA,FALSE,50000 +78090,both interview and exam,female,15,NA,white,1,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +78091,both interview and exam,female,18,NA,other,1,225,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,7500 +78092,both interview and exam,female,6,NA,asian,1,72,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +78093,both interview and exam,male,29,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +78094,both interview and exam,female,39,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +78095,both interview and exam,female,51,NA,other 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american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,22500 +78105,both interview and exam,female,36,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,no,TRUE,7500 +78106,both interview and exam,male,12,NA,black,1,151,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +78107,both interview and exam,female,54,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +78108,both interview and exam,male,49,NA,black,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,TRUE,17500 +78109,both interview and exam,male,16,NA,white,1,202,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +78110,both interview and exam,female,8,NA,white,1,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +78111,both interview and exam,male,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +78112,both interview and exam,female,8,NA,other,2,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +78113,both interview and exam,female,12,NA,white,1,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +78114,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,2500 +78115,both interview and exam,male,11,NA,white,2,143,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +78116,both interview and exam,female,7,NA,other hispanic,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,50000 +78117,both interview and exam,male,8,NA,other hispanic,1,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +78118,both interview and exam,female,11,NA,other hispanic,1,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +78119,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,87500 +78120,both interview and exam,male,9,NA,asian,2,119,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +78121,both interview and exam,male,22,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +78122,both interview and exam,female,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +78123,both interview and exam,male,0,8,black,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 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exam,male,0,6,other hispanic,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +78134,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +78135,interview only,male,10,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +78136,both interview and exam,male,5,NA,white,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78137,both interview and exam,female,7,NA,mexican american,2,87,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,17500 +78138,both interview and exam,male,66,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78139,both interview and exam,male,60,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +78140,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78141,both interview and exam,male,9,NA,white,2,116,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +78142,both interview and exam,female,13,NA,other hispanic,1,161,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,60000 +78143,both interview 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exam,male,0,3,white,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78153,both interview and exam,female,18,NA,black,1,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,70000 +78154,both interview and exam,female,2,NA,white,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +78155,both interview and exam,male,9,NA,white,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +78156,interview only,male,32,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +78157,both interview and exam,male,3,NA,black,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78158,both interview and exam,female,41,NA,black,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,no,TRUE,22500 +78159,both interview and exam,female,4,NA,other,2,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +78160,both interview and exam,male,9,NA,black,2,111,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,2500 +78161,both interview and exam,female,34,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,no,TRUE,17500 +78162,both interview and 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exam,female,19,NA,black,1,232,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,12500 +78273,both interview and exam,female,7,NA,white,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +78274,both interview and exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +78275,both interview and exam,female,24,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,yes,TRUE,22500 +78276,both interview and exam,male,6,NA,white,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +78277,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,22500 +78278,both interview and exam,male,6,NA,white,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +78279,both interview and exam,female,14,NA,white,2,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,17500 +78280,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +78281,both interview and exam,male,6,NA,black,1,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +78282,both 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interview and exam,female,60,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78487,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +78488,both interview and exam,female,0,2,other,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +78489,both interview and exam,female,31,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,no,TRUE,87500 +78490,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +78491,both interview and exam,female,11,NA,black,1,139,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,50000 +78492,both interview and exam,female,4,NA,other,2,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +78493,both interview and exam,male,11,NA,white,2,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +78494,both interview and exam,female,0,5,mexican american,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +78495,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,30000 +78496,both interview and exam,female,19,NA,mexican american,1,232,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,17500 +78497,both interview and exam,male,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +78498,both interview and exam,female,78,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +78499,both interview and exam,male,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,30000 +78500,both interview and exam,male,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +78501,both interview and exam,female,19,NA,other,2,229,FALSE,NA,FALSE,FALSE,0.5,9,NA,NA,NA,TRUE,2500 +78502,both interview and exam,female,1,16,mexican american,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78503,both interview and exam,female,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,2,widowed,NA,TRUE,12500 +78504,both interview and exam,female,60,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +78505,interview only,male,0,1,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78506,both interview and exam,male,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +78507,both interview and exam,male,2,24,black,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78508,both interview and exam,male,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +78509,both interview and exam,female,13,NA,mexican american,2,162,NA,NA,FALSE,FALSE,7.5,7,NA,NA,NA,FALSE,17500 +78510,both interview and exam,male,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78511,both interview and exam,male,15,NA,black,2,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +78512,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +78513,both interview and exam,female,2,NA,white,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 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exam,female,60,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,50000 +78524,both interview and exam,female,1,17,white,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +78525,both interview and exam,male,11,NA,other hispanic,1,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +78526,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,never_married,NA,TRUE,87500 +78527,both interview and exam,female,72,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +78528,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,87500 +78529,both interview and exam,female,19,NA,other hispanic,2,234,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,NA +78530,both interview and exam,female,7,NA,black,1,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +78531,both interview and exam,male,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78532,interview only,male,28,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,100000 +78533,both interview and exam,female,48,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +78534,both interview and exam,female,67,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,widowed,NA,FALSE,NA +78535,both interview and exam,female,80,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +78536,both interview and exam,male,51,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,TRUE,60000 +78537,both interview and exam,male,7,NA,white,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +78538,interview only,female,32,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,unable to ascertain,TRUE,30000 +78539,both interview and exam,female,0,10,asian,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78540,both interview and exam,male,8,NA,white,2,101,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +78541,both interview and exam,male,11,NA,asian,1,140,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,70000 +78542,both interview and exam,female,41,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,living_with_partner,no,FALSE,30000 +78543,both interview and exam,female,3,NA,white,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78544,both interview and exam,male,1,23,white,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +78545,both interview and exam,male,1,20,black,1,21,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +78546,both interview and exam,female,10,NA,mexican american,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +78547,both interview and exam,male,7,NA,white,2,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +78548,both interview and exam,female,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,NA +78549,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +78550,interview only,female,2,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78551,both interview and exam,female,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +78552,both interview and exam,female,68,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,7500 +78553,both interview and exam,female,10,NA,white,2,125,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +78554,both interview and exam,male,10,NA,mexican american,2,122,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +78555,both interview and exam,male,5,NA,mexican american,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,60000 +78556,both interview and exam,female,60,NA,white,1,NA,FALSE,NA,FALSE,FALSE,55,NA,3,divorced,NA,TRUE,2500 +78557,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +78558,both interview and exam,female,5,NA,other hispanic,1,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +78559,both interview and exam,female,11,NA,white,1,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +78560,both interview and exam,male,22,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +78561,both interview and exam,male,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +78562,both interview and exam,male,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +78563,both interview and exam,male,9,NA,asian,2,109,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +78564,both interview and exam,male,8,NA,other hispanic,1,102,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +78565,both interview and exam,male,6,NA,black,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +78566,both interview and exam,male,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +78567,both interview and exam,female,0,3,white,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78568,both interview and exam,female,29,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,30000 +78569,both interview and exam,female,19,NA,white,2,233,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,7500 +78570,both interview and exam,male,0,4,white,1,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78571,both interview and exam,female,0,8,mexican american,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +78572,both interview and exam,male,51,NA,white,2,NA,FALSE,NA,FALSE,TRUE,45,NA,5,widowed,NA,TRUE,40000 +78573,both interview and exam,male,5,NA,mexican american,1,68,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,FALSE,12500 +78574,both interview and exam,female,10,NA,black,2,120,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +78575,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,2500 +78576,both interview and exam,female,15,NA,black,2,182,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +78577,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,NA +78578,both interview and exam,female,11,NA,mexican american,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +78579,both interview and exam,male,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +78580,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +78581,both interview and exam,female,44,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,no,TRUE,50000 +78582,both interview and exam,female,15,NA,white,2,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +78583,both interview and exam,male,54,NA,other hispanic,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +78584,both interview and exam,female,11,NA,white,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +78585,both interview and exam,male,8,NA,black,1,107,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +78586,both interview and exam,female,41,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +78587,both interview and exam,female,57,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,NA,TRUE,60000 +78588,both interview and exam,male,49,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,4,separated,NA,FALSE,NA +78589,both interview and exam,female,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,22500 +78590,interview only,female,42,NA,mexican american,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,living_with_partner,unable to ascertain,FALSE,NA +78591,both interview and exam,female,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +78592,both interview and exam,female,4,NA,other,2,54,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78593,both interview and exam,female,8,NA,other hispanic,2,98,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,22500 +78594,both interview and exam,male,1,13,mexican american,2,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +78595,both interview and exam,male,31,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +78596,both interview and exam,female,9,NA,white,2,116,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +78597,both interview and exam,male,61,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,TRUE,NA +78598,both interview and exam,male,63,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +78599,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +78600,both interview and exam,female,11,NA,white,2,144,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +78601,both interview and exam,male,46,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +78602,both interview and exam,female,14,NA,other hispanic,2,174,NA,NA,FALSE,FALSE,3,9,NA,NA,NA,FALSE,22500 +78603,both interview and exam,male,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +78604,both interview and exam,female,11,NA,white,1,135,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +78605,both interview and exam,female,11,NA,white,1,143,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +78606,both interview and exam,male,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +78607,interview 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hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +78617,both interview and exam,female,1,14,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +78618,both interview and exam,male,0,6,black,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78619,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,70000 +78620,both interview and exam,male,64,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,TRUE,22500 +78621,both interview and exam,male,50,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +78622,both interview and exam,male,16,NA,white,2,197,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +78623,both interview and exam,male,12,NA,white,2,151,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +78624,both interview and exam,female,13,NA,mexican american,1,165,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +78625,both interview and exam,male,2,NA,black,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +78626,both interview and exam,male,51,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,22500 +78627,both interview and exam,male,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +78628,both interview and exam,female,11,NA,mexican american,1,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,50000 +78629,both interview and exam,female,13,NA,white,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,70000 +78630,both interview and exam,male,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +78631,both interview and exam,female,28,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +78632,both interview and exam,male,2,NA,mexican american,2,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +78633,both interview and exam,male,24,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,never_married,NA,TRUE,40000 +78634,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,2500 +78635,both interview and exam,male,11,NA,other,1,136,NA,NA,FALSE,FALSE,12.5,5,NA,NA,NA,TRUE,50000 +78636,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,no,TRUE,7500 +78637,both interview and exam,female,7,NA,black,1,88,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +78638,both interview and exam,male,40,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +78639,both interview and exam,female,10,NA,mexican american,2,127,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,60000 +78640,both interview and exam,male,66,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,45,NA,3,married,NA,TRUE,30000 +78641,both interview and exam,male,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +78642,both interview and exam,female,19,NA,white,2,229,FALSE,NA,FALSE,FALSE,12.5,14,NA,NA,NA,TRUE,17500 +78643,both interview and exam,male,0,2,white,2,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78644,both interview and exam,male,0,3,black,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +78645,both 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exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +78728,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,2500 +78729,both interview and exam,female,18,NA,other hispanic,1,219,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +78730,both interview and exam,female,0,9,mexican american,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78731,both interview and exam,female,18,NA,mexican american,1,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +78732,both interview and exam,female,10,NA,asian,1,130,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +78733,both interview and exam,male,27,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,30000 +78734,both interview and exam,female,4,NA,asian,2,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78735,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +78736,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +78737,both interview and exam,female,71,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,7500 +78738,both interview and exam,female,2,NA,other,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78739,both interview and exam,male,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78740,both interview and exam,male,10,NA,mexican american,2,124,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,50000 +78741,both interview and exam,male,37,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,50000 +78742,both interview and exam,male,53,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +78743,both interview and exam,female,8,NA,black,1,107,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +78744,both interview and exam,female,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78745,both interview and exam,male,2,NA,mexican 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interview and exam,male,33,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,3,married,NA,TRUE,NA +78766,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +78767,both interview and exam,male,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +78768,both interview and exam,female,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +78769,both interview and exam,male,19,NA,mexican american,2,236,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +78770,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +78771,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +78772,both interview and exam,female,30,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,no,FALSE,2500 +78773,both interview and exam,female,8,NA,other,1,96,NA,NA,FALSE,TRUE,3,1,NA,NA,NA,TRUE,NA +78774,both interview and 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exam,female,2,NA,white,1,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +78794,both interview and exam,male,60,NA,other,1,NA,TRUE,TRUE,FALSE,TRUE,17.5,NA,4,married,NA,TRUE,40000 +78795,both interview and exam,female,0,9,black,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78796,both interview and exam,female,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +78797,both interview and exam,male,37,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,TRUE,100000 +78798,both interview and exam,male,19,NA,black,2,231,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,7500 +78799,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78800,both interview and exam,female,0,3,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +78801,both interview and exam,male,37,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +78802,both interview and exam,female,14,NA,white,2,169,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 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exam,male,3,NA,black,2,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +78831,both interview and exam,male,8,NA,white,2,101,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +78832,both interview and exam,male,32,NA,black,2,NA,NA,NA,FALSE,TRUE,7.5,NA,5,married,NA,TRUE,60000 +78833,both interview and exam,male,27,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +78834,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,70000 +78835,both interview and exam,female,11,NA,other,2,133,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +78836,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +78837,both interview and exam,female,16,NA,mexican american,2,200,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +78838,both interview and exam,male,78,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +78839,both interview and exam,male,8,NA,other hispanic,1,106,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,17500 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exam,female,6,NA,white,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +78850,both interview and exam,male,15,NA,mexican american,2,184,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +78851,both interview and exam,female,6,NA,white,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +78852,both interview and exam,male,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,divorced,NA,FALSE,NA +78853,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +78854,both interview and exam,male,67,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +78855,both interview and exam,female,4,NA,white,2,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +78856,both interview and exam,female,2,NA,mexican american,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78857,both interview and exam,female,6,NA,other,2,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +78858,both interview and exam,male,77,NA,other 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exam,male,8,NA,white,1,101,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +78878,interview only,male,12,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +78879,both interview and exam,male,0,0,white,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +78880,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +78881,both interview and exam,female,28,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,7500 +78882,both interview and exam,female,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +78883,both interview and exam,male,51,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +78884,both interview and exam,female,26,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,no,FALSE,17500 +78885,both interview and exam,female,61,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78886,both interview and exam,female,4,NA,other 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interview and exam,male,61,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,divorced,NA,TRUE,7500 +78906,both interview and exam,male,15,NA,black,1,189,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,17500 +78907,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78908,both interview and exam,female,9,NA,asian,2,119,NA,NA,FALSE,FALSE,3,4,NA,NA,NA,TRUE,12500 +78909,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,50000 +78910,both interview and exam,male,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +78911,both interview and exam,female,56,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,NA,FALSE,87500 +78912,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,70000 +78913,both interview and exam,female,7,NA,mexican american,1,91,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,30000 +78914,both interview and exam,male,0,9,asian,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78915,both interview and exam,male,0,2,white,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +78916,both interview and exam,female,60,NA,black,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,70000 +78917,interview only,female,26,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,12500 +78918,both interview and exam,male,67,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,0.5,NA,3,married,NA,TRUE,100000 +78919,both interview and exam,female,47,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78920,both interview and exam,male,20,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,FALSE,30000 +78921,both interview and exam,male,47,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +78922,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +78923,both interview and exam,female,15,NA,white,2,186,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,NA +78924,both interview and exam,female,50,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +78925,both interview and exam,female,19,NA,asian,1,229,FALSE,NA,FALSE,FALSE,3,13,NA,NA,NA,TRUE,2500 +78926,both interview and exam,male,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +78927,both interview and exam,male,8,NA,black,2,104,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,50000 +78928,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +78929,both interview and exam,female,71,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,30000 +78930,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +78931,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +78932,both interview and exam,male,13,NA,asian,1,167,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 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exam,female,58,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,87500 +78943,both interview and exam,male,12,NA,other hispanic,2,153,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +78944,both interview and exam,female,56,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +78945,both interview and exam,female,5,NA,black,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +78946,both interview and exam,male,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +78947,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +78948,both interview and exam,female,5,NA,black,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +78949,both interview and exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +78950,both interview and exam,female,73,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,7500 +78951,both interview and 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exam,male,75,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +79202,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +79203,both interview and exam,female,4,NA,asian,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79204,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +79205,both interview and exam,male,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +79206,both interview and exam,male,72,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +79207,both interview and exam,female,25,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +79208,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +79209,both interview and exam,male,6,NA,white,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +79210,both interview and exam,male,25,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +79211,both interview and exam,female,39,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,never_married,no,TRUE,12500 +79212,both interview and exam,female,0,2,other hispanic,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +79213,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,40000 +79214,both interview and exam,female,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +79215,both interview and exam,female,28,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,living_with_partner,yes,TRUE,50000 +79216,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,100000 +79217,both interview and exam,male,33,NA,black,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,4,married,NA,TRUE,100000 +79218,both interview and exam,male,14,NA,black,1,170,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +79219,both interview and 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exam,female,72,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +79487,both interview and exam,female,42,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,married,no,FALSE,22500 +79488,both interview and exam,male,42,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,40000 +79489,both interview and exam,female,8,NA,white,1,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +79490,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,2500 +79491,both interview and exam,female,34,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,no,TRUE,100000 +79492,both interview and exam,male,13,NA,other hispanic,1,162,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +79493,both interview and exam,female,16,NA,mexican american,2,201,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,30000 +79494,both interview and exam,male,80,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,100000 +79495,both interview and 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exam,male,5,NA,white,1,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +79906,both interview and exam,female,50,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +79907,both interview and exam,female,0,0,white,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +79908,both interview and exam,male,19,NA,mexican american,1,236,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,30000 +79909,interview only,female,0,5,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +79910,both interview and exam,male,14,NA,white,2,169,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +79911,both interview and exam,female,16,NA,black,1,197,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +79912,both interview and exam,female,20,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +79913,both interview and exam,male,63,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,30000 +79914,both interview and exam,female,16,NA,mexican american,1,200,NA,NA,FALSE,FALSE,NA,10,NA,NA,NA,TRUE,NA +79915,both interview and exam,male,64,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +79916,both interview and exam,female,55,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,NA,TRUE,87500 +79917,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +79918,both interview and exam,male,70,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,2500 +79919,both interview and exam,female,62,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,2,divorced,NA,FALSE,17500 +79920,both interview and exam,male,59,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,NA,TRUE,17500 +79921,both interview and exam,female,43,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,no,TRUE,87500 +79922,both interview and exam,female,10,NA,mexican american,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +79923,both interview and exam,male,50,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,70000 +79924,both interview and exam,male,59,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,55,NA,3,married,NA,TRUE,30000 +79925,both interview and exam,male,49,NA,mexican american,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +79926,both interview and exam,female,28,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,living_with_partner,no,TRUE,40000 +79927,both interview and exam,female,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,22500 +79928,both interview and exam,female,67,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +79929,both interview and exam,female,60,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +79930,both interview and exam,female,13,NA,black,2,168,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,NA +79931,both interview and exam,female,2,NA,white,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +79932,both interview and exam,male,22,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,50000 +79933,both interview and exam,female,72,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,2,married,NA,FALSE,NA +79934,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,30000 +79935,both interview and exam,male,4,NA,black,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +79936,both interview and exam,male,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,40000 +79937,interview only,female,80,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,17500 +79938,both interview and exam,male,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +79939,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +79940,both interview and exam,female,26,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,yes,FALSE,17500 +79941,interview only,female,14,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +79942,both interview and exam,male,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +79943,both interview and exam,female,17,NA,asian,1,216,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +79944,both interview and exam,female,58,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +79945,both interview and exam,female,0,7,black,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +79946,both interview and exam,female,43,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,100000 +79947,both interview and exam,female,2,NA,mexican american,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79948,both interview and exam,female,6,NA,other hispanic,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +79949,both interview and exam,male,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,87500 +79950,both interview and exam,female,37,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,no,FALSE,70000 +79951,both interview and exam,female,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +79952,both interview and exam,male,55,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +79953,both interview and exam,male,19,NA,black,2,229,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,22500 +79954,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,70000 +79955,both interview and exam,male,37,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +79956,interview only,male,49,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,2500 +79957,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,60000 +79958,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +79959,both interview and exam,female,19,NA,black,1,235,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,12500 +79960,both interview and exam,female,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,70000 +79961,both interview and exam,female,6,NA,white,2,83,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +79962,both interview and exam,male,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,NA +79963,both interview and exam,male,25,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,87500 +79964,both interview and exam,female,10,NA,mexican american,2,130,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +79965,both interview and exam,female,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +79966,both interview and exam,male,0,8,other,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +79967,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,22500 +79968,both interview and exam,female,8,NA,white,2,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,50000 +79969,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,70000 +79970,both interview and exam,male,71,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +79971,both interview and exam,female,4,NA,white,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79972,both interview and exam,female,34,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,35,NA,4,never_married,no,TRUE,40000 +79973,both interview and exam,female,17,NA,asian,2,212,FALSE,NA,FALSE,FALSE,7.5,11,NA,NA,NA,TRUE,NA +79974,both interview and exam,female,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +79975,both interview and exam,male,1,20,other hispanic,1,21,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +79976,both interview and exam,male,1,22,other,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +79977,both interview and exam,male,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +79978,both interview and exam,female,37,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,no,TRUE,40000 +79979,both interview and exam,male,80,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,30000 +79980,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,22500 +79981,both interview and exam,male,1,23,black,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +79982,both interview and exam,male,45,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +79983,both interview and exam,female,0,5,other,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +79984,both interview and exam,female,4,NA,mexican american,1,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +79985,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +79986,both interview and exam,male,2,NA,white,2,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +79987,both interview and exam,female,66,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,divorced,NA,FALSE,7500 +79988,both interview and exam,male,57,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,7500 +79989,both interview and exam,female,42,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +79990,both interview and exam,male,5,NA,black,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +79991,both interview and exam,male,10,NA,white,2,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +79992,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +79993,both interview and exam,female,15,NA,black,2,185,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +79994,both interview and exam,male,19,NA,mexican american,1,234,FALSE,NA,FALSE,FALSE,NA,12,NA,NA,NA,TRUE,22500 +79995,both interview and exam,female,15,NA,other,2,184,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +79996,both interview and exam,male,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 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exam,male,47,NA,black,1,NA,FALSE,NA,FALSE,FALSE,25,NA,5,divorced,NA,TRUE,60000 +80007,both interview and exam,male,73,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,7500 +80008,both interview and exam,female,67,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,1,widowed,NA,FALSE,NA +80009,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +80010,both interview and exam,male,39,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80011,both interview and exam,female,2,NA,white,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80012,both interview and exam,male,1,19,other,2,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +80013,both interview and exam,female,62,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +80014,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80015,both interview and exam,male,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80016,both interview and exam,male,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,living_with_partner,NA,FALSE,22500 +80017,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +80018,both interview and exam,male,10,NA,other,2,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +80019,both interview and exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,22500 +80020,both interview and exam,female,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,50000 +80021,both interview and exam,female,16,NA,other,1,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,NA +80022,both interview and exam,male,21,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +80023,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80024,both interview and exam,female,48,NA,mexican 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exam,male,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +80034,both interview and exam,female,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,no,TRUE,40000 +80035,both interview and exam,male,4,NA,white,2,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80036,both interview and exam,female,16,NA,other hispanic,1,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +80037,both interview and exam,male,64,NA,mexican american,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +80038,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,NA +80039,both interview and exam,male,3,NA,asian,2,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80040,both interview and exam,female,70,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,7500 +80041,both interview and exam,female,42,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,TRUE,22500 +80042,both interview and exam,female,10,NA,white,2,121,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,NA +80043,both interview and exam,female,38,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +80044,both interview and exam,male,77,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +80045,both interview and exam,male,3,NA,black,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80046,both interview and exam,female,1,13,mexican american,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +80047,both interview and exam,female,22,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +80048,both interview and exam,male,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +80049,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80050,both interview and exam,male,8,NA,white,1,104,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +80051,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +80052,both interview and exam,female,62,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,never_married,NA,FALSE,NA +80053,both interview and exam,male,16,NA,black,2,198,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +80054,both interview and exam,male,13,NA,other hispanic,1,161,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +80055,both interview and exam,female,44,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,married,no,FALSE,50000 +80056,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,70000 +80057,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +80058,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,17500 +80059,both interview and exam,female,47,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,22500 +80060,both interview and exam,female,42,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +80061,both interview and exam,female,50,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +80062,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +80063,both interview and exam,male,80,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +80064,both interview and exam,male,32,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,22500 +80065,both interview and exam,male,2,NA,mexican american,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80066,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,87500 +80067,both interview and exam,male,65,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,NA,FALSE,2500 +80068,both interview and exam,female,9,NA,asian,1,120,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +80069,both interview and exam,male,10,NA,black,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +80070,both interview and exam,female,1,17,white,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80071,interview only,female,66,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +80072,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,22500 +80073,both interview and exam,female,57,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,50000 +80074,both interview and exam,female,10,NA,mexican american,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,40000 +80075,both interview and exam,male,32,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +80076,both interview and exam,female,2,NA,other hispanic,1,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +80077,both interview and exam,female,12,NA,white,1,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80078,both interview and exam,male,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,1,widowed,NA,TRUE,12500 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american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,never_married,NA,TRUE,12500 +80089,both interview and exam,female,51,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,2,never_married,NA,TRUE,12500 +80090,both interview and exam,female,0,8,white,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80091,both interview and exam,male,65,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +80092,both interview and exam,female,65,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80093,both interview and exam,female,8,NA,asian,2,104,NA,NA,FALSE,FALSE,3,2,NA,NA,NA,TRUE,100000 +80094,both interview and exam,female,69,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,60000 +80095,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +80096,both interview and exam,female,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,NA +80097,both interview and exam,male,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80098,both interview and exam,male,15,NA,mexican american,2,185,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +80099,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,70000 +80100,both interview and exam,male,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +80101,both interview and exam,male,29,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,70000 +80102,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,separated,NA,TRUE,40000 +80103,both interview and exam,male,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,87500 +80104,both interview and exam,male,11,NA,mexican american,1,138,NA,NA,FALSE,FALSE,NA,3,NA,NA,NA,FALSE,30000 +80105,both interview and exam,male,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,30000 +80106,both interview and exam,female,19,NA,mexican american,1,238,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +80107,both interview and exam,female,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +80108,both interview and exam,female,4,NA,other hispanic,2,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +80109,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,yes,TRUE,87500 +80110,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +80111,both interview and exam,female,18,NA,black,2,228,FALSE,NA,FALSE,TRUE,12.5,13,NA,NA,NA,TRUE,NA +80112,both interview and exam,male,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +80113,both interview and exam,male,1,16,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80114,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +80115,both interview and exam,male,80,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +80116,interview only,female,61,NA,black,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,separated,NA,TRUE,2500 +80117,both interview and exam,male,0,0,black,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80118,both interview and exam,female,8,NA,white,2,102,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +80119,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,70000 +80120,both interview and exam,female,65,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +80121,both interview and exam,male,68,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,2,married,NA,TRUE,NA +80122,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +80123,both interview and exam,male,71,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +80124,both interview and exam,male,70,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +80125,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,unable to ascertain,TRUE,22500 +80126,both interview and exam,male,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +80127,both interview and exam,male,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80128,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,22500 +80129,both interview and exam,male,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +80130,both interview and exam,male,51,NA,other,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,NA,TRUE,100000 +80131,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,7500 +80132,both interview and exam,male,37,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,never_married,NA,TRUE,NA +80133,both interview and exam,male,80,NA,black,2,NA,TRUE,FALSE,FALSE,TRUE,55,NA,5,married,NA,TRUE,100000 +80134,both interview and exam,female,18,NA,mexican american,2,223,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,30000 +80135,interview only,female,22,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,NA,never_married,unable to ascertain,TRUE,NA +80136,both interview and exam,male,65,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,FALSE,22500 +80137,both interview and exam,male,30,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,married,NA,TRUE,40000 +80138,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +80139,both interview and exam,female,39,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,divorced,no,TRUE,50000 +80140,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +80141,both interview and exam,male,16,NA,black,1,204,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +80142,both interview and exam,male,3,NA,white,1,38,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,100000 +80143,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,never_married,NA,TRUE,NA +80144,both interview and exam,male,50,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +80145,both interview and exam,male,22,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,FALSE,7500 +80146,both interview and exam,male,33,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,FALSE,7500 +80147,both interview and exam,female,0,4,white,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80148,both interview and exam,male,80,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,7500 +80149,both interview and exam,female,20,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,NA +80150,both interview and exam,female,12,NA,other hispanic,2,151,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,22500 +80151,both interview and exam,male,6,NA,white,2,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +80152,both interview and exam,male,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +80153,both interview and exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80154,both interview and exam,female,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +80155,both interview and exam,male,52,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,FALSE,NA +80156,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +80157,interview only,female,42,NA,mexican american,NA,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,unable to ascertain,FALSE,22500 +80158,both interview and exam,male,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +80159,both interview and exam,male,7,NA,black,2,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,2500 +80160,both interview and exam,female,13,NA,white,1,161,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +80161,both interview and exam,female,10,NA,other hispanic,2,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,50000 +80162,both interview and exam,female,17,NA,white,2,211,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,60000 +80163,both interview and exam,female,63,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +80164,both interview and exam,male,19,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,12500 +80165,both interview and exam,female,65,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,60000 +80166,both interview and exam,male,17,NA,other hispanic,1,210,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +80167,both interview and exam,female,9,NA,white,1,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +80168,both interview and exam,male,38,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +80169,both interview and exam,female,42,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,no,FALSE,NA +80170,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 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exam,male,9,NA,other,1,117,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +80181,both interview and exam,female,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,30000 +80182,both interview and exam,female,14,NA,asian,1,171,NA,NA,FALSE,FALSE,0.5,7,NA,NA,NA,TRUE,2500 +80183,both interview and exam,male,75,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,40000 +80184,both interview and exam,male,13,NA,other hispanic,2,166,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +80185,both interview and exam,male,61,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,2,married,NA,TRUE,30000 +80186,both interview and exam,female,10,NA,black,2,131,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80187,both interview and exam,male,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +80188,both interview and exam,male,55,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,50000 +80189,both interview and exam,male,18,NA,other,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +80190,both interview and exam,female,33,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +80191,both interview and exam,male,6,NA,other,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,50000 +80192,both interview and exam,male,0,6,black,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80193,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,60000 +80194,both interview and exam,female,18,NA,mexican american,1,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +80195,both interview and exam,male,1,13,mexican american,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +80196,both interview and exam,male,13,NA,mexican american,2,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,70000 +80197,both interview and exam,male,44,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,living_with_partner,NA,FALSE,30000 +80198,both interview and exam,female,7,NA,white,1,91,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +80199,both interview and exam,female,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,50000 +80200,both interview and exam,male,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +80201,both interview and exam,female,63,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,divorced,NA,TRUE,30000 +80202,both interview and exam,male,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +80203,both interview and exam,male,67,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,NA +80204,both interview and exam,male,59,NA,white,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,TRUE,40000 +80205,both interview and exam,male,75,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +80206,both interview and exam,female,63,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,55,NA,2,married,NA,FALSE,12500 +80207,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +80208,interview only,male,1,20,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80209,both interview and exam,male,0,3,black,2,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80210,both interview and exam,male,37,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,FALSE,87500 +80211,both interview and exam,female,7,NA,mexican american,1,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +80212,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +80213,both interview and exam,female,0,5,mexican american,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80214,both interview and exam,male,46,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +80215,both interview and exam,male,22,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +80216,both interview and 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exam,female,12,NA,white,2,152,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +80244,both interview and exam,female,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,yes,TRUE,100000 +80245,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +80246,both interview and exam,male,4,NA,white,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80247,both interview and exam,female,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,17500 +80248,both interview and exam,female,29,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +80249,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +80250,both interview and exam,male,72,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +80251,both interview and exam,female,27,NA,black,2,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,no,TRUE,40000 +80252,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +80253,both interview and exam,male,8,NA,asian,2,104,NA,NA,FALSE,FALSE,7.5,2,NA,NA,NA,TRUE,87500 +80254,both interview and exam,female,31,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,unable to ascertain,TRUE,60000 +80255,interview only,female,3,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80256,both interview and exam,male,2,NA,other hispanic,1,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +80257,both interview and exam,female,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +80258,both interview and exam,male,19,NA,black,2,229,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +80259,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,40000 +80260,both interview and exam,male,40,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,TRUE,87500 +80261,both interview and exam,female,38,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,100000 +80262,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +80263,both interview and exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +80264,both interview and exam,female,21,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,NA +80265,both interview and exam,female,35,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,100000 +80266,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +80267,both interview and exam,male,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +80268,both interview and exam,male,71,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,60000 +80269,both interview and exam,male,25,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,never_married,NA,TRUE,40000 +80270,interview only,male,37,NA,mexican 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exam,male,38,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80280,both interview and exam,female,31,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,living_with_partner,no,FALSE,100000 +80281,both interview and exam,female,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +80282,both interview and exam,female,5,NA,mexican american,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +80283,both interview and exam,female,13,NA,other hispanic,1,162,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,2500 +80284,both interview and exam,male,11,NA,black,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80285,both interview and exam,male,50,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +80286,both interview and exam,male,38,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,40000 +80287,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,60000 +80288,both interview and exam,male,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,17500 +80289,both interview and exam,female,37,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,no,TRUE,12500 +80290,both interview and exam,male,1,13,black,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80291,both interview and exam,male,31,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +80292,both interview and exam,female,69,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +80293,both interview and exam,female,11,NA,black,2,142,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +80294,both interview and exam,female,75,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +80295,both interview and exam,female,38,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,no,TRUE,87500 +80296,both interview and exam,female,64,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,22500 +80297,both interview and exam,female,16,NA,mexican american,2,194,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +80298,both interview and exam,female,4,NA,other hispanic,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80299,both interview and exam,male,15,NA,black,1,181,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +80300,both interview and exam,female,61,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +80301,both interview and exam,male,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +80302,both interview and exam,female,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,unable to ascertain,TRUE,12500 +80303,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +80304,both interview and exam,male,43,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,30000 +80305,both interview and exam,female,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +80306,both interview and exam,female,4,NA,mexican american,2,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80307,both interview and exam,female,75,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,17500 +80308,both interview and exam,male,39,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,TRUE,60000 +80309,both interview and exam,female,44,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,no,FALSE,NA +80310,both interview and exam,male,18,NA,black,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +80311,both interview and exam,female,11,NA,black,1,142,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +80312,both interview and exam,male,40,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +80313,both interview and exam,female,2,NA,white,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80314,both interview and exam,female,10,NA,black,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +80315,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +80316,both interview and exam,female,11,NA,black,2,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,NA +80317,both interview and exam,female,14,NA,white,1,177,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +80318,both interview and exam,female,2,NA,black,1,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +80319,both interview and exam,female,8,NA,mexican american,1,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +80320,both interview and exam,female,9,NA,black,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +80321,both interview and exam,male,72,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +80322,both interview and exam,female,55,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,TRUE,70000 +80323,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,2500 +80324,both interview and exam,female,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +80325,both interview and exam,female,19,NA,mexican american,1,234,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,22500 +80326,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +80327,both interview and exam,male,27,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,5,never_married,NA,TRUE,12500 +80328,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +80329,both interview and exam,female,69,NA,mexican american,1,NA,FALSE,NA,FALSE,NA,35,NA,1,separated,NA,TRUE,70000 +80330,both interview and exam,male,73,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,50000 +80331,both interview and exam,male,27,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +80332,both interview and exam,male,24,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,17500 +80333,both interview and exam,female,45,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,NA +80334,both interview and exam,female,14,NA,white,2,173,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +80335,both interview and exam,male,28,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,30000 +80336,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +80337,both interview and exam,female,14,NA,asian,2,180,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +80338,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,30000 +80339,both interview and exam,female,37,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,living_with_partner,no,FALSE,17500 +80340,both interview and exam,male,61,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +80341,both interview and exam,female,8,NA,white,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,70000 +80342,both interview and exam,female,2,NA,black,1,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80343,both interview and exam,female,24,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,no,TRUE,NA +80344,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +80345,both interview and exam,female,71,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,55,NA,1,married,NA,FALSE,22500 +80346,both interview and exam,male,6,NA,white,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +80347,both interview and exam,female,44,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,living_with_partner,no,FALSE,NA +80348,both interview and exam,female,10,NA,asian,2,121,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +80349,both interview and exam,female,28,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,60000 +80350,both interview and exam,female,31,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +80351,both interview and exam,female,37,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +80352,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,40000 +80353,both interview and exam,female,9,NA,mexican american,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,70000 +80354,both interview and exam,female,12,NA,asian,2,151,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +80355,both interview and exam,female,70,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,separated,NA,FALSE,12500 +80356,both interview and exam,male,12,NA,black,1,145,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +80357,both interview and exam,female,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,12500 +80358,both interview and exam,male,4,NA,black,1,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80359,both interview and exam,male,4,NA,other hispanic,2,53,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +80360,both interview and exam,female,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80361,both interview and exam,male,19,NA,white,2,231,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,100000 +80362,both interview and exam,female,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80363,both interview and exam,female,13,NA,asian,2,162,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +80364,both interview and exam,female,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +80365,both interview and exam,female,34,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,never_married,no,TRUE,100000 +80366,both interview and exam,male,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80367,both interview and exam,female,71,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,FALSE,22500 +80368,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +80369,both interview and exam,female,31,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,no,TRUE,30000 +80370,both interview and exam,male,0,10,black,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80371,both interview and exam,female,39,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,no,TRUE,40000 +80372,both interview and exam,male,42,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80373,both interview and exam,female,1,16,mexican american,2,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80374,both interview and exam,female,0,5,black,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +80375,both interview and exam,male,47,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,100000 +80376,both interview and exam,female,3,NA,white,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +80377,both interview and exam,male,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +80378,both interview and exam,female,3,NA,mexican american,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80379,both interview and exam,male,67,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,30000 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exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,12500 +80390,both interview and exam,female,65,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +80391,both interview and exam,male,23,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,never_married,NA,FALSE,22500 +80392,both interview and exam,female,16,NA,white,1,195,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +80393,both interview and exam,male,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +80394,both interview and exam,male,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,87500 +80395,both interview and exam,male,9,NA,mexican american,1,110,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +80396,both interview and exam,male,31,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +80397,both interview and exam,female,50,NA,white,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,NA +80398,both interview and exam,female,17,NA,asian,1,205,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +80399,interview only,male,3,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80400,both interview and exam,male,0,1,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80401,both interview and exam,female,19,NA,black,2,239,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,17500 +80402,both interview and exam,male,66,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +80403,both interview and exam,female,38,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,no,TRUE,40000 +80404,both interview and exam,male,0,1,black,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +80405,both interview and exam,female,24,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,yes,TRUE,22500 +80406,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,NA +80407,both interview and exam,female,15,NA,white,2,192,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +80408,both interview and exam,female,43,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,widowed,no,TRUE,40000 +80409,both interview and exam,female,5,NA,white,1,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80410,both interview and exam,male,47,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,NA,TRUE,NA +80411,both interview and exam,male,41,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,living_with_partner,NA,FALSE,22500 +80412,both interview and exam,male,3,NA,white,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80413,both interview and exam,male,46,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +80414,both interview and exam,male,24,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,never_married,NA,FALSE,40000 +80415,both interview and exam,male,6,NA,white,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +80416,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +80417,both interview and exam,female,60,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,TRUE,22500 +80418,both interview and exam,male,2,NA,other hispanic,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +80419,both interview and exam,female,12,NA,black,1,152,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +80420,both interview and exam,female,6,NA,black,2,73,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +80421,both interview and exam,female,13,NA,white,2,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +80422,both interview and exam,female,0,1,white,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80423,both interview and exam,male,8,NA,white,1,104,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +80424,both interview and exam,female,14,NA,other hispanic,1,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +80425,both interview and exam,male,19,NA,mexican american,2,231,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,22500 +80426,both interview and exam,female,0,9,mexican american,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 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american,2,NA,FALSE,NA,FALSE,TRUE,55,NA,2,widowed,NA,FALSE,12500 +80437,both interview and exam,female,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80438,both interview and exam,female,37,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,no,TRUE,12500 +80439,both interview and exam,female,1,20,mexican american,2,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80440,both interview and exam,female,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +80441,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +80442,both interview and exam,female,41,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,no,FALSE,NA +80443,both interview and exam,female,8,NA,mexican american,2,108,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +80444,both interview and exam,female,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,unable to ascertain,TRUE,NA +80445,both interview and exam,male,22,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +80446,both interview and exam,female,31,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,87500 +80447,both interview and exam,female,8,NA,asian,2,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +80448,both interview and exam,female,26,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,never_married,no,TRUE,100000 +80449,both interview and exam,female,7,NA,other hispanic,2,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +80450,interview only,female,75,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +80451,both interview and exam,male,12,NA,white,2,151,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +80452,both interview and exam,female,1,23,white,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +80453,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +80454,both interview and exam,male,63,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,55,NA,1,divorced,NA,TRUE,2500 +80455,both interview and exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80456,both interview and exam,female,47,NA,other,2,NA,FALSE,NA,FALSE,TRUE,45,NA,5,divorced,NA,TRUE,87500 +80457,both interview and exam,female,16,NA,other hispanic,2,200,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +80458,both interview and exam,female,24,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,married,unable to ascertain,FALSE,17500 +80459,both interview and exam,female,16,NA,mexican american,2,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,70000 +80460,both interview and exam,female,12,NA,white,2,152,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +80461,both interview and exam,female,3,NA,white,2,37,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80462,both interview and exam,male,2,NA,white,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80463,both interview and exam,female,13,NA,black,1,161,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 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exam,female,13,NA,black,2,161,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +80474,both interview and exam,female,20,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +80475,both interview and exam,male,16,NA,black,1,201,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +80476,both interview and exam,male,12,NA,other,2,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80477,both interview and exam,male,49,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,100000 +80478,both interview and exam,female,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80479,both interview and exam,male,62,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +80480,both interview and exam,male,16,NA,other hispanic,1,203,NA,NA,FALSE,FALSE,0.5,8,NA,NA,NA,FALSE,22500 +80481,both interview and exam,male,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,17500 +80482,both interview and exam,female,55,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +80483,interview only,female,56,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,12500 +80484,both interview and exam,male,13,NA,mexican american,1,168,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,87500 +80485,both interview and exam,male,0,9,other,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80486,both interview and exam,female,69,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80487,both interview and exam,female,6,NA,mexican american,2,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +80488,interview only,male,7,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +80489,both interview and exam,female,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,60000 +80490,both interview and exam,female,33,NA,black,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,never_married,no,TRUE,40000 +80491,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,100000 +80492,both interview and exam,female,35,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,no,TRUE,50000 +80493,both interview and exam,male,52,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +80494,interview only,female,22,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,unable to ascertain,TRUE,2500 +80495,both interview and exam,male,0,0,white,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80496,both interview and exam,female,48,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,70000 +80497,both interview and exam,female,37,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,separated,no,FALSE,30000 +80498,both interview and exam,male,64,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,NA,TRUE,100000 +80499,both interview and exam,male,7,NA,mexican american,1,93,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +80500,both interview and 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exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80510,both interview and exam,male,10,NA,white,1,124,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +80511,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,12500 +80512,both interview and exam,female,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +80513,both interview and exam,female,40,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +80514,both interview and exam,female,1,22,white,1,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80515,both interview and exam,female,12,NA,asian,2,150,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +80516,both interview and exam,female,42,NA,black,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,living_with_partner,no,TRUE,70000 +80517,both interview and exam,male,55,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +80518,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80519,both interview and exam,female,36,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,no,FALSE,40000 +80520,both interview and exam,female,40,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,50000 +80521,both interview and exam,male,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80522,both interview and exam,male,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +80523,both interview and exam,male,52,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,never_married,NA,FALSE,12500 +80524,both interview and exam,female,12,NA,other,2,148,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +80525,both interview and exam,female,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,30000 +80526,both interview and exam,female,35,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,2500 +80527,both interview and exam,male,0,10,mexican 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american,1,222,FALSE,NA,FALSE,FALSE,17.5,12,NA,NA,NA,TRUE,40000 +80854,both interview and exam,female,27,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +80855,both interview and exam,female,12,NA,other hispanic,1,155,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +80856,both interview and exam,female,11,NA,mexican american,1,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,30000 +80857,both interview and exam,male,17,NA,white,2,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +80858,both interview and exam,male,65,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80859,both interview and exam,female,75,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +80860,both interview and exam,female,9,NA,black,1,117,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +80861,both interview and exam,female,0,11,mexican american,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +80862,both interview and exam,male,21,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,never_married,NA,TRUE,100000 +80863,both interview and exam,female,37,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,no,TRUE,100000 +80864,both interview and exam,male,54,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,7500 +80865,both interview and exam,female,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,7500 +80866,both interview and exam,male,0,1,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80867,both interview and exam,female,6,NA,mexican american,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,50000 +80868,both interview and exam,female,61,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,3,widowed,NA,FALSE,100000 +80869,both interview and exam,male,18,NA,white,1,221,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +80870,both interview and exam,male,10,NA,other hispanic,2,128,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,12500 +80871,both interview and exam,female,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +80872,both interview and exam,male,66,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,TRUE,NA +80873,both interview and exam,female,36,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,no,TRUE,100000 +80874,interview only,female,74,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +80875,both interview and exam,female,0,5,mexican american,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80876,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,70000 +80877,both interview and exam,male,8,NA,black,1,106,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +80878,both interview and exam,female,65,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +80879,both interview and exam,female,48,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +80880,both interview and exam,male,28,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,40000 +80881,both interview and exam,female,30,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,NA +80882,both interview and exam,male,18,NA,black,2,220,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,50000 +80883,both interview and exam,male,18,NA,mexican american,2,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,22500 +80884,both interview and exam,male,60,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,17500 +80885,both interview and exam,male,32,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +80886,both interview and exam,male,4,NA,other,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80887,interview only,male,2,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +80888,both interview and exam,female,4,NA,other,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80889,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +80890,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +80891,both interview and exam,female,1,14,white,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80892,both interview and exam,female,59,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +80893,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +80894,both interview and exam,female,67,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +80895,both interview and exam,male,14,NA,asian,1,180,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +80896,both interview and exam,female,9,NA,mexican american,2,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +80897,both interview and exam,male,7,NA,black,1,89,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,2500 +80898,both interview and exam,male,76,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,7500 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exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +80909,both interview and exam,female,12,NA,mexican american,1,151,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,40000 +80910,both interview and exam,male,14,NA,black,1,169,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +80911,both interview and exam,male,44,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80912,both interview and exam,female,28,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,no,FALSE,87500 +80913,both interview and exam,male,1,15,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +80914,both interview and exam,female,2,NA,other,2,34,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,2500 +80915,both interview and exam,female,66,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +80916,both interview and exam,female,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,100000 +80917,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +80918,both interview and exam,female,3,NA,black,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80919,both interview and exam,male,6,NA,asian,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +80920,both interview and exam,female,28,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,living_with_partner,unable to ascertain,FALSE,30000 +80921,both interview and exam,female,25,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,2,living_with_partner,no,FALSE,87500 +80922,both interview and exam,male,14,NA,mexican american,2,177,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,17500 +80923,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +80924,both interview and exam,female,39,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,NA +80925,both interview and exam,male,3,NA,black,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80926,both interview and exam,female,1,21,other hispanic,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80927,both interview and exam,male,4,NA,other,2,60,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80928,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,70000 +80929,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,40000 +80930,both interview and exam,male,73,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,100000 +80931,both interview and exam,female,11,NA,other,2,138,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80932,both interview and exam,male,39,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +80933,both interview and exam,male,11,NA,other hispanic,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +80934,both interview and exam,male,65,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,TRUE,22500 +80935,both interview and exam,female,0,1,white,1,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80936,both interview and exam,male,38,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80937,both interview and exam,female,18,NA,black,1,227,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,12500 +80938,both interview and exam,female,19,NA,white,2,232,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +80939,both interview and exam,male,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +80940,both interview and exam,female,11,NA,black,1,134,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +80941,both interview and exam,female,51,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +80942,both interview and exam,male,3,NA,white,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +80943,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,22500 +80944,both interview and exam,male,11,NA,black,2,137,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +80945,both interview and exam,male,61,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,TRUE,60000 +80946,both interview and exam,male,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +80947,both interview and exam,male,12,NA,white,1,156,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +80948,both interview and exam,male,18,NA,black,1,219,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +80949,both interview and exam,female,7,NA,mexican american,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +80950,both interview and exam,male,0,4,other hispanic,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80951,both interview and exam,female,5,NA,white,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +80952,both interview and exam,female,1,15,other hispanic,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,70000 +80953,both interview and exam,male,15,NA,mexican american,2,188,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +80954,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +80955,both interview and exam,female,72,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +80956,both interview and exam,female,18,NA,asian,2,221,FALSE,NA,FALSE,FALSE,0.5,12,NA,NA,NA,TRUE,2500 +80957,both interview and exam,male,12,NA,black,1,156,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +80958,both interview and exam,male,9,NA,mexican american,2,113,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +80959,interview only,female,24,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,living_with_partner,unable to ascertain,TRUE,70000 +80960,both interview and exam,male,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,30000 +80961,both interview and exam,female,41,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,87500 +80962,both interview and exam,female,72,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,22500 +80963,both interview and exam,male,4,NA,black,1,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +80964,both interview and exam,female,19,NA,white,1,238,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,60000 +80965,both interview and exam,male,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +80966,both interview and exam,female,27,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,50000 +80967,both interview and exam,male,40,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,FALSE,22500 +80968,both interview and exam,male,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +80969,interview only,female,17,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +80970,both interview and exam,male,14,NA,mexican american,1,171,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +80971,both interview and exam,male,8,NA,white,2,103,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +80972,both interview and exam,male,8,NA,asian,1,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +80973,both interview and exam,female,47,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,NA,TRUE,12500 +80974,both interview and exam,female,14,NA,other,2,175,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +80975,both interview and exam,female,26,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,22500 +80976,both interview and exam,male,59,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +80977,both interview and exam,male,0,8,mexican american,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +80978,both interview and exam,male,0,1,other,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80979,both interview and exam,male,29,NA,other hispanic,1,NA,TRUE,FALSE,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +80980,both interview and exam,female,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,50000 +80981,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +80982,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +80983,both interview and exam,female,5,NA,black,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +80984,both interview and exam,female,7,NA,other,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +80985,both interview and exam,male,46,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,25,NA,5,married,NA,TRUE,87500 +80986,both interview and exam,female,1,19,other,2,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +80987,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,30000 +80988,both interview and exam,female,65,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,30000 +80989,both interview and exam,male,46,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +80990,both interview and exam,male,35,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,NA +80991,both interview and exam,female,11,NA,black,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +80992,both interview and exam,female,16,NA,white,1,198,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +80993,both interview and exam,male,11,NA,white,1,136,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +80994,both interview and exam,male,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +80995,both interview and exam,female,2,NA,black,2,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +80996,both interview and exam,female,4,NA,mexican american,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +80997,both interview and exam,male,26,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,17500 +80998,both interview and exam,female,0,3,black,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +80999,both interview and exam,male,15,NA,white,2,192,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +81000,both interview and exam,male,28,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +81001,both interview and exam,female,13,NA,other hispanic,2,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,40000 +81002,both interview and exam,male,9,NA,white,1,109,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +81003,both interview and exam,female,16,NA,white,2,192,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +81004,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +81005,both interview and exam,female,1,16,white,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81006,both interview and exam,female,10,NA,mexican american,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +81007,interview only,female,3,NA,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81008,both interview and exam,male,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81009,both interview and exam,female,56,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,TRUE,17500 +81010,both interview and exam,male,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +81011,both interview and exam,female,60,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81012,both interview and exam,male,34,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,12500 +81013,both interview and exam,male,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81014,both interview and exam,male,27,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +81015,both interview and exam,female,20,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +81016,both interview and exam,male,6,NA,other hispanic,1,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +81017,both interview and exam,male,15,NA,white,2,187,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,60000 +81018,both interview and exam,female,9,NA,black,2,113,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,50000 +81019,both interview and exam,female,14,NA,black,1,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +81020,both interview and exam,male,40,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +81021,interview only,male,2,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81022,both interview and exam,male,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,30000 +81023,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,yes,TRUE,17500 +81024,both interview and exam,male,6,NA,white,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +81025,both interview and exam,female,69,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,divorced,NA,FALSE,NA +81026,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,30000 +81027,both interview and exam,female,0,9,black,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81028,both interview and exam,male,12,NA,other hispanic,1,147,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,NA +81029,both interview and exam,male,43,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,married,NA,FALSE,NA +81030,both interview and exam,male,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,NA +81031,both interview and exam,male,9,NA,black,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,2500 +81032,both interview and exam,male,71,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +81033,both interview and exam,female,9,NA,mexican american,1,120,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,30000 +81034,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +81035,both interview and exam,male,10,NA,white,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +81036,both interview and exam,male,2,NA,black,1,37,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81037,both interview and exam,male,60,NA,black,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,NA,TRUE,87500 +81038,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +81039,both interview and exam,male,64,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,7500 +81040,both interview and exam,female,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,60000 +81041,both interview and exam,female,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +81042,both interview and exam,male,63,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,separated,NA,TRUE,100000 +81043,both interview and exam,female,18,NA,white,2,218,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +81044,both interview and exam,male,10,NA,mexican american,1,130,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,30000 +81045,both interview and exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81046,interview only,female,4,NA,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81047,both interview and exam,female,8,NA,mexican american,2,108,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +81048,both interview and exam,female,13,NA,black,1,162,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,2500 +81049,both interview and exam,female,12,NA,other hispanic,1,146,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81050,both interview and exam,female,38,NA,other,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,no,TRUE,50000 +81051,both interview and exam,male,41,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81052,both interview and exam,female,44,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,70000 +81053,both interview and exam,male,3,NA,mexican american,1,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +81054,both interview and exam,female,66,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,22500 +81055,both interview and exam,female,48,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,40000 +81056,both interview and exam,female,49,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +81057,both interview and exam,female,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +81058,both interview and exam,female,5,NA,white,2,70,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81059,both interview and exam,male,4,NA,other hispanic,1,59,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81060,both interview and exam,female,14,NA,white,2,172,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +81061,both interview and exam,male,44,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +81062,interview only,female,48,NA,asian,NA,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +81063,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,22500 +81064,both interview and exam,male,11,NA,white,2,141,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,22500 +81065,both interview and exam,female,19,NA,black,2,231,FALSE,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +81066,both interview and exam,female,1,18,white,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81067,both interview and exam,female,7,NA,white,1,85,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +81068,both interview and exam,male,59,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81069,both interview and exam,female,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,no,TRUE,7500 +81070,both interview and exam,male,31,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,NA,FALSE,40000 +81071,both interview and exam,male,2,NA,mexican american,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81072,both interview and exam,male,17,NA,mexican american,2,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,22500 +81073,both interview and exam,female,13,NA,black,2,164,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,NA +81074,both interview and exam,female,19,NA,other hispanic,1,234,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,22500 +81075,both interview and exam,male,30,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +81076,both interview and exam,female,18,NA,asian,2,224,FALSE,NA,FALSE,TRUE,7.5,13,NA,NA,NA,TRUE,30000 +81077,both interview and exam,male,0,8,mexican american,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81078,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,25,NA,4,never_married,NA,FALSE,NA +81079,both interview and exam,male,76,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,17500 +81080,both interview and exam,female,12,NA,black,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81081,both interview and exam,male,3,NA,black,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81082,both interview and exam,female,60,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,never_married,NA,FALSE,NA +81083,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81084,both interview and exam,female,26,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,never_married,no,TRUE,100000 +81085,both interview and exam,male,4,NA,other,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81086,interview only,female,9,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +81087,both interview and exam,female,36,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81088,both interview and exam,female,54,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,30000 +81089,both interview and exam,male,11,NA,other hispanic,1,144,NA,NA,FALSE,FALSE,7.5,6,NA,NA,NA,FALSE,NA +81090,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,22500 +81091,both interview and exam,female,11,NA,black,1,136,NA,NA,FALSE,FALSE,NA,5,NA,NA,NA,TRUE,30000 +81092,both interview and exam,male,29,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,living_with_partner,NA,TRUE,12500 +81093,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,17500 +81094,both interview and exam,male,6,NA,other hispanic,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +81095,both interview and exam,male,51,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,40000 +81096,both interview and exam,female,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,unable to ascertain,TRUE,7500 +81097,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,30000 +81098,both interview and exam,female,5,NA,white,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81099,both interview and exam,female,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +81100,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +81101,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +81102,both interview and exam,male,4,NA,mexican american,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +81103,both interview and exam,male,80,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +81104,both interview and exam,female,67,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,7500 +81105,both interview and exam,male,63,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +81106,both interview and exam,female,10,NA,mexican american,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,87500 +81107,both interview and exam,female,54,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81108,both interview and exam,female,13,NA,mexican american,1,167,NA,NA,FALSE,FALSE,12.5,7,NA,NA,NA,FALSE,30000 +81109,both interview and exam,female,77,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81110,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81111,both interview and exam,female,77,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +81112,both interview and exam,female,3,NA,white,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81113,interview only,female,80,NA,other,NA,NA,FALSE,NA,FALSE,TRUE,55,NA,3,married,NA,TRUE,40000 +81114,both interview and exam,female,9,NA,black,1,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +81115,both interview and exam,male,60,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,100000 +81116,both interview and exam,female,16,NA,mexican american,1,200,NA,NA,FALSE,FALSE,7.5,10,NA,NA,NA,TRUE,22500 +81117,both interview and exam,male,19,NA,mexican american,1,236,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,FALSE,40000 +81118,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,no,TRUE,60000 +81119,both interview and exam,female,37,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,87500 +81120,both interview and exam,male,3,NA,other hispanic,1,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81121,both interview and exam,male,61,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +81122,both interview and exam,female,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,22500 +81123,both interview and exam,male,8,NA,white,1,103,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81124,both interview and exam,female,15,NA,white,2,190,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,7500 +81125,both interview and exam,male,15,NA,white,2,192,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +81126,both interview and exam,female,11,NA,other hispanic,2,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +81127,both interview and exam,male,9,NA,white,2,112,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +81128,both interview and exam,female,10,NA,other,2,125,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +81129,both interview and exam,male,12,NA,black,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,50000 +81130,both interview and exam,male,18,NA,asian,2,226,FALSE,NA,FALSE,TRUE,12.5,14,NA,NA,NA,TRUE,100000 +81131,both interview and exam,male,49,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +81132,both interview and exam,male,6,NA,black,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +81133,both interview and exam,female,17,NA,white,2,210,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81134,both interview and exam,female,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81135,both interview and exam,male,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,60000 +81136,both interview and exam,female,78,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,3,widowed,NA,TRUE,22500 +81137,both interview and exam,female,16,NA,mexican american,1,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +81138,both interview and exam,female,42,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,4,married,no,TRUE,100000 +81139,both interview and exam,male,23,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,4,never_married,NA,TRUE,87500 +81140,both interview and exam,male,6,NA,asian,1,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81141,both interview and exam,male,70,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,22500 +81142,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +81143,interview only,female,80,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +81144,both interview and exam,male,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +81145,both interview and exam,female,3,NA,black,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81146,both interview and exam,female,8,NA,other,2,99,NA,NA,FALSE,FALSE,0.5,0,NA,NA,NA,TRUE,2500 +81147,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81148,both interview and exam,female,73,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +81149,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81150,both interview and exam,male,13,NA,mexican american,2,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +81151,both interview and exam,male,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81152,both interview and exam,female,34,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,yes,TRUE,40000 +81153,both interview and exam,female,30,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,no,TRUE,30000 +81154,both interview and exam,male,50,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,25,NA,3,married,NA,FALSE,70000 +81155,both interview and exam,female,56,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +81156,both interview and exam,male,7,NA,black,1,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +81157,both interview and exam,female,3,NA,mexican american,2,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81158,both interview and exam,female,13,NA,mexican american,1,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,NA +81159,both interview and exam,female,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,60000 +81160,both interview and exam,male,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +81161,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,17500 +81162,both interview and exam,female,80,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,widowed,NA,TRUE,87500 +81163,both interview and exam,female,79,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,30000 +81164,both interview and exam,male,5,NA,black,1,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81165,both interview and exam,male,51,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,FALSE,100000 +81166,both interview and exam,female,73,NA,white,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,NA,TRUE,7500 +81167,both interview and exam,male,7,NA,white,1,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81168,both interview and exam,female,28,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,never_married,no,TRUE,60000 +81169,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +81170,both interview and exam,female,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,40000 +81171,both interview and exam,female,49,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,60000 +81172,both interview and exam,female,4,NA,white,1,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +81173,both interview and exam,female,50,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +81174,both interview and exam,female,31,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,30000 +81175,both interview and exam,male,80,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +81176,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,no,FALSE,40000 +81177,both interview and exam,female,48,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81178,both interview and exam,male,24,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +81179,interview only,male,80,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,NA +81180,both interview and exam,female,14,NA,mexican american,2,176,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +81181,both interview and exam,male,4,NA,white,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81182,both interview and exam,female,16,NA,asian,1,203,NA,NA,FALSE,FALSE,3,9,NA,NA,NA,TRUE,7500 +81183,both interview and exam,female,5,NA,mexican american,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81184,both interview and exam,male,7,NA,white,2,91,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81185,interview only,female,25,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,unable to ascertain,TRUE,100000 +81186,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +81187,both interview and exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,22500 +81188,both interview and exam,female,14,NA,mexican american,2,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +81189,both interview and exam,male,5,NA,white,2,63,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81190,both interview and exam,female,23,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +81191,both interview and exam,female,14,NA,asian,2,176,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +81192,both interview and exam,female,41,NA,other,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,TRUE,70000 +81193,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +81194,both interview and exam,female,11,NA,mexican american,2,144,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +81195,both interview and exam,female,4,NA,mexican american,1,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +81196,both interview and exam,female,41,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,divorced,no,TRUE,40000 +81197,both interview and exam,female,47,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,NA +81198,both interview and exam,male,0,7,black,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81199,both interview and exam,female,10,NA,asian,2,122,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,40000 +81200,both interview and exam,male,5,NA,black,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81201,both interview and exam,male,56,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,FALSE,40000 +81202,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,22500 +81203,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81204,both interview and exam,female,65,NA,black,2,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,TRUE,NA +81205,both interview and exam,female,4,NA,white,2,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81206,both interview and exam,male,47,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +81207,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,NA,TRUE,100000 +81208,both interview and exam,female,2,NA,black,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +81209,both interview and exam,male,58,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,100000 +81210,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,100000 +81211,both interview and exam,male,3,NA,asian,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81212,both interview and exam,female,37,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +81213,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,married,NA,TRUE,40000 +81214,both interview and exam,male,50,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,NA,TRUE,30000 +81215,both interview and exam,female,0,7,white,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81216,both interview and exam,female,30,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81217,both interview and exam,male,45,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +81218,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81219,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,40000 +81220,both interview and exam,male,12,NA,white,2,150,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81221,both interview and exam,female,68,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,widowed,NA,FALSE,100000 +81222,both interview and exam,male,14,NA,white,2,174,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +81223,both interview and exam,female,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,17500 +81224,both interview and exam,female,18,NA,white,2,221,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,100000 +81225,both interview and exam,male,37,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +81226,both interview and exam,male,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,12500 +81227,both interview and exam,female,12,NA,white,1,150,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,NA +81228,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81229,both interview and exam,male,74,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,widowed,NA,FALSE,2500 +81230,both interview and exam,female,52,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +81231,both interview and exam,female,44,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,12500 +81232,both interview and exam,female,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +81233,both interview and exam,male,10,NA,white,2,122,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +81234,both interview and exam,male,67,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,55,NA,5,divorced,NA,TRUE,NA +81235,both interview and exam,male,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +81236,both interview and exam,female,7,NA,black,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +81237,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +81238,both interview and exam,female,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,40000 +81239,both interview and exam,female,14,NA,white,2,179,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,22500 +81240,both interview and exam,male,7,NA,black,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +81241,both interview and exam,male,51,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,50000 +81242,both interview and exam,male,14,NA,mexican american,1,177,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,17500 +81243,both interview and exam,male,8,NA,black,1,100,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +81244,both interview and exam,female,47,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81245,interview only,female,16,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +81246,both interview and exam,male,17,NA,black,1,215,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,22500 +81247,both interview and exam,male,15,NA,black,1,187,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +81248,both interview and exam,female,68,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +81249,both interview and exam,female,7,NA,white,2,88,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81250,both interview and exam,male,50,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,7500 +81251,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,FALSE,TRUE,55,NA,3,widowed,NA,TRUE,22500 +81252,both interview and exam,male,15,NA,black,2,189,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +81253,both interview and exam,male,4,NA,mexican american,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81254,both interview and exam,female,12,NA,other hispanic,2,156,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,NA +81255,both interview and exam,female,1,20,white,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81256,both interview and exam,male,69,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,12500 +81257,both interview and exam,male,7,NA,black,1,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +81258,both interview and exam,male,2,NA,other,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +81259,both interview and exam,male,75,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +81260,both interview and exam,male,44,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,100000 +81261,both interview and exam,female,14,NA,white,2,177,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +81262,both interview and exam,female,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81263,both interview and exam,male,2,NA,black,2,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81264,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,87500 +81265,both interview and exam,male,7,NA,other,2,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +81266,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +81267,both interview and exam,female,75,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +81268,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,12500 +81269,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +81270,both interview and exam,male,43,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,100000 +81271,interview only,male,1,14,other,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81272,both interview and exam,female,46,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,never_married,NA,FALSE,NA +81273,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +81274,both interview and exam,male,13,NA,mexican american,2,164,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +81275,both interview and exam,female,50,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,FALSE,30000 +81276,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81277,both interview and exam,male,3,NA,mexican american,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +81278,both interview and exam,male,18,NA,other,2,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +81279,both interview and exam,male,7,NA,other,2,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +81280,both interview and exam,male,15,NA,asian,1,182,NA,NA,FALSE,FALSE,12.5,8,NA,NA,NA,TRUE,100000 +81281,both interview and exam,male,17,NA,black,1,207,FALSE,NA,FALSE,FALSE,NA,11,NA,NA,NA,TRUE,NA +81282,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +81283,both interview and exam,female,67,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,TRUE,40000 +81284,both interview and exam,female,64,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,married,NA,FALSE,30000 +81285,both interview and exam,female,74,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +81286,both interview and exam,female,16,NA,asian,1,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +81287,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,60000 +81288,both interview and exam,female,71,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,widowed,NA,TRUE,17500 +81289,both interview and exam,female,17,NA,white,2,211,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81290,both interview and exam,male,30,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,2500 +81291,both interview and exam,male,21,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +81292,both interview and exam,male,47,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,87500 +81293,both interview and exam,male,7,NA,black,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81294,both interview and exam,male,18,NA,black,1,220,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +81295,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81296,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +81297,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,50000 +81298,both interview and exam,male,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,NA,NA,5,married,NA,TRUE,NA +81299,both interview and exam,female,2,NA,white,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81300,both interview and exam,male,17,NA,white,1,215,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +81301,both interview and exam,male,3,NA,white,1,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81302,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +81303,both interview and exam,male,20,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +81304,both interview and exam,female,20,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,never_married,unable to ascertain,FALSE,87500 +81305,both interview and exam,female,2,NA,mexican american,2,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +81306,both interview and exam,male,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +81307,both interview and exam,female,8,NA,mexican american,2,106,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +81308,both interview and exam,male,4,NA,mexican american,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +81309,both interview and exam,female,55,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,40000 +81310,both interview and exam,male,19,NA,mexican american,2,239,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +81311,both interview and exam,male,68,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,NA +81312,both interview and exam,female,19,NA,asian,2,237,FALSE,NA,FALSE,FALSE,3,13,NA,NA,NA,TRUE,22500 +81313,both interview and exam,male,20,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +81314,both interview and exam,male,10,NA,other,1,128,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +81315,both interview and exam,male,3,NA,other,2,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81316,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,40000 +81317,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81318,both interview and exam,female,16,NA,white,2,198,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +81319,both interview and exam,female,38,NA,black,1,NA,FALSE,NA,FALSE,FALSE,35,NA,4,divorced,no,TRUE,40000 +81320,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +81321,both interview and exam,female,80,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,2,widowed,NA,TRUE,70000 +81322,both interview and exam,female,55,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,divorced,NA,TRUE,40000 +81323,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81324,both interview and exam,male,1,22,black,1,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +81325,both interview and exam,female,9,NA,asian,2,112,NA,NA,FALSE,TRUE,7.5,3,NA,NA,NA,TRUE,100000 +81326,both interview and exam,female,16,NA,mexican american,2,201,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,FALSE,50000 +81327,both interview and exam,male,11,NA,white,1,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81328,both interview and exam,male,18,NA,white,1,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +81329,both interview and exam,female,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +81330,both interview and exam,female,6,NA,mexican american,2,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +81331,both interview and exam,female,27,NA,white,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,never_married,no,TRUE,50000 +81332,both interview and exam,female,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +81333,both interview and exam,male,2,NA,black,2,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 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interview and exam,male,59,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,70000 +81345,both interview and exam,female,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,40000 +81346,both interview and exam,male,2,NA,white,1,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81347,both interview and exam,male,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81348,both interview and exam,male,21,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,never_married,NA,FALSE,50000 +81349,both interview and exam,male,36,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,living_with_partner,NA,FALSE,17500 +81350,both interview and exam,female,58,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,FALSE,30000 +81351,both interview and exam,female,14,NA,other,2,175,NA,NA,FALSE,FALSE,0.5,7,NA,NA,NA,TRUE,2500 +81352,both interview and exam,male,58,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,22500 +81353,both interview and exam,male,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81354,both interview and exam,female,3,NA,white,1,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81355,both interview and exam,female,6,NA,black,1,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +81356,both interview and exam,male,12,NA,black,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +81357,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +81358,both interview and exam,female,77,NA,black,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,widowed,NA,TRUE,7500 +81359,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +81360,both interview and exam,male,0,5,other hispanic,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81361,both interview and exam,female,8,NA,mexican american,2,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +81362,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,NA 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exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,70000 +81373,both interview and exam,male,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +81374,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,no,TRUE,60000 +81375,both interview and exam,female,41,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,no,TRUE,87500 +81376,both interview and exam,female,5,NA,asian,1,71,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81377,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81378,both interview and exam,female,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +81379,both interview and exam,male,48,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,100000 +81380,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,12500 +81381,both interview and exam,female,73,NA,white,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,1,widowed,NA,TRUE,12500 +81382,both interview and exam,male,71,NA,mexican american,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81383,both interview and exam,male,16,NA,white,2,196,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +81384,both interview and exam,male,40,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,100000 +81385,both interview and exam,male,69,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81386,both interview and exam,female,18,NA,mexican american,1,220,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 +81387,both interview and exam,female,52,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,never_married,NA,TRUE,12500 +81388,both interview and exam,male,26,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,TRUE,22500 +81389,both interview and exam,male,13,NA,asian,2,160,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,70000 +81390,both interview and exam,male,3,NA,other,1,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81391,both interview and exam,male,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +81392,both interview and exam,female,11,NA,mexican american,2,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,70000 +81393,both interview and exam,female,16,NA,other hispanic,2,201,NA,NA,FALSE,FALSE,3,9,NA,NA,NA,FALSE,NA +81394,both interview and exam,female,10,NA,mexican american,1,130,NA,NA,FALSE,FALSE,7.5,4,NA,NA,NA,FALSE,40000 +81395,both interview and exam,male,23,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +81396,both interview and exam,male,21,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,never_married,NA,TRUE,50000 +81397,interview only,male,15,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,22500 +81398,both interview and exam,female,2,NA,white,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81399,interview 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exam,female,65,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,70000 +81410,both interview and exam,male,6,NA,white,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,60000 +81411,both interview and exam,male,15,NA,asian,2,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +81412,both interview and exam,male,67,NA,black,2,NA,FALSE,NA,FALSE,TRUE,45,NA,5,divorced,NA,TRUE,22500 +81413,both interview and exam,female,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,70000 +81414,both interview and exam,male,13,NA,black,2,163,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +81415,both interview and exam,male,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81416,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +81417,both interview and exam,male,2,NA,black,1,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +81418,both interview and exam,female,61,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,22500 +81419,both interview and exam,female,14,NA,mexican american,1,169,NA,NA,FALSE,FALSE,12.5,7,NA,NA,NA,TRUE,22500 +81420,both interview and exam,male,1,15,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81421,both interview and exam,female,7,NA,black,1,85,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +81422,both interview and exam,male,4,NA,mexican american,2,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81423,both interview and exam,male,7,NA,asian,1,92,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +81424,both interview and exam,female,27,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +81425,both interview and exam,male,2,NA,black,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81426,both interview and exam,female,12,NA,black,1,155,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +81427,both interview and exam,male,52,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,living_with_partner,NA,FALSE,17500 +81428,both interview and exam,female,26,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +81429,both interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81430,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81431,interview only,male,5,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81432,both interview and exam,male,8,NA,black,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +81433,both interview and exam,male,17,NA,mexican american,1,206,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +81434,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +81435,both interview and exam,male,18,NA,white,1,216,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +81436,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,7500 +81437,both interview and exam,male,16,NA,black,1,195,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +81438,both interview and exam,female,56,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,60000 +81439,both interview and exam,male,0,3,white,1,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81440,both interview and exam,female,2,NA,other hispanic,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81441,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,22500 +81442,both interview and exam,female,32,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,divorced,no,FALSE,NA +81443,both interview and exam,male,1,12,white,1,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81444,both interview and exam,female,51,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,FALSE,70000 +81445,both interview and exam,male,10,NA,mexican american,1,129,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,NA +81446,both interview and exam,female,11,NA,mexican american,1,136,NA,NA,FALSE,FALSE,12.5,5,NA,NA,NA,FALSE,30000 +81447,both interview and exam,female,69,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,7500 +81448,both interview and exam,male,18,NA,other hispanic,2,226,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,7500 +81449,both interview and exam,male,6,NA,black,2,79,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81450,both interview and exam,female,56,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,divorced,NA,TRUE,50000 +81451,both interview and exam,male,19,NA,white,1,236,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,40000 +81452,both interview and exam,male,60,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +81453,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +81454,both interview and exam,male,15,NA,other,1,190,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,22500 +81455,both interview and exam,male,1,15,black,2,16,NA,NA,FALSE,TRUE,0.5,NA,NA,NA,NA,TRUE,100000 +81456,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +81457,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,100000 +81458,both interview and exam,female,0,9,mexican american,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81459,both interview and exam,female,1,23,mexican american,2,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +81460,both interview and exam,female,46,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,87500 +81461,both interview and exam,male,24,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,NA,TRUE,22500 +81462,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,FALSE,NA +81463,both interview and exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,22500 +81464,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81465,both interview and exam,female,68,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,55,NA,4,married,NA,TRUE,12500 +81466,both interview and exam,male,0,4,mexican american,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +81467,both interview and exam,female,7,NA,asian,1,85,NA,NA,FALSE,TRUE,3,0,NA,NA,NA,TRUE,100000 +81468,both interview and exam,male,74,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81469,both interview and exam,male,16,NA,mexican american,1,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,NA +81470,both interview and exam,female,43,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,87500 +81471,both interview and exam,female,14,NA,asian,1,170,NA,NA,FALSE,FALSE,0.5,7,NA,NA,NA,TRUE,87500 +81472,both interview and exam,male,29,NA,other,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,never_married,NA,TRUE,NA +81473,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,unable to ascertain,TRUE,17500 +81474,both interview and exam,female,78,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,40000 +81475,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,22500 +81476,both interview and exam,male,12,NA,white,2,147,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +81477,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +81478,both interview and exam,female,4,NA,black,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81479,both interview and exam,male,11,NA,black,2,141,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81480,both interview and exam,male,12,NA,black,1,157,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,60000 +81481,both interview and exam,female,28,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,married,no,TRUE,60000 +81482,both interview and exam,male,49,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81483,both interview and exam,male,5,NA,mexican american,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 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exam,male,5,NA,black,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81494,both interview and exam,male,38,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +81495,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +81496,both interview and exam,male,14,NA,white,2,174,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,87500 +81497,both interview and exam,female,72,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,50000 +81498,both interview and exam,female,11,NA,mexican american,2,133,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81499,both interview and exam,female,18,NA,mexican american,2,220,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +81500,both interview and exam,female,10,NA,mexican american,1,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +81501,both interview and exam,female,6,NA,black,1,75,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,30000 +81502,both interview and exam,male,17,NA,black,2,205,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 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exam,male,69,NA,asian,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +81513,both interview and exam,male,7,NA,black,2,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +81514,both interview and exam,male,23,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +81515,both interview and exam,male,2,NA,mexican american,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81516,both interview and exam,female,60,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +81517,both interview and exam,female,15,NA,asian,1,191,NA,NA,FALSE,FALSE,7.5,9,NA,NA,NA,TRUE,17500 +81518,both interview and exam,female,13,NA,black,1,159,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +81519,both interview and exam,male,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81520,interview only,female,15,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,22500 +81521,both interview and exam,female,55,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,100000 +81522,both interview and exam,female,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,NA +81523,both interview and exam,female,57,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +81524,both interview and exam,male,73,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,FALSE,50000 +81525,both interview and exam,male,10,NA,mexican american,1,120,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,70000 +81526,both interview and exam,female,16,NA,other,2,203,NA,NA,FALSE,FALSE,0.5,8,NA,NA,NA,TRUE,2500 +81527,both interview and exam,male,35,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,50000 +81528,both interview and exam,female,41,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,17500 +81529,both interview and exam,female,1,13,mexican american,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,NA +81530,both interview and exam,female,73,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81531,both interview and exam,female,5,NA,other hispanic,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +81532,both interview and exam,male,5,NA,asian,2,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81533,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +81534,both interview and exam,female,49,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,17500 +81535,both interview and exam,female,46,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +81536,both interview and exam,female,8,NA,other hispanic,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +81537,both interview and exam,female,55,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,divorced,NA,FALSE,NA +81538,both interview and exam,male,12,NA,mexican american,2,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,7500 +81539,both interview and exam,male,7,NA,mexican american,2,94,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +81540,both interview and exam,female,7,NA,black,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81541,both interview and exam,female,15,NA,black,1,188,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +81542,both interview and exam,male,3,NA,white,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81543,both interview and exam,male,14,NA,white,2,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81544,both interview and exam,male,37,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,87500 +81545,both interview and exam,male,16,NA,mexican american,2,200,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +81546,both interview and exam,male,6,NA,black,1,82,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,60000 +81547,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,12500 +81548,both interview and exam,male,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,40000 +81549,both interview and exam,female,6,NA,white,2,81,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +81550,both interview and exam,male,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81551,both interview and exam,female,15,NA,mexican american,2,191,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +81552,both interview and exam,female,62,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +81553,both interview and exam,female,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81554,both interview and exam,female,8,NA,mexican american,2,98,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,40000 +81555,both interview and exam,female,6,NA,black,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +81556,both interview and exam,female,25,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +81557,both interview and exam,male,13,NA,other,1,160,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +81558,both interview and exam,female,7,NA,white,1,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81559,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81560,both interview and exam,male,1,15,white,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81561,both interview and exam,male,10,NA,white,1,127,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +81562,both interview and exam,male,2,NA,other hispanic,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81563,both interview and exam,male,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +81564,both interview and exam,male,50,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,married,NA,TRUE,17500 +81565,both interview and exam,male,9,NA,mexican american,1,119,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,17500 +81566,both interview and exam,male,52,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +81567,both interview and exam,male,3,NA,asian,1,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81568,both interview and exam,female,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,50000 +81569,both interview and exam,male,1,12,asian,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81570,both interview and exam,female,58,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +81571,both interview and exam,female,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,yes,TRUE,30000 +81572,both interview and exam,female,15,NA,black,1,183,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,30000 +81573,both interview and exam,female,64,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,1,never_married,NA,TRUE,2500 +81574,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81575,both interview and exam,male,11,NA,mexican american,2,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,60000 +81576,both interview and exam,female,40,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,no,FALSE,NA +81577,both interview and exam,male,9,NA,mexican american,2,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,87500 +81578,both interview and exam,male,60,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81579,both interview and exam,female,73,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,1,never_married,NA,FALSE,22500 +81580,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +81581,both interview and exam,male,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,widowed,NA,TRUE,12500 +81582,both interview and exam,male,72,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,22500 +81583,both interview and exam,female,18,NA,mexican american,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +81584,both interview and exam,female,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81585,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,22500 +81586,both interview and exam,male,6,NA,other hispanic,1,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +81587,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +81588,both interview and exam,female,11,NA,black,2,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +81589,both interview and exam,female,9,NA,asian,2,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +81590,both interview and exam,male,28,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,living_with_partner,NA,FALSE,30000 +81591,both interview and exam,female,14,NA,other,2,170,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +81592,interview only,female,4,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81593,both interview and exam,male,68,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,3,separated,NA,FALSE,17500 +81594,both interview and exam,male,60,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +81595,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +81596,both interview and exam,male,35,NA,white,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,NA,TRUE,22500 +81597,interview only,male,63,NA,black,NA,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,50000 +81598,both interview and exam,male,50,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,30000 +81599,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81600,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81601,both interview and exam,male,65,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,17500 +81602,both interview and exam,female,37,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,NA +81603,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +81604,both interview and exam,female,29,NA,black,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,never_married,no,TRUE,30000 +81605,both interview and exam,male,43,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,100000 +81606,both interview and exam,female,42,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,married,no,TRUE,100000 +81607,both interview and exam,female,29,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +81608,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81609,both interview and exam,male,54,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,FALSE,NA +81610,both interview and exam,male,60,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,married,NA,FALSE,NA +81611,both interview and exam,male,31,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,separated,NA,FALSE,NA +81612,both interview and exam,female,3,NA,mexican american,1,38,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +81613,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,17500 +81614,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +81615,both interview and exam,female,10,NA,mexican american,2,127,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,17500 +81616,both interview and exam,female,10,NA,mexican american,1,122,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,17500 +81617,both interview and exam,male,52,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,25,NA,3,never_married,NA,FALSE,NA +81618,both interview and exam,female,19,NA,white,1,230,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +81619,both interview and exam,female,18,NA,mexican american,2,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,40000 +81620,both interview and exam,male,26,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,NA +81621,both interview and exam,female,15,NA,white,2,186,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +81622,both interview and exam,female,65,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +81623,both interview and exam,female,63,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,50000 +81624,both interview and exam,female,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81625,both interview and exam,female,41,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,married,no,TRUE,70000 +81626,both interview and exam,female,40,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,separated,no,TRUE,30000 +81627,both interview and exam,female,24,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,NA +81628,both interview and exam,female,66,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +81629,both interview and exam,female,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81630,both interview and exam,female,14,NA,white,1,173,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,60000 +81631,both interview and exam,male,1,15,other,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +81632,both interview and exam,female,3,NA,black,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81633,both interview and exam,male,51,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +81634,both interview and exam,male,14,NA,white,2,175,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +81635,both interview and exam,female,5,NA,other hispanic,1,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81636,both interview and exam,male,79,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,100000 +81637,both interview and exam,male,5,NA,mexican american,1,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +81638,both interview and exam,female,15,NA,mexican american,1,188,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,FALSE,22500 +81639,both interview and exam,female,13,NA,black,1,158,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +81640,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +81641,both interview and exam,female,9,NA,black,2,118,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +81642,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +81643,both interview and exam,female,50,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,22500 +81644,both interview and exam,male,6,NA,white,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81645,both interview and exam,female,52,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,FALSE,100000 +81646,both interview and exam,male,0,9,black,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81647,both interview and exam,female,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +81648,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +81649,both interview and exam,female,19,NA,mexican american,1,237,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,70000 +81650,both interview and exam,male,9,NA,mexican american,1,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,30000 +81651,both interview and exam,male,2,NA,white,2,36,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81652,both interview and exam,male,0,0,black,2,0,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81653,both interview and exam,male,14,NA,mexican american,1,173,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,NA +81654,both interview and exam,male,67,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81655,interview only,male,80,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +81656,both interview and exam,male,14,NA,other,2,175,NA,NA,FALSE,FALSE,0.5,7,NA,NA,NA,TRUE,2500 +81657,both interview and exam,male,3,NA,white,2,39,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +81658,both interview and exam,female,2,NA,other hispanic,2,25,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,87500 +81659,both interview and exam,female,38,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,separated,no,FALSE,7500 +81660,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,22500 +81661,both interview and exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,40000 +81662,both interview and exam,female,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +81663,both interview and exam,female,9,NA,mexican american,2,116,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,FALSE,12500 +81664,both interview and exam,female,51,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,60000 +81665,both interview and exam,male,36,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +81666,both interview and exam,female,37,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,NA +81667,both interview and exam,female,19,NA,black,2,229,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,50000 +81668,both interview and exam,male,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +81669,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,30000 +81670,both interview and exam,female,15,NA,asian,2,181,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,NA +81671,both interview and exam,male,65,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,40000 +81672,both interview and exam,female,33,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,separated,no,TRUE,12500 +81673,both interview and exam,female,2,NA,white,1,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81674,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,22500 +81675,both interview and exam,female,74,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +81676,both interview and exam,female,14,NA,other hispanic,1,173,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +81677,both interview and exam,male,60,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,FALSE,87500 +81678,both interview and exam,male,17,NA,black,1,213,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,17500 +81679,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81680,both interview and exam,female,18,NA,mexican american,1,222,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,70000 +81681,both interview and exam,female,42,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,3,married,no,FALSE,87500 +81682,both interview and exam,female,6,NA,other hispanic,1,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,NA +81683,both interview and exam,female,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +81684,both interview and exam,female,2,NA,white,1,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81685,both interview and exam,male,12,NA,white,1,153,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +81686,both interview and exam,female,55,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,70000 +81687,both interview and exam,male,13,NA,mexican american,1,168,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +81688,both interview and exam,female,3,NA,other,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81689,both interview and exam,female,18,NA,white,1,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,22500 +81690,both interview and exam,male,1,14,white,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81691,both interview and exam,male,9,NA,white,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +81692,both interview and exam,female,17,NA,black,2,214,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,60000 +81693,both interview and exam,female,7,NA,black,2,93,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,22500 +81694,both interview and exam,female,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +81695,both interview and exam,female,36,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,unable to ascertain,TRUE,40000 +81696,both interview and exam,female,3,NA,asian,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81697,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +81698,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81699,both interview and exam,female,19,NA,black,2,238,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,60000 +81700,both interview and exam,female,30,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +81701,both interview and exam,male,52,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81702,both interview and exam,male,6,NA,other,1,76,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,87500 +81703,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81704,both interview and exam,male,45,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81705,both interview and exam,male,9,NA,white,2,112,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +81706,both interview and exam,male,45,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81707,both interview and exam,male,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +81708,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,2500 +81709,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +81710,both interview and exam,female,3,NA,white,1,38,NA,NA,FALSE,FALSE,0.5,NA,NA,NA,NA,TRUE,100000 +81711,both interview and exam,female,32,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +81712,both interview and exam,male,66,NA,other hispanic,2,NA,TRUE,TRUE,FALSE,TRUE,55,NA,4,married,NA,TRUE,60000 +81713,both interview and exam,female,16,NA,black,1,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,22500 +81714,both interview and exam,female,58,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81715,both interview and exam,female,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,NA +81716,both interview and exam,female,11,NA,other,2,142,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +81717,both interview and exam,male,35,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +81718,both interview and exam,male,1,18,white,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81719,both interview and exam,male,43,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,40000 +81720,both interview and exam,male,11,NA,mexican american,1,144,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,FALSE,70000 +81721,both interview and exam,female,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +81722,both interview and exam,female,47,NA,black,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,100000 +81723,both interview and exam,male,1,16,other hispanic,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81724,both interview and exam,male,10,NA,black,1,127,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +81725,both interview and exam,female,40,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,no,TRUE,100000 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american,2,150,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,50000 +81736,both interview and exam,female,76,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +81737,both interview and exam,male,70,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,60000 +81738,both interview and exam,female,15,NA,mexican american,2,188,NA,NA,FALSE,TRUE,12.5,9,NA,NA,NA,FALSE,40000 +81739,interview only,female,13,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81740,both interview and exam,male,21,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,4,never_married,NA,TRUE,22500 +81741,both interview and exam,male,43,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,17500 +81742,both interview and exam,male,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81743,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,FALSE,TRUE,55,NA,2,widowed,NA,TRUE,22500 +81744,both interview and exam,female,5,NA,white,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81745,both interview and exam,male,16,NA,black,1,204,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +81746,both interview and exam,female,8,NA,black,1,98,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81747,both interview and exam,male,1,15,black,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81748,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +81749,both interview and exam,male,0,1,white,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81750,both interview and exam,female,22,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,22500 +81751,both interview and exam,female,17,NA,mexican american,1,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,17500 +81752,both interview and exam,male,41,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +81753,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +81754,both interview and exam,female,16,NA,black,1,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81755,both interview and exam,male,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81756,both interview and exam,male,2,NA,white,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81757,both interview and exam,male,10,NA,black,2,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,17500 +81758,both interview and exam,male,14,NA,black,1,172,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +81759,both interview and exam,male,9,NA,black,2,110,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,17500 +81760,both interview and exam,female,36,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,married,no,FALSE,22500 +81761,both interview and exam,female,1,14,black,1,14,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81762,both interview and exam,female,22,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,no,TRUE,NA +81763,both interview and exam,female,61,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,30000 +81764,both interview and exam,male,74,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,NA +81765,both interview and exam,male,17,NA,other hispanic,1,211,FALSE,NA,FALSE,FALSE,0.5,9,NA,NA,NA,FALSE,50000 +81766,both interview and exam,male,32,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81767,interview only,female,57,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,60000 +81768,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +81769,both interview and exam,male,4,NA,asian,1,51,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,87500 +81770,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,2,married,NA,FALSE,NA +81771,both interview and exam,male,18,NA,white,2,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +81772,both interview and exam,male,49,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,FALSE,30000 +81773,both interview and exam,male,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +81774,both interview and exam,male,0,3,other,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81775,both interview and exam,male,17,NA,white,2,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +81776,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,no,TRUE,7500 +81777,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,70000 +81778,both interview and exam,male,18,NA,black,1,221,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81779,both interview and exam,female,63,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,7500 +81780,both interview and exam,male,22,NA,mexican american,2,NA,TRUE,TRUE,FALSE,TRUE,17.5,NA,3,never_married,NA,TRUE,40000 +81781,both interview and exam,male,50,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81782,both interview and exam,male,17,NA,asian,1,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,22500 +81783,both interview and exam,male,44,NA,black,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,100000 +81784,both interview and exam,female,53,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,30000 +81785,both interview and exam,female,70,NA,other hispanic,2,NA,FALSE,NA,FALSE,NA,55,NA,1,widowed,NA,TRUE,12500 +81786,both interview and exam,female,1,20,other hispanic,2,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81787,both interview and exam,male,34,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,40000 +81788,both interview and exam,male,0,6,white,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81789,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,12500 +81790,both interview and exam,female,8,NA,asian,1,100,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +81791,both interview and exam,male,1,21,white,2,22,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81792,interview only,male,49,NA,white,NA,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +81793,both interview and exam,male,4,NA,mexican american,2,52,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81794,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,100000 +81795,both interview and exam,male,50,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,TRUE,70000 +81796,both interview and exam,female,8,NA,black,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +81797,both interview and exam,female,74,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,40000 +81798,both interview and exam,male,71,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,22500 +81799,both interview and exam,male,10,NA,other,2,130,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +81800,both interview and exam,male,7,NA,black,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,2500 +81801,both interview and exam,male,53,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,100000 +81802,both interview and exam,male,30,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,never_married,NA,TRUE,100000 +81803,both interview and exam,male,18,NA,asian,1,225,FALSE,NA,FALSE,FALSE,3,13,NA,NA,NA,TRUE,2500 +81804,both interview and exam,female,14,NA,black,1,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81805,both interview and exam,female,21,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,yes,TRUE,22500 +81806,both interview and exam,female,32,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,no,TRUE,70000 +81807,both interview and exam,male,0,4,black,2,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81808,both interview and exam,female,18,NA,mexican american,2,218,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,87500 +81809,both interview and exam,male,40,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81810,both interview and exam,male,11,NA,other,2,140,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +81811,interview only,female,2,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81812,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,60000 +81813,both interview and exam,female,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,60000 +81814,both interview and exam,male,67,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81815,both interview and exam,male,75,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,12500 +81816,both interview and exam,female,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,12500 +81817,both interview and exam,male,6,NA,black,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,50000 +81818,both interview and exam,male,75,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +81819,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,17500 +81820,both interview and exam,male,65,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +81821,both interview and exam,male,0,9,other hispanic,1,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +81822,both interview and exam,female,51,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,60000 +81823,both interview and exam,male,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,12500 +81824,both interview and exam,male,78,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +81825,both interview and exam,female,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,22500 +81826,both interview and exam,female,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +81827,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81828,both interview and exam,female,45,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81829,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,FALSE,FALSE,25,NA,4,separated,no,TRUE,40000 +81830,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +81831,both interview and exam,female,72,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +81832,interview only,male,80,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +81833,both interview and exam,male,72,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81834,both interview and exam,male,33,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,50000 +81835,both interview and exam,female,47,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,NA +81836,both interview and exam,female,36,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,87500 +81837,both interview and exam,female,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,unable to ascertain,TRUE,17500 +81838,both interview and exam,male,5,NA,other,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81839,both interview and exam,male,13,NA,other hispanic,1,160,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,12500 +81840,both interview and exam,male,6,NA,asian,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81841,both interview and exam,female,11,NA,white,1,133,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +81842,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,40000 +81843,both interview and exam,male,19,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +81844,both interview and exam,male,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,70000 +81845,both interview and exam,male,75,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81846,both interview and exam,female,19,NA,mexican american,1,232,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,7500 +81847,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +81848,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,4,never_married,no,TRUE,100000 +81849,both interview and exam,female,44,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,no,FALSE,22500 +81850,both interview and exam,male,67,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81851,both interview and exam,male,73,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +81852,both interview and exam,male,1,15,mexican american,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81853,both interview and exam,male,17,NA,asian,1,214,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +81854,both interview and exam,male,38,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,7500 +81855,both interview and exam,female,27,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,17500 +81856,both interview and exam,male,7,NA,other hispanic,2,97,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +81857,both interview and exam,male,5,NA,mexican american,1,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,40000 +81858,both interview and exam,female,22,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,30000 +81859,both interview and exam,male,0,8,white,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +81860,both interview and exam,male,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +81861,both interview and exam,female,14,NA,white,2,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81862,interview only,female,20,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,7500 +81863,both interview and exam,male,56,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +81864,both interview and exam,male,17,NA,white,2,208,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +81865,both interview and exam,male,42,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +81866,both interview and exam,female,53,NA,black,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,separated,NA,TRUE,12500 +81867,both interview and exam,male,57,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,40000 +81868,both interview and exam,female,2,NA,other hispanic,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81869,both interview and exam,female,9,NA,other hispanic,2,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +81870,interview only,female,37,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,unable to ascertain,TRUE,100000 +81871,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +81872,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,30000 +81873,interview only,male,62,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,45,NA,5,never_married,NA,TRUE,100000 +81874,both interview and exam,male,3,NA,white,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81875,both interview and exam,female,70,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,1,married,NA,FALSE,17500 +81876,both interview and exam,male,9,NA,black,2,115,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +81877,both interview and exam,female,44,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +81878,both interview and exam,male,7,NA,asian,2,86,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +81879,both interview and exam,male,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +81880,both interview and exam,female,8,NA,mexican american,1,99,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,40000 +81881,both interview and exam,male,9,NA,mexican american,2,120,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,87500 +81882,both interview and exam,female,36,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,NA,NA,3,living_with_partner,no,FALSE,2500 +81883,both interview and exam,male,19,NA,white,2,237,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,40000 +81884,both interview and exam,male,6,NA,white,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,2500 +81885,both interview and exam,female,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,yes,TRUE,NA +81886,both interview and exam,male,47,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81887,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,12500 +81888,both interview and exam,male,0,10,asian,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +81889,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,yes,TRUE,7500 +81890,both interview and exam,female,67,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +81891,both interview and exam,female,28,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,no,TRUE,100000 +81892,both interview and exam,male,16,NA,white,2,194,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,22500 +81893,both interview and exam,male,30,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,TRUE,50000 +81894,both interview and exam,female,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,30000 +81895,both interview and exam,female,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +81896,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,22500 +81897,both interview and exam,female,12,NA,other hispanic,2,155,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,17500 +81898,both interview and exam,female,29,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,unable to ascertain,TRUE,30000 +81899,both interview and exam,male,55,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,50000 +81900,both interview and exam,female,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +81901,both interview and exam,male,0,6,white,2,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +81902,both interview and exam,male,6,NA,white,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +81903,both interview and exam,male,30,NA,asian,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +81904,both interview and exam,female,47,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,4,never_married,NA,TRUE,70000 +81905,both interview and exam,male,15,NA,black,2,189,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,60000 +81906,both interview and exam,male,8,NA,mexican american,2,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +81907,both interview and exam,male,13,NA,black,2,157,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +81908,both interview and exam,female,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +81909,both interview and exam,female,18,NA,black,2,224,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +81910,both interview and exam,male,30,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,60000 +81911,both interview and exam,male,13,NA,black,1,161,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +81912,both interview and exam,male,6,NA,mexican american,2,82,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,NA +81913,both interview and exam,female,18,NA,mexican american,1,226,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,2500 +81914,both interview and exam,male,15,NA,other,1,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +81915,both interview and exam,male,6,NA,asian,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81916,both interview and exam,male,6,NA,white,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +81917,both interview and exam,male,14,NA,black,1,169,NA,NA,FALSE,FALSE,7.5,7,NA,NA,NA,TRUE,22500 +81918,interview only,female,19,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,17.5,14,NA,NA,NA,TRUE,7500 +81919,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +81920,both interview and exam,male,50,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81921,both interview and exam,female,14,NA,black,2,180,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,7500 +81922,both interview and exam,female,9,NA,white,2,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +81923,both interview and exam,male,35,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +81924,both interview and exam,female,10,NA,mexican american,2,124,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,30000 +81925,both interview and exam,male,23,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,never_married,NA,TRUE,50000 +81926,both interview and exam,male,12,NA,white,1,148,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,40000 +81927,both interview and exam,female,5,NA,other hispanic,2,66,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +81928,both interview and exam,male,2,NA,mexican american,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +81929,both interview and exam,female,15,NA,mexican american,2,188,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +81930,both interview and exam,male,18,NA,other hispanic,2,228,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,30000 +81931,both interview and exam,male,6,NA,white,2,82,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81932,both interview and exam,female,24,NA,black,1,NA,FALSE,NA,FALSE,FALSE,3,NA,2,living_with_partner,yes,TRUE,50000 +81933,both interview and exam,female,80,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,7500 +81934,both interview and exam,female,61,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +81935,both interview and exam,female,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,7500 +81936,both interview and exam,female,1,23,other hispanic,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81937,interview only,male,15,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +81938,interview only,female,34,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,unable to ascertain,TRUE,87500 +81939,both interview and exam,female,5,NA,mexican american,2,69,NA,NA,FALSE,FALSE,3,NA,NA,NA,NA,FALSE,12500 +81940,both interview and exam,female,24,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,NA +81941,both interview and exam,male,17,NA,other hispanic,2,209,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +81942,both interview and exam,male,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,30000 +81943,both interview and exam,female,13,NA,other,2,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +81944,both interview and exam,female,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,60000 +81945,both interview and exam,female,53,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,NA,TRUE,87500 +81946,both interview and exam,female,30,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,no,FALSE,NA +81947,both interview and exam,female,0,1,black,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81948,both interview and exam,male,17,NA,mexican american,1,207,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,FALSE,NA +81949,both interview and exam,male,47,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,87500 +81950,both interview and exam,male,52,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,60000 +81951,both interview and exam,male,14,NA,mexican american,2,172,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,100000 +81952,both interview and exam,male,56,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,70000 +81953,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,40000 +81954,both interview and exam,male,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +81955,both interview and exam,male,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,60000 +81956,both interview and exam,female,35,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,married,no,TRUE,87500 +81957,both interview and exam,male,49,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +81958,both interview and exam,female,2,NA,white,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +81959,both interview and exam,male,77,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81960,both interview and exam,male,17,NA,asian,2,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +81961,both interview and exam,female,13,NA,white,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +81962,both interview and exam,female,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +81963,both interview and exam,male,3,NA,asian,1,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +81964,both interview and exam,male,0,8,black,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81965,both interview and exam,male,42,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +81966,both interview and exam,female,31,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,87500 +81967,both interview and exam,female,30,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,2500 +81968,both interview and exam,female,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,7500 +81969,both interview and exam,male,58,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,married,NA,TRUE,40000 +81970,both interview and exam,female,53,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,17500 +81971,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,50000 +81972,interview only,female,6,NA,mexican american,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,30000 +81973,both interview and exam,female,0,9,black,2,10,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +81974,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +81975,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +81976,both interview and exam,female,6,NA,white,2,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +81977,both interview and exam,female,16,NA,mexican american,1,196,NA,NA,FALSE,FALSE,12.5,9,NA,NA,NA,TRUE,22500 +81978,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 +81979,both interview and exam,male,53,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +81980,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +81981,both interview and exam,female,3,NA,other hispanic,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +81982,both interview and exam,female,55,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +81983,both interview and exam,female,72,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +81984,both interview and exam,female,6,NA,asian,1,83,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +81985,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,100000 +81986,both interview and exam,male,6,NA,other hispanic,1,74,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +81987,both interview and exam,female,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,TRUE,40000 +81988,both interview and exam,male,65,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,12500 +81989,both interview and exam,female,46,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,12500 +81990,both interview and exam,female,3,NA,white,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +81991,both interview and exam,female,12,NA,black,2,147,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +81992,both interview and exam,female,51,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,divorced,NA,TRUE,87500 +81993,both interview and exam,male,43,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,0.5,NA,5,married,NA,TRUE,100000 +81994,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,60000 +81995,both interview and exam,male,74,NA,asian,2,NA,TRUE,TRUE,FALSE,TRUE,45,NA,4,married,NA,TRUE,NA +81996,both interview and exam,male,48,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,FALSE,NA +81997,both interview and exam,male,80,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +81998,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,NA +81999,both interview and exam,male,3,NA,black,1,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82000,both interview and exam,male,6,NA,white,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +82001,both interview and exam,male,50,NA,white,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,married,NA,TRUE,60000 +82002,both interview and exam,female,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +82003,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +82004,both interview and exam,male,1,15,black,1,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82005,both interview and exam,male,68,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,30000 +82006,both interview and exam,male,46,NA,black,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,TRUE,50000 +82007,both interview and exam,female,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +82008,both interview and exam,female,9,NA,mexican american,1,119,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,7500 +82009,interview only,female,8,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +82010,interview only,female,36,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,unable to ascertain,TRUE,100000 +82011,both interview and exam,male,31,NA,white,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,NA,TRUE,87500 +82012,both interview and exam,female,71,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82013,both interview and exam,female,2,NA,black,2,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82014,both interview and exam,male,12,NA,white,2,145,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +82015,interview only,female,70,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,50000 +82016,both interview and exam,female,3,NA,white,1,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82017,both interview and exam,female,18,NA,white,2,223,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +82018,both interview and exam,male,11,NA,black,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,22500 +82019,both interview and exam,male,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +82020,both interview and exam,male,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +82021,both interview and exam,female,53,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +82022,both interview and exam,female,10,NA,black,1,122,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +82023,both interview and exam,female,41,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,40000 +82024,both interview and exam,female,7,NA,black,1,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,NA +82025,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +82026,both interview and exam,male,68,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82027,both interview and exam,male,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,30000 +82028,both interview and exam,female,46,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +82029,both interview and exam,female,6,NA,other hispanic,2,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82030,both interview and exam,female,3,NA,asian,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82031,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,22500 +82032,both interview and exam,male,8,NA,black,2,96,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +82033,both interview and exam,male,7,NA,black,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,7500 +82034,both interview and exam,male,13,NA,other hispanic,2,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,FALSE,30000 +82035,interview only,female,1,23,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82036,both interview and exam,male,17,NA,other hispanic,2,206,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +82037,both interview and exam,female,43,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,no,TRUE,30000 +82038,both interview and exam,male,0,4,white,1,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82039,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,FALSE,FALSE,3,NA,5,never_married,no,TRUE,22500 +82040,both interview and exam,male,7,NA,black,2,90,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +82041,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 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hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,no,TRUE,100000 +82052,both interview and exam,female,60,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +82053,both interview and exam,female,43,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +82054,both interview and exam,male,8,NA,mexican american,2,107,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,7500 +82055,both interview and exam,male,77,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +82056,both interview and exam,male,76,NA,other hispanic,1,NA,TRUE,FALSE,FALSE,TRUE,55,NA,4,married,NA,TRUE,30000 +82057,both interview and exam,female,36,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,30000 +82058,both interview and exam,male,34,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,100000 +82059,both interview and exam,female,29,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +82060,both interview and exam,female,25,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,30000 +82061,both interview and exam,female,80,NA,black,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,widowed,NA,TRUE,NA +82062,both interview and exam,female,54,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,12500 +82063,both interview and exam,male,10,NA,white,1,123,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,NA +82064,both interview and exam,female,6,NA,other hispanic,1,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +82065,both interview and exam,male,3,NA,white,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +82066,both interview and exam,female,15,NA,white,2,183,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +82067,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,7500 +82068,both interview and exam,male,44,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,living_with_partner,NA,FALSE,30000 +82069,both interview and exam,male,10,NA,black,2,132,NA,NA,FALSE,FALSE,NA,5,NA,NA,NA,TRUE,50000 +82070,both interview and exam,male,18,NA,white,2,218,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +82071,both interview and exam,female,16,NA,white,1,201,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,40000 +82072,both interview and exam,male,14,NA,white,2,170,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,30000 +82073,both interview and exam,male,19,NA,white,1,237,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +82074,both interview and exam,female,1,14,white,1,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +82075,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82076,both interview and exam,female,5,NA,other,2,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82077,both interview and exam,male,40,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,NA,TRUE,87500 +82078,both interview and exam,male,8,NA,mexican american,1,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +82079,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,70000 +82080,both interview and exam,male,2,NA,white,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82081,both interview and exam,male,0,8,mexican american,1,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +82082,both interview and exam,male,2,NA,asian,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82083,both interview and exam,female,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,100000 +82084,both interview and exam,male,1,13,white,1,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82085,both interview and exam,male,54,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +82086,both interview and exam,male,21,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +82087,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82088,both interview and exam,female,19,NA,black,1,236,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,12500 +82089,both interview and exam,male,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,7500 +82090,both interview and exam,female,48,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,40000 +82091,both interview and exam,female,69,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,30000 +82092,interview only,female,62,NA,other hispanic,NA,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,divorced,NA,FALSE,12500 +82093,both interview and exam,male,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,12500 +82094,interview only,male,27,NA,other hispanic,NA,NA,FALSE,NA,FALSE,FALSE,3,NA,1,never_married,NA,FALSE,40000 +82095,both interview and exam,female,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,70000 +82096,both interview and exam,male,16,NA,black,2,199,NA,NA,FALSE,FALSE,3,11,NA,NA,NA,TRUE,40000 +82097,both interview and exam,male,6,NA,asian,1,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,NA +82098,both interview and exam,male,64,NA,mexican 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exam,male,43,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82108,both interview and exam,male,61,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,NA,FALSE,50000 +82109,both interview and exam,male,19,NA,white,2,235,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,22500 +82110,both interview and exam,male,27,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,7500 +82111,both interview and exam,male,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82112,both interview and exam,female,37,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +82113,both interview and exam,male,69,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +82114,both interview and exam,female,14,NA,black,1,174,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +82115,both interview and exam,male,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,17500 +82116,both interview and exam,female,18,NA,mexican 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interview and exam,male,40,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,7500 +82165,both interview and exam,male,44,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +82166,both interview and exam,male,6,NA,black,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,2500 +82167,both interview and exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82168,interview only,male,17,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,NA +82169,both interview and exam,female,58,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,never_married,NA,FALSE,NA +82170,both interview and exam,female,62,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,25,NA,5,married,NA,TRUE,100000 +82171,both interview and exam,male,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 +82172,both interview and exam,male,29,NA,other,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,40000 +82173,both interview and 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exam,female,50,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,50000 +82259,both interview and exam,male,20,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,7500 +82260,both interview and exam,male,9,NA,white,2,120,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +82261,both interview and exam,male,42,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +82262,both interview and exam,female,1,13,mexican american,2,15,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +82263,both interview and exam,female,9,NA,black,1,117,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,40000 +82264,both interview and exam,male,5,NA,other hispanic,1,72,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 +82265,both interview and exam,male,8,NA,white,2,98,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,100000 +82266,interview only,female,0,10,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82267,both interview and exam,female,6,NA,white,2,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +82268,both interview and exam,female,4,NA,white,1,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82269,both interview and exam,female,23,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,never_married,no,FALSE,NA +82270,both interview and exam,male,49,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,3,NA,1,married,NA,TRUE,40000 +82271,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,30000 +82272,both interview and exam,female,0,2,mexican american,1,3,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82273,both interview and exam,female,1,23,white,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82274,both interview and exam,male,5,NA,other hispanic,2,67,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82275,both interview and exam,female,42,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,5,married,unable to ascertain,TRUE,30000 +82276,interview only,female,51,NA,other,NA,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,17500 +82277,both interview and exam,female,71,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,40000 +82278,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +82279,both interview and exam,female,13,NA,black,2,164,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,NA +82280,both interview and exam,male,6,NA,white,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82281,both interview and exam,female,41,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,30000 +82282,both interview and exam,male,34,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,30000 +82283,both interview and exam,male,48,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,FALSE,NA +82284,both interview and exam,female,8,NA,white,2,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +82285,both interview and exam,female,57,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +82286,both interview and exam,female,14,NA,white,1,178,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +82287,both interview and exam,female,19,NA,other hispanic,1,233,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,12500 +82288,both interview and exam,male,55,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +82289,both interview and exam,female,0,11,mexican american,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82290,both interview and exam,male,43,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,2,married,NA,TRUE,40000 +82291,both interview and exam,female,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82292,interview only,female,3,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82293,both interview and exam,female,4,NA,asian,2,58,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82294,both interview and exam,male,8,NA,asian,1,103,NA,NA,FALSE,FALSE,3,3,NA,NA,NA,TRUE,7500 +82295,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,22500 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interview and exam,male,43,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,NA,TRUE,NA +82307,both interview and exam,female,73,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +82308,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +82309,both interview and exam,female,23,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,7500 +82310,both interview and exam,female,19,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +82311,both interview and exam,male,17,NA,black,1,209,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +82312,both interview and exam,female,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,22500 +82313,both interview and exam,female,15,NA,black,1,192,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,40000 +82314,both interview and exam,male,13,NA,other hispanic,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,17500 +82315,both interview and exam,male,23,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82316,both interview and exam,male,73,NA,mexican american,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +82317,both interview and exam,male,7,NA,mexican american,2,96,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,30000 +82318,both interview and exam,male,27,NA,black,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,never_married,NA,TRUE,2500 +82319,both interview and exam,female,35,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,22500 +82320,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +82321,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82322,interview only,male,41,NA,other,NA,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +82323,both interview and exam,male,2,NA,black,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82324,both interview and exam,male,6,NA,other hispanic,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,17500 +82325,both interview and exam,male,39,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +82326,both interview and exam,male,10,NA,white,2,133,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,50000 +82327,both interview and exam,female,2,NA,black,1,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +82328,both interview and exam,male,2,NA,black,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +82329,both interview and exam,male,45,NA,white,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,5,married,NA,TRUE,100000 +82330,both interview and exam,female,51,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82331,both interview and exam,male,16,NA,asian,2,200,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,NA +82332,both interview and exam,male,0,1,asian,2,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82333,both interview and exam,female,10,NA,other hispanic,2,127,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,NA +82334,both interview and exam,female,50,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,7500 +82335,both interview and exam,male,52,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +82336,both interview and exam,male,28,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,NA +82337,both interview and exam,female,35,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,no,TRUE,30000 +82338,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,30000 +82339,both interview and exam,male,0,10,mexican american,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +82340,both interview and exam,female,19,NA,asian,1,229,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,NA +82341,both interview and exam,male,16,NA,black,2,199,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,12500 +82342,both interview and exam,female,25,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,50000 +82343,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82344,both interview and exam,male,70,NA,black,1,NA,FALSE,NA,FALSE,FALSE,25,NA,1,divorced,NA,TRUE,30000 +82345,both interview and exam,male,32,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +82346,both interview and exam,female,51,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,separated,NA,TRUE,40000 +82347,both interview and exam,male,2,NA,mexican american,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82348,both interview and exam,female,29,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,yes,TRUE,87500 +82349,both interview and exam,female,11,NA,white,2,137,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,40000 +82350,both interview and exam,female,7,NA,other hispanic,1,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +82351,both interview and exam,male,65,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,30000 +82352,both interview and exam,male,0,11,mexican american,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,17500 +82353,both interview and exam,male,53,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +82354,both interview and exam,female,57,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82355,both interview and exam,female,70,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +82356,both interview and exam,female,63,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82357,both interview and exam,female,26,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,no,TRUE,30000 +82358,both interview and exam,male,13,NA,other,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,17500 +82359,both interview and exam,male,48,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +82360,both interview and exam,female,51,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +82361,both interview and exam,male,17,NA,mexican american,2,206,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 +82362,both interview and exam,male,7,NA,other hispanic,1,89,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,FALSE,17500 +82363,both interview and exam,male,38,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,22500 +82364,both interview and exam,female,0,9,white,2,9,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82365,both interview and exam,female,17,NA,black,1,213,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,50000 +82366,both interview and exam,female,6,NA,mexican american,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +82367,both interview and exam,male,35,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,married,NA,FALSE,2500 +82368,both interview and exam,female,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,17500 +82369,both interview and exam,female,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,no,TRUE,30000 +82370,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,2500 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exam,male,44,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82381,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,FALSE,TRUE,45,NA,2,widowed,NA,TRUE,NA +82382,both interview and exam,male,3,NA,black,2,37,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82383,both interview and exam,male,62,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,45,NA,1,married,NA,FALSE,30000 +82384,both interview and exam,female,65,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82385,both interview and exam,male,2,NA,white,1,30,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82386,both interview and exam,female,2,NA,black,1,35,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82387,both interview and exam,female,0,4,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82388,both interview and exam,male,34,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +82389,both interview and exam,female,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,unable to ascertain,TRUE,40000 +82390,both interview and exam,male,0,6,asian,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82391,both interview and exam,male,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +82392,both interview and exam,male,6,NA,black,2,76,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,12500 +82393,both interview and exam,male,20,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +82394,both interview and exam,male,18,NA,mexican american,2,216,FALSE,NA,FALSE,FALSE,12.5,14,NA,NA,NA,TRUE,NA +82395,both interview and exam,female,25,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,50000 +82396,both interview and exam,male,19,NA,white,1,237,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,50000 +82397,both interview and exam,male,33,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,NA +82398,both interview and exam,male,31,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +82399,both interview and exam,male,2,NA,other,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82400,both interview and exam,male,16,NA,black,2,197,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,17500 +82401,both interview and exam,female,30,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,100000 +82402,both interview and exam,male,65,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,TRUE,87500 +82403,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82404,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,22500 +82405,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,40000 +82406,both interview and exam,male,73,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,NA,never_married,NA,TRUE,12500 +82407,both interview and exam,male,44,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +82408,both interview and exam,male,18,NA,white,2,217,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,30000 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exam,male,16,NA,white,2,199,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,50000 +82419,both interview and exam,female,1,23,asian,1,24,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82420,both interview and exam,male,35,NA,black,2,NA,FALSE,NA,FALSE,TRUE,7.5,NA,4,married,NA,TRUE,40000 +82421,both interview and exam,female,13,NA,asian,1,164,NA,NA,FALSE,TRUE,12.5,7,NA,NA,NA,TRUE,100000 +82422,both interview and exam,female,10,NA,asian,1,127,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +82423,both interview and exam,male,56,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82424,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,7500 +82425,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,no,TRUE,50000 +82426,both interview and exam,male,24,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,22500 +82427,both interview and exam,male,48,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,70000 +82428,both interview and exam,female,26,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,40000 +82429,both interview and exam,male,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82430,both interview and exam,female,24,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,no,TRUE,40000 +82431,interview only,female,0,8,other hispanic,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +82432,both interview and exam,male,60,NA,black,2,NA,FALSE,NA,FALSE,FALSE,25,NA,2,married,NA,TRUE,NA +82433,both interview and exam,male,1,16,black,2,16,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82434,both interview and exam,female,70,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,NA +82435,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,12500 +82436,both interview and exam,male,61,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,2,married,NA,FALSE,87500 +82437,both interview and exam,female,1,12,other hispanic,2,12,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,12500 +82438,both interview and exam,male,7,NA,black,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +82439,both interview and exam,female,48,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82440,both interview and exam,female,63,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82441,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,87500 +82442,both interview and exam,female,0,7,mexican american,2,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82443,both interview and exam,male,11,NA,black,1,140,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,7500 +82444,both interview and exam,male,2,NA,black,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82445,both interview and exam,female,52,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82446,both interview and exam,male,66,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,30000 +82447,both interview and exam,female,15,NA,other,1,192,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +82448,both interview and exam,male,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +82449,both interview and exam,male,42,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,NA,FALSE,12500 +82450,both interview and exam,female,34,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,no,FALSE,7500 +82451,both interview and exam,female,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,17500 +82452,both interview and exam,female,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,87500 +82453,both interview and exam,female,0,4,other,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82454,both interview and exam,female,37,NA,other,1,NA,FALSE,NA,FALSE,FALSE,3,NA,4,married,no,TRUE,30000 +82455,both interview and exam,female,25,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,NA +82456,both interview and exam,female,0,6,black,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82457,both interview and exam,male,10,NA,mexican american,1,130,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,17500 +82458,both interview and exam,female,3,NA,other,1,48,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82459,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +82460,both interview and exam,female,58,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,NA +82461,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +82462,both interview and exam,male,36,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,NA,NA,1,living_with_partner,NA,FALSE,30000 +82463,both interview and exam,female,48,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,NA,TRUE,100000 +82464,both interview and exam,male,62,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,50000 +82465,both interview and exam,female,44,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,living_with_partner,no,TRUE,12500 +82466,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,70000 +82467,both interview and exam,male,22,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,30000 +82468,both interview and exam,male,11,NA,other,2,135,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,70000 +82469,both interview and exam,male,1,18,asian,1,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82470,both interview and exam,male,13,NA,black,1,158,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,30000 +82471,interview only,female,22,NA,other hispanic,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,unable to ascertain,TRUE,12500 +82472,both interview and exam,male,13,NA,white,1,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +82473,interview only,female,8,NA,other,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,7500 +82474,both interview and exam,female,2,NA,mexican american,2,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82475,both interview and exam,female,1,20,mexican american,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,70000 +82476,both interview and exam,male,10,NA,white,1,129,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +82477,both interview and exam,male,34,NA,white,2,NA,FALSE,NA,FALSE,TRUE,35,NA,2,never_married,NA,TRUE,12500 +82478,both interview and exam,male,12,NA,mexican american,2,149,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,12500 +82479,both interview and exam,male,27,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,living_with_partner,NA,TRUE,60000 +82480,both interview and exam,male,12,NA,white,1,149,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,87500 +82481,both interview and exam,female,0,3,white,1,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +82482,both interview and exam,female,80,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +82483,both interview and exam,male,32,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,3,NA,5,married,NA,TRUE,60000 +82484,both interview and exam,male,14,NA,black,1,174,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +82485,both interview and exam,female,33,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,4,married,no,TRUE,40000 +82486,both interview and exam,male,40,NA,other,1,NA,FALSE,NA,FALSE,FALSE,3,NA,3,married,NA,TRUE,30000 +82487,both interview and exam,male,21,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +82488,both interview and exam,male,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82489,both interview and exam,male,41,NA,asian,2,NA,TRUE,TRUE,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +82490,interview only,male,0,1,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82491,both interview and exam,male,14,NA,black,1,171,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +82492,both interview and exam,female,25,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,60000 +82493,both interview and exam,female,9,NA,white,2,120,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,30000 +82494,both interview and exam,female,19,NA,mexican american,1,236,FALSE,NA,FALSE,FALSE,NA,13,NA,NA,NA,TRUE,NA +82495,both interview and exam,female,51,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,30000 +82496,both interview and exam,male,8,NA,mexican american,1,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +82497,both interview and exam,female,11,NA,mexican american,1,144,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,87500 +82498,both interview and exam,male,18,NA,mexican american,1,227,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,FALSE,NA +82499,both interview and exam,male,12,NA,black,2,152,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,17500 +82500,both interview and exam,male,38,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +82501,both interview and exam,female,38,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,4,married,no,TRUE,100000 +82502,both interview and exam,female,16,NA,white,2,193,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,40000 +82503,both interview and exam,female,16,NA,black,1,193,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +82504,both interview and exam,male,73,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,3,separated,NA,FALSE,7500 +82505,both interview and exam,male,8,NA,white,1,103,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,22500 +82506,both interview and exam,female,1,17,mexican american,1,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82507,both interview and exam,male,72,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +82508,both interview and exam,male,5,NA,black,1,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82509,both interview and exam,male,63,NA,mexican american,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,30000 +82510,both interview and exam,male,0,11,white,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82511,both interview and exam,female,9,NA,other,1,109,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +82512,both interview and exam,female,21,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,no,TRUE,22500 +82513,both interview and exam,male,47,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,5,married,NA,TRUE,100000 +82514,both interview and exam,female,4,NA,asian,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82515,both interview and exam,male,11,NA,asian,2,144,NA,NA,TRUE,TRUE,NA,6,NA,NA,NA,TRUE,100000 +82516,both interview and exam,male,11,NA,mexican american,1,139,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,2500 +82517,both interview and exam,male,59,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,50000 +82518,both interview and exam,male,13,NA,mexican american,1,158,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,70000 +82519,both interview and exam,female,25,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,30000 +82520,both interview and exam,female,16,NA,mexican american,1,201,NA,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,70000 +82521,both interview and exam,female,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +82522,both interview and exam,male,15,NA,other hispanic,2,182,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,50000 +82523,both interview and exam,female,7,NA,other hispanic,2,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +82524,both interview and exam,female,21,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +82525,both interview and exam,male,6,NA,other,2,73,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +82526,both interview and exam,female,2,NA,mexican american,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82527,both interview and exam,female,39,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,100000 +82528,both interview and exam,male,15,NA,other hispanic,2,191,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,100000 +82529,both interview and exam,female,35,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,3,separated,no,TRUE,60000 +82530,both interview and exam,female,4,NA,asian,1,55,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82531,both interview and exam,female,36,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,no,FALSE,NA +82532,both interview and exam,male,16,NA,asian,1,194,NA,NA,FALSE,FALSE,0.5,9,NA,NA,NA,TRUE,17500 +82533,both interview and exam,female,26,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,NA +82534,both interview and exam,male,18,NA,mexican american,1,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,40000 +82535,both interview and exam,female,64,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +82536,both interview and exam,female,49,NA,other,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,87500 +82537,interview only,female,25,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,unable to ascertain,TRUE,12500 +82538,both interview and exam,female,26,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,30000 +82539,both interview and exam,female,1,18,asian,1,20,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82540,both interview and exam,male,20,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,17.5,NA,2,married,NA,TRUE,22500 +82541,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +82542,both interview and exam,male,66,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,1,married,NA,FALSE,22500 +82543,both interview and exam,female,12,NA,other,2,147,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,12500 +82544,both interview and exam,male,9,NA,mexican american,2,117,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,FALSE,22500 +82545,both interview and exam,male,8,NA,other hispanic,2,107,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +82546,both interview and exam,male,4,NA,white,2,57,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +82547,both interview and exam,female,65,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,2,married,NA,TRUE,NA +82548,both interview and exam,female,0,7,white,1,8,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82549,both interview and exam,male,8,NA,mexican american,2,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,30000 +82550,both interview and exam,female,34,NA,other hispanic,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,30000 +82551,both interview and exam,female,2,NA,black,2,31,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +82552,both interview and exam,female,2,NA,mexican american,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82553,both interview and exam,male,0,10,white,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82554,both interview and exam,female,54,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,100000 +82555,both interview and exam,female,1,18,white,1,19,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +82556,both interview and exam,female,4,NA,mexican american,2,49,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,30000 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exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,87500 +82567,both interview and exam,male,25,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,60000 +82568,both interview and exam,male,3,NA,asian,2,45,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82569,both interview and exam,male,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,7500 +82570,both interview and exam,male,80,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +82571,interview only,male,46,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82572,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,12500 +82573,both interview and exam,female,7,NA,other hispanic,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82574,both interview and exam,male,36,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,40000 +82575,both interview and exam,male,4,NA,other,2,50,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82576,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +82577,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,no,TRUE,100000 +82578,both interview and exam,female,11,NA,white,2,133,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,100000 +82579,both interview and exam,female,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,30000 +82580,both interview and exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,12500 +82581,both interview and exam,male,17,NA,other hispanic,2,216,FALSE,NA,FALSE,TRUE,3,13,NA,NA,NA,TRUE,40000 +82582,both interview and exam,male,71,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,1,married,NA,TRUE,12500 +82583,both interview and exam,female,6,NA,white,2,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82584,interview only,male,0,2,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 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exam,female,3,NA,white,2,40,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82595,both interview and exam,male,18,NA,white,2,225,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,7500 +82596,both interview and exam,male,73,NA,other hispanic,2,NA,FALSE,NA,FALSE,TRUE,35,NA,5,widowed,NA,FALSE,70000 +82597,both interview and exam,male,56,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,100000 +82598,both interview and exam,male,0,4,white,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82599,both interview and exam,male,2,NA,white,2,29,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +82600,both interview and exam,male,12,NA,black,2,148,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +82601,both interview and exam,male,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,separated,NA,TRUE,17500 +82602,both interview and exam,male,6,NA,other,2,77,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +82603,both interview and exam,female,44,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,4,divorced,no,TRUE,100000 +82604,both interview and exam,male,49,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,NA +82605,both interview and exam,female,46,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +82606,both interview and exam,male,10,NA,mexican american,1,130,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,FALSE,22500 +82607,both interview and exam,male,3,NA,other hispanic,2,42,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,87500 +82608,both interview and exam,male,78,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,living_with_partner,NA,TRUE,NA +82609,both interview and exam,female,46,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +82610,both interview and exam,male,72,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82611,both interview and exam,male,33,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,4,never_married,NA,TRUE,100000 +82612,both interview and exam,female,64,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,living_with_partner,NA,FALSE,12500 +82613,both interview and exam,male,19,NA,black,2,233,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,30000 +82614,both interview and exam,female,14,NA,asian,1,173,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,60000 +82615,both interview and exam,male,57,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82616,both interview and exam,male,63,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,12500 +82617,both interview and exam,female,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,70000 +82618,both interview and exam,male,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +82619,both interview and exam,male,69,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +82620,both interview and exam,male,3,NA,white,2,41,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,17500 +82621,both interview and exam,male,41,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,5,married,NA,TRUE,100000 +82622,both interview and exam,female,5,NA,white,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 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exam,male,78,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,22500 +82652,both interview and exam,male,73,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,3,married,NA,TRUE,87500 +82653,both interview and exam,male,7,NA,white,1,94,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,12500 +82654,both interview and exam,female,18,NA,other hispanic,1,219,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,87500 +82655,both interview and exam,female,75,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,1,widowed,NA,TRUE,50000 +82656,both interview and exam,male,12,NA,white,2,153,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,100000 +82657,both interview and exam,female,66,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,30000 +82658,both interview and exam,male,6,NA,black,1,80,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,17500 +82659,both interview and exam,female,0,6,black,1,7,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82660,both interview and exam,female,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,40000 +82661,both interview and exam,female,6,NA,asian,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +82662,interview only,female,13,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +82663,both interview and exam,female,0,4,black,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82664,both interview and exam,male,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +82665,both interview and exam,female,53,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,22500 +82666,both interview and exam,male,47,NA,black,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,married,NA,TRUE,NA +82667,both interview and exam,male,5,NA,asian,2,61,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +82668,both interview and exam,male,32,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,NA +82669,both interview and exam,female,33,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +82670,both interview and exam,male,18,NA,mexican american,2,223,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,17500 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exam,male,41,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,22500 +82681,both interview and exam,male,1,17,black,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82682,both interview and exam,male,37,NA,black,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,widowed,NA,TRUE,100000 +82683,interview only,male,9,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,12500 +82684,both interview and exam,female,42,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,no,TRUE,40000 +82685,both interview and exam,male,47,NA,white,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,divorced,NA,TRUE,40000 +82686,both interview and exam,male,10,NA,other hispanic,2,121,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,2500 +82687,both interview and exam,female,5,NA,black,1,69,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +82688,both interview and exam,male,63,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,35,NA,5,widowed,NA,TRUE,NA +82689,both interview and exam,female,0,1,white,1,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +82690,both interview and exam,male,6,NA,white,1,72,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82691,both interview and exam,male,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,separated,NA,TRUE,NA +82692,both interview and exam,male,39,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,7500 +82693,both interview and exam,male,6,NA,mexican american,2,80,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,22500 +82694,both interview and exam,female,8,NA,mexican american,2,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,NA +82695,both interview and exam,male,20,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,22500 +82696,both interview and exam,female,22,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,12500 +82697,both interview and exam,female,18,NA,asian,1,227,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +82698,both interview and exam,male,74,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,70000 +82699,both interview and exam,male,7,NA,other,1,95,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,50000 +82700,both interview and exam,male,4,NA,asian,2,52,NA,NA,FALSE,NA,3,NA,NA,NA,NA,TRUE,87500 +82701,both interview and exam,female,14,NA,white,2,179,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,2500 +82702,both interview and exam,female,64,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,50000 +82703,both interview and exam,male,50,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,4,living_with_partner,NA,TRUE,50000 +82704,both interview and exam,male,41,NA,white,1,NA,FALSE,NA,FALSE,TRUE,45,NA,4,married,NA,TRUE,100000 +82705,both interview and exam,female,76,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82706,both interview and exam,female,9,NA,white,1,113,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +82707,interview only,male,73,NA,white,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,12500 +82708,both interview and exam,female,78,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 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exam,male,34,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +82719,both interview and exam,female,35,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +82720,both interview and exam,male,58,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,married,NA,TRUE,50000 +82721,both interview and exam,male,49,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,50000 +82722,both interview and exam,male,6,NA,mexican american,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +82723,both interview and exam,female,74,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +82724,both interview and exam,female,28,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,7500 +82725,both interview and exam,female,17,NA,asian,1,208,FALSE,NA,FALSE,TRUE,3,11,NA,NA,NA,TRUE,7500 +82726,both interview and exam,female,16,NA,black,1,197,NA,NA,TRUE,TRUE,NA,9,NA,NA,NA,TRUE,87500 +82727,both interview and exam,male,77,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82728,both interview and exam,female,18,NA,mexican american,2,218,FALSE,NA,FALSE,FALSE,17.5,11,NA,NA,NA,TRUE,NA +82729,both interview and exam,female,22,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,no,TRUE,17500 +82730,both interview and exam,female,14,NA,asian,1,171,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +82731,both interview and exam,female,36,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,no,TRUE,40000 +82732,both interview and exam,male,9,NA,white,2,116,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +82733,both interview and exam,female,40,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +82734,interview only,male,29,NA,mexican american,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +82735,both interview and exam,female,23,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,living_with_partner,no,TRUE,40000 +82736,both interview and exam,male,26,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,50000 +82737,both interview and exam,female,66,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +82738,both interview and exam,male,3,NA,black,2,47,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +82739,both interview and exam,female,55,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +82740,both interview and exam,male,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,widowed,NA,TRUE,40000 +82741,both interview and exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,7500 +82742,both interview and exam,female,52,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,divorced,NA,TRUE,100000 +82743,both interview and exam,female,47,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,married,NA,TRUE,NA +82744,both interview and exam,male,0,0,black,2,2,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82745,both interview and exam,male,38,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,living_with_partner,NA,TRUE,60000 +82746,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,living_with_partner,NA,TRUE,50000 +82747,both interview and exam,female,0,10,white,2,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +82748,both interview and exam,female,43,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,17500 +82749,both interview and exam,male,64,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +82750,both interview and exam,female,27,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,4,living_with_partner,no,TRUE,50000 +82751,both interview and exam,female,0,5,white,2,6,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +82752,interview only,male,34,NA,black,NA,NA,FALSE,NA,FALSE,FALSE,3,NA,4,married,NA,TRUE,30000 +82753,both interview and exam,female,2,NA,other hispanic,1,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82754,both interview and 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exam,male,67,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,FALSE,22500 +82774,both interview and exam,female,19,NA,black,2,235,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,2500 +82775,both interview and exam,male,57,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,4,married,NA,FALSE,NA +82776,both interview and exam,male,37,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,3,married,NA,TRUE,30000 +82777,both interview and exam,female,2,NA,mexican american,2,28,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,7500 +82778,both interview and exam,male,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +82779,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82780,both interview and exam,female,28,NA,other,2,NA,FALSE,NA,FALSE,FALSE,7.5,NA,3,married,no,FALSE,NA +82781,both interview and exam,female,17,NA,mexican american,2,210,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,87500 +82782,both interview and exam,male,53,NA,other 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exam,female,51,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,87500 +82812,both interview and exam,male,62,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,17500 +82813,both interview and exam,female,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,no,TRUE,50000 +82814,both interview and exam,male,44,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,NA +82815,interview only,female,80,NA,asian,NA,NA,FALSE,NA,FALSE,TRUE,35,NA,5,widowed,NA,TRUE,7500 +82816,both interview and exam,male,66,NA,black,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82817,both interview and exam,female,16,NA,other,2,203,NA,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,100000 +82818,both interview and exam,male,11,NA,black,1,136,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +82819,both interview and exam,male,2,NA,black,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +82820,both interview and exam,male,78,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,50000 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exam,male,59,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,87500 +82841,both interview and exam,male,45,NA,asian,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,60000 +82842,both interview and exam,female,68,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +82843,both interview and exam,female,14,NA,black,2,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,70000 +82844,both interview and exam,male,58,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,87500 +82845,both interview and exam,male,64,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,100000 +82846,both interview and exam,female,33,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,12.5,NA,2,married,no,TRUE,50000 +82847,both interview and exam,female,5,NA,white,2,65,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,70000 +82848,both interview and exam,female,18,NA,other,1,219,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +82849,both interview and exam,male,80,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 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exam,female,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,widowed,NA,TRUE,50000 +82860,both interview and exam,male,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82861,both interview and exam,female,6,NA,black,1,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,30000 +82862,both interview and exam,female,39,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,5,married,no,TRUE,100000 +82863,interview only,female,69,NA,black,NA,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,50000 +82864,both interview and exam,male,31,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,NA +82865,both interview and exam,female,14,NA,other hispanic,1,175,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,FALSE,17500 +82866,interview only,female,5,NA,white,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,87500 +82867,both interview and exam,female,41,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,no,TRUE,100000 +82868,both interview and exam,male,78,NA,white,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,12500 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interview and exam,female,76,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,40000 +82880,both interview and exam,female,6,NA,other hispanic,2,79,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,30000 +82881,both interview and exam,male,70,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82882,both interview and exam,female,80,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,55,NA,5,widowed,NA,TRUE,NA +82883,both interview and exam,female,1,17,asian,2,18,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82884,both interview and exam,male,18,NA,white,1,228,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,100000 +82885,both interview and exam,male,10,NA,black,1,131,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,22500 +82886,both interview and exam,male,80,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,NA +82887,both interview and exam,female,7,NA,black,1,91,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +82888,both interview and 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exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,17500 +82898,both interview and exam,male,66,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,TRUE,30000 +82899,both interview and exam,male,66,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,45,NA,3,married,NA,TRUE,NA +82900,both interview and exam,male,80,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +82901,both interview and exam,male,68,NA,mexican american,2,NA,FALSE,NA,FALSE,TRUE,35,NA,1,living_with_partner,NA,FALSE,12500 +82902,both interview and exam,female,41,NA,white,1,NA,FALSE,NA,FALSE,TRUE,0.5,NA,5,married,no,TRUE,100000 +82903,both interview and exam,female,57,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,50000 +82904,both interview and exam,female,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,87500 +82905,both interview and exam,male,7,NA,mexican american,1,86,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +82906,both interview 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exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,22500 +82946,both interview and exam,female,45,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,70000 +82947,both interview and exam,female,0,4,white,1,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82948,both interview and exam,female,45,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,12500 +82949,both interview and exam,male,67,NA,white,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,3,married,NA,TRUE,40000 +82950,interview only,female,2,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +82951,both interview and exam,female,65,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,30000 +82952,both interview and exam,female,66,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82953,both interview and exam,male,68,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +82954,interview only,male,4,NA,black,NA,NA,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +82955,interview 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exam,male,47,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,separated,NA,TRUE,7500 +83160,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,100000 +83161,both interview and exam,female,2,NA,asian,2,32,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +83162,both interview and exam,female,19,NA,white,2,234,FALSE,NA,TRUE,TRUE,NA,14,NA,NA,NA,TRUE,100000 +83163,both interview and exam,male,57,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,1,married,NA,FALSE,NA +83164,both interview and exam,male,8,NA,white,1,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +83165,both interview and exam,female,47,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,25,NA,1,separated,NA,TRUE,50000 +83166,both interview and exam,female,6,NA,other,2,78,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,87500 +83167,both interview and exam,female,2,NA,black,1,27,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +83168,both interview and exam,male,8,NA,asian,2,105,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,40000 +83169,both interview and 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exam,male,15,NA,black,1,186,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,22500 +83374,both interview and exam,male,61,NA,white,2,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,100000 +83375,both interview and exam,male,70,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,FALSE,100000 +83376,both interview and exam,female,43,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +83377,both interview and exam,female,11,NA,white,1,134,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,30000 +83378,both interview and exam,male,1,20,mexican american,1,21,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +83379,both interview and exam,female,48,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,7500 +83380,both interview and exam,female,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,30000 +83381,both interview and exam,male,59,NA,other,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,17500 +83382,both interview and 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exam,male,2,NA,black,2,26,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,40000 +83420,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,70000 +83421,both interview and exam,female,2,NA,white,1,33,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +83422,both interview and exam,male,1,13,black,2,13,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,2500 +83423,both interview and exam,male,66,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,45,NA,5,married,NA,FALSE,100000 +83424,both interview and exam,female,57,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,30000 +83425,both interview and exam,female,34,NA,asian,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,5,married,yes,TRUE,100000 +83426,both interview and exam,female,56,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +83427,both interview and exam,female,27,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,50000 +83428,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,divorced,NA,TRUE,30000 +83429,both interview and exam,female,61,NA,other hispanic,1,NA,FALSE,NA,FALSE,TRUE,7.5,NA,3,married,NA,FALSE,30000 +83430,both interview and exam,female,23,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,87500 +83431,both interview and exam,female,64,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,87500 +83432,both interview and exam,male,62,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,NA +83433,both interview and exam,female,29,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,30000 +83434,both interview and exam,female,1,23,other hispanic,2,23,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,12500 +83435,both interview and exam,female,8,NA,black,2,101,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,7500 +83436,both interview and exam,male,76,NA,mexican american,2,NA,FALSE,NA,FALSE,FALSE,35,NA,1,married,NA,FALSE,60000 +83437,both interview and exam,female,49,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,50000 +83438,both interview and exam,male,57,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +83439,both interview and exam,male,30,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,never_married,NA,TRUE,NA +83440,both interview and exam,female,13,NA,asian,1,160,NA,NA,FALSE,FALSE,3,7,NA,NA,NA,TRUE,60000 +83441,both interview and exam,male,62,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,60000 +83442,both interview and exam,female,0,3,black,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,30000 +83443,both interview and exam,male,0,10,black,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +83444,both interview and exam,male,5,NA,other,2,64,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +83445,both interview and exam,female,80,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,7500 +83446,both interview and exam,male,68,NA,black,2,NA,FALSE,NA,FALSE,TRUE,12.5,NA,1,living_with_partner,NA,TRUE,2500 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exam,female,65,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,NA,TRUE,12500 +83457,both interview and exam,female,13,NA,asian,2,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,40000 +83458,both interview and exam,female,11,NA,white,2,141,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,12500 +83459,both interview and exam,female,31,NA,white,2,NA,FALSE,NA,FALSE,TRUE,17.5,NA,5,living_with_partner,no,TRUE,2500 +83460,both interview and exam,male,79,NA,black,1,NA,TRUE,TRUE,TRUE,TRUE,NA,NA,2,married,NA,TRUE,40000 +83461,both interview and exam,female,42,NA,other hispanic,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,no,TRUE,22500 +83462,both interview and exam,male,2,NA,white,1,34,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,22500 +83463,both interview and exam,male,10,NA,white,1,121,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,TRUE,60000 +83464,both interview and exam,female,75,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,never_married,NA,TRUE,NA +83465,both interview and exam,male,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,never_married,NA,TRUE,22500 +83466,both interview and exam,female,32,NA,other hispanic,2,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,divorced,yes,FALSE,NA +83467,both interview and exam,male,20,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +83468,both interview and exam,male,15,NA,white,2,184,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,50000 +83469,both interview and exam,male,0,4,white,2,5,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,7500 +83470,both interview and exam,male,4,NA,white,1,56,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +83471,both interview and exam,female,0,3,white,1,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +83472,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,married,NA,TRUE,100000 +83473,both interview and exam,female,3,NA,mexican american,2,44,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +83474,both interview and exam,female,11,NA,mexican american,1,143,NA,NA,TRUE,TRUE,NA,5,NA,NA,NA,TRUE,30000 +83475,both interview and exam,female,13,NA,other hispanic,1,161,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,30000 +83476,both interview and exam,male,22,NA,mexican american,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,7500 +83477,both interview and exam,male,20,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,NA,TRUE,87500 +83478,both interview and exam,male,33,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,living_with_partner,NA,TRUE,100000 +83479,both interview and exam,female,8,NA,black,1,97,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,2500 +83480,both interview and exam,female,24,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,70000 +83481,both interview and exam,male,80,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,NA +83482,both interview and exam,female,11,NA,other hispanic,1,134,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,17500 +83483,both interview and exam,female,54,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,widowed,NA,TRUE,100000 +83484,both interview and exam,female,67,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,divorced,NA,TRUE,12500 +83485,both interview and exam,male,18,NA,black,1,219,FALSE,NA,TRUE,TRUE,NA,10,NA,NA,NA,TRUE,30000 +83486,both interview and exam,female,25,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,2500 +83487,both interview and exam,male,33,NA,white,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,4,married,NA,TRUE,40000 +83488,both interview and exam,female,4,NA,mexican american,2,51,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +83489,both interview and exam,male,13,NA,black,2,163,NA,NA,TRUE,TRUE,NA,7,NA,NA,NA,TRUE,12500 +83490,both interview and exam,male,8,NA,mexican american,2,98,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +83491,both interview and exam,female,39,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,married,no,TRUE,7500 +83492,both interview and exam,male,22,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,40000 +83493,both interview and exam,female,6,NA,mexican american,1,75,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,FALSE,7500 +83494,both interview and exam,female,19,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,60000 +83495,both interview and exam,male,3,NA,white,1,46,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +83496,both interview and exam,female,18,NA,black,1,220,FALSE,NA,TRUE,TRUE,NA,12,NA,NA,NA,TRUE,60000 +83497,both interview and exam,female,29,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,no,TRUE,100000 +83498,interview only,male,7,NA,asian,NA,NA,NA,NA,TRUE,TRUE,NA,1,NA,NA,NA,TRUE,100000 +83499,both interview and exam,male,30,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,50000 +83500,both interview and exam,female,6,NA,white,1,84,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,100000 +83501,both interview and exam,male,10,NA,white,1,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,100000 +83502,both interview and exam,female,8,NA,mexican american,1,99,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,100000 +83503,both interview and exam,male,24,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,living_with_partner,NA,TRUE,30000 +83504,both interview and exam,female,2,NA,asian,1,34,NA,NA,FALSE,TRUE,3,NA,NA,NA,NA,TRUE,50000 +83505,both interview and exam,female,70,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,35,NA,5,married,NA,TRUE,30000 +83506,both interview and exam,male,46,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,married,NA,TRUE,87500 +83507,both interview and exam,male,50,NA,other hispanic,1,NA,FALSE,NA,FALSE,FALSE,17.5,NA,4,married,NA,FALSE,30000 +83508,both interview and exam,male,0,2,other,1,4,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,50000 +83509,both interview and exam,male,5,NA,other hispanic,2,68,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,50000 +83510,both interview and exam,male,54,NA,black,1,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,17500 +83511,both interview and exam,female,68,NA,other,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,17500 +83512,both interview and exam,male,9,NA,mexican american,1,117,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,87500 +83513,both interview and exam,male,1,17,black,1,17,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,NA +83514,both interview and exam,female,53,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,35,NA,3,married,NA,FALSE,NA +83515,both interview and exam,male,3,NA,asian,1,43,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +83516,both interview and exam,female,66,NA,asian,1,NA,FALSE,NA,FALSE,TRUE,17.5,NA,3,separated,NA,TRUE,7500 +83517,both interview and exam,female,17,NA,asian,1,205,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,100000 +83518,both interview and exam,female,33,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,100000 +83519,both interview and exam,male,19,NA,white,1,239,FALSE,NA,TRUE,TRUE,NA,13,NA,NA,NA,TRUE,17500 +83520,both interview and exam,female,49,NA,other 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exam,female,59,NA,asian,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,3,married,NA,TRUE,100000 +83530,both interview and exam,female,80,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,widowed,NA,TRUE,40000 +83531,both interview and exam,male,15,NA,black,1,184,NA,NA,TRUE,TRUE,NA,8,NA,NA,NA,TRUE,100000 +83532,both interview and exam,female,17,NA,mexican american,2,208,FALSE,NA,TRUE,TRUE,NA,11,NA,NA,NA,TRUE,40000 +83533,both interview and exam,male,63,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,married,NA,TRUE,60000 +83534,both interview and exam,male,2,NA,mexican american,2,25,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,FALSE,22500 +83535,both interview and exam,male,69,NA,black,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +83536,both interview and exam,female,20,NA,mexican american,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,never_married,no,TRUE,40000 +83537,both interview and exam,male,0,1,white,1,1,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,100000 +83538,both interview and exam,male,0,10,black,1,11,NA,NA,TRUE,TRUE,NA,NA,NA,NA,NA,TRUE,60000 +83539,both interview and exam,female,73,NA,asian,2,NA,FALSE,NA,FALSE,TRUE,25,NA,1,never_married,NA,TRUE,40000 +83540,both interview and exam,male,30,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,2,never_married,NA,TRUE,12500 +83541,both interview and exam,male,44,NA,mexican american,1,NA,FALSE,NA,FALSE,FALSE,12.5,NA,2,married,NA,FALSE,22500 +83542,both interview and exam,female,71,NA,black,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,divorced,NA,TRUE,40000 +83543,both interview and exam,male,71,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,3,widowed,NA,TRUE,12500 +83544,both interview and exam,male,68,NA,mexican american,1,NA,FALSE,NA,FALSE,TRUE,45,NA,3,divorced,NA,TRUE,17500 +83545,both interview and exam,female,7,NA,black,2,93,NA,NA,TRUE,TRUE,NA,2,NA,NA,NA,TRUE,12500 +83546,both interview and exam,male,59,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,5,married,NA,TRUE,100000 +83547,both interview and 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interview and exam,female,65,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,1,widowed,NA,TRUE,22500 +83577,both interview and exam,female,10,NA,white,2,132,NA,NA,TRUE,TRUE,NA,4,NA,NA,NA,TRUE,50000 +83578,both interview and exam,female,63,NA,white,2,NA,FALSE,NA,FALSE,TRUE,55,NA,5,divorced,NA,TRUE,60000 +83579,both interview and exam,female,6,NA,black,1,81,NA,NA,TRUE,TRUE,NA,0,NA,NA,NA,TRUE,40000 +83580,both interview and exam,male,28,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,divorced,NA,TRUE,50000 +83581,both interview and exam,female,41,NA,black,2,NA,TRUE,FALSE,TRUE,TRUE,NA,NA,5,divorced,yes,TRUE,22500 +83582,both interview and exam,female,9,NA,mexican american,1,114,NA,NA,TRUE,TRUE,NA,3,NA,NA,NA,FALSE,17500 +83583,both interview and exam,male,20,NA,white,1,NA,FALSE,NA,TRUE,TRUE,NA,NA,3,never_married,NA,TRUE,30000 +83584,both interview and exam,female,56,NA,white,2,NA,FALSE,NA,TRUE,TRUE,NA,NA,4,divorced,NA,TRUE,7500 +83585,both interview and 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b/docs/content/complete/01_custom_functions_complete.html @@ -0,0 +1,1351 @@ + + + + + + + + + +Custom functions – Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+
+ +
+ +
+ + + + +
+ +
+
+

Custom functions

+
+ + + +
+ + + + +
+ + + +
+ + +
+

A simple custom function

+

In this notebook, you will learn how to define your own functions.

+
+
# define a function called `add_one()` that adds 1 to its argument, x
+add_one <- function(x) {
+  x + 1
+}
+
+

The code that is run when you “call” your function is inside the curly parentheses.

+
+
# apply function add_one() to 5
+add_one(5)
+
+
[1] 6
+
+
+
+
# apply function add_one() to 5 using a *named argument*
+add_one(x = 5)
+
+
[1] 6
+
+
+

What happens when the body of your function contains two pieces of code?

+
+
# re-define add_one() with two lines of code: x - 1 and x + 1
+add_one <- function(x) {
+  x - 1
+  x + 1
+}
+
+
+
# apply add_one to 5 again
+add_one(5)
+
+
[1] 6
+
+
+

By default, any custom R function you create will automatically return the final result that is computed.

+

For this reason, it is common to explicitly provide a “return statement”.

+
+
# redefine add_one() but apply the return statement to x - 1 only
+add_one <- function(x) {
+  return(x - 1)
+  x + 1
+}
+
+
+
# apply add_one to 5 again
+add_one(5)
+
+
[1] 4
+
+
+
+
+

The general syntax of a custom function

+

The general syntax of a custom function is shown below:

+
+
fn_name <- function(arg) {
+  # code involving arg
+  
+  return(object)
+}
+
+
+
+

Exercise

+

Write a function called “cube” that returns the cubic (^3) of the argument

+
+
# define function cube()
+cube <- function(value) {
+  cubed_value = value^3
+  return(cubed_value)
+}
+
+
+
# apply cube() to 3
+cube(value = 3)
+
+
[1] 27
+
+
+
+
+

Multiple arguments

+

To create a function with multiple arguments, you need to provide two arguments inside the function definition, separated by a comma. The function below has two arguments: x and y:

+
+
# define a function called add_x2y that computes x + 2y
+add_x2y <- function(x, y) {
+  x + 2*y
+}
+
+

When you call this add_x2y(), you can then specify a value for each argument, separated by a comma:

+
+
# apply add_x2y() to x = 2 and y = 5
+add_x2y(2, 5)
+
+
[1] 12
+
+
+

When you have multiple arguments, funny things can start to happen when you don’t name your arguments.

+

What do you think will happen if you first provide a named argument for the second argument y by specifying y = 2, and then provide an unnamed argument afterwards?

+
+
add_x2y(y = 2, 5)
+
+
[1] 9
+
+
+

R will be clever and it will first apply the named arguments by assigning y to the value 2, and then fill in the remaining argument, so x will be assigned to the value 5.

+

It is good practice to name your arguments if there is any chance for ambiguity.

+
+
# run add_x2y() with named arguments x = 2 and y = 5
+add_x2y(x = 2, y = 5)
+
+
[1] 12
+
+
+

Note that when you provide named arguments, it technically doesn’t matter which order you provide them in (but this is not true when you don’t provide named arguments!)

+
+
# run add_x2y() with named arguments y = 5 and x = 2
+add_x2y(y = 5, x = 2)
+
+
[1] 12
+
+
+

Again, note that even when you provide named arguments in a function call (e.g., in add_x2y(x = 2, y = 5)), you are not defining a global version of the arguments, i.e., there is no y defined:

+
+
y
+
+
Error in eval(expr, envir, enclos): object 'y' not found
+
+
+

What do you think will happen when you call add_x2y without any parentheses?

+
+
# run add_x2y
+add_x2y
+
+
function(x, y) {
+  x + 2*y
+}
+<bytecode: 0x12902b270>
+
+
+

It will print out the definition of the function!

+

What do you think will happen when you call add_x2y with parentheses but no arguments?

+
+
add_x2y()
+
+
Error in add_x2y(): argument "x" is missing, with no default
+
+
+

You get an error! We can fix this by providing “default” values for the arguments.

+
+

Default values

+

To provide default values for your arguments, you can assign the argument inside the function definition. In the example below, both x and y are given the default values of 1.

+
+
# redefine add_x2y() with default values for x and y (both 1)
+add_x2y <- function(x = 1, y = 1) {
+  x + 2*y
+}
+
+
+
# call add_x2y() without any arguments
+add_x2y()
+
+
[1] 3
+
+
+

What happens if we only provide some of the arguments?

+
+
# run add_x2y() with a single unnamed argument, 4
+add_x2y(4)
+
+
[1] 6
+
+
+
+
# run add_x2y() with a single argument: y = 3
+add_x2y(y = 3)
+
+
[1] 7
+
+
+
+
+

Exercise

+

Without using the mean() function, write a function called my_mean() that takes four values as its arguments and computes their mean. Ensure that each argument has a default of 0. Use your function to compute the mean of the values 4, 5, 2, 1.

+

How would you modify your function to take a single vector of length 4 as its argument instead of four separate arguments?

+
+

Solution

+
+
my_mean <- function(a = 0, b = 0, c = 0, d = 0) {
+  return((a + b + c + d) / 4)
+}
+
+

Note that when we run this function it is taking four separate arguments (rather than a vector, as the original mean function does):

+
+
my_mean(4, 5, 2, 1)
+
+
[1] 3
+
+
+

You can define a function that instead takes a single vector as its argument:

+
+
my_mean_vec <- function(vec) {
+  return(sum(vec) / length(vec))
+}
+
+

and then to run this function, you provide a vector by wrapping the four values inside c():

+
+
my_mean_vec(c(4, 5, 2, 1))
+
+
[1] 3
+
+
+

What happens if you apply your original my_mean() function to this vector?

+
+
my_mean(c(4, 5, 2, 1))
+
+
[1] 1.00 1.25 0.50 0.25
+
+
+

This is equivalent to assigning the argument a = c(4, 5, 2, 1), and then not providing any values for the b, c, and d arguments (so their default values are used). So the above code is equivalent to:

+
+
# (a + b + c + d) / 4
+
+(c(4, 5, 2, 1) + 0 + 0 + 0) / 4
+
+
[1] 1.00 1.25 0.50 0.25
+
+
+

The fact that we haven’t told any of our functions what type of object the arguments should be means that the function will simply take whatever object it is given and try and run the code.

+
+
+
+
+

If/else statements

+
+

If statements

+

The following code defines a variable a, and then runs some conditional code that is only run if the condition a == 1 is TRUE.

+
+
# define a variable a containing 5
+a <- 5
+# if a is equal to 1, print out some text
+if (a == 1) {
+  "a is 1"
+}
+
+# Then:
+# 1. try the code again, with a equal to 1
+# 2. replace the code that is run in the if statement with a mathematical computation
+# 3. replace the code that is run in the if statement with a variable definition (e.g., define y <- 3)
+
+a <- 1
+# if a is equal to 1, print out some text
+if (a == 1) {
+  y <- 3
+}
+
+

Unlike for a function, if you define a variable inside an if statement, then this variable will have been defined in our “global” environment too.

+
+
# Does y exist globally?
+y
+
+
+
+

Else statemenets

+

The “else” part of the “if/else” statement provides some code that will be run if the “if” condition is not TRUE.

+
+
# define a variable "a" containing 3
+a <- 3
+# if "a" equals 1, define y <- 3, else define y <- 9
+if (a == 1) {
+  y <- 3
+} else {
+  y <- 9
+}
+
+
+
# check what y was assigned to
+y
+
+
[1] 9
+
+
+
+
+

Using “if” statements to provide custom errors for a function

+

The following uses an “if” statement to add a “stop condition” that throws an error when innapropriate arguments are provided

+
+
# add an "if" condition to throw an error if `a` is either non-numeric OR the length of `a` is greater than 1
+my_mean <- function(a = 0, b = 0, c = 0, d = 0) {
+  # write your if statement here containing a stop() function
+  if (!is.numeric(a) | (length(a) != 1)) {
+    stop("'a' must be a numeric value of length 1")
+  }
+  return((a + b + c + d) / 4)
+}
+
+
+
+

Exercise

+
    +
  1. Write a standalone if/else statement that checks whether the value in a variable called age is at least 18. If the age variable is 18 or older, your statement should return the character value of “You are eligible to vote” and if not, your statement should return “You are not eligible to vote”
    2. +
+
+
age <- 21
+if (age >= 18) {
+  "You are eligible to vote"
+} else {
+  "You are not eligible to vote"
+}
+
+
[1] "You are eligible to vote"
+
+
+
    +
  1. Write a function that computes the area of a circle (area = pi * radius^2) with the radius as its argument, and throws an error if a non-numeric or a negative radius value is given.
    2. +
+
+
circle_area <- function(radius) {
+  if (!is.numeric(radius) | radius < 0) {
+    stop("'radius' must be a non-negative numeric value")
+  }
+  area <- pi * radius^2
+  return(area)
+}
+
+

Test your function on the following code

+
+
# the following should throw an error:
+circle_area("4")
+
+
Error in circle_area("4"): 'radius' must be a non-negative numeric value
+
+
circle_area(-4)
+
+
Error in circle_area(-4): 'radius' must be a non-negative numeric value
+
+
# the following should NOT throw an error:
+circle_area(4)
+
+
[1] 50.26548
+
+
+
+
+
+

Default argument options with match.arg()

+

Below, we give an example of providing multiple options to an argument.

+
+
# define a function add_x2y with three arguments:
+# x: a numeric value with default value 1
+# y: a numeric value with default value 1
+# output_type: a character value with default value "numeric" and alternative option "character"
+
+# in the body of the function:
+# use match.arg() to ensure that output_type is one of the options provided
+# use an if statement to modify the output based on the value of output_type
+
+
+add_x2y <- function(x = 1, y = 1, output_type = c("numeric", "character")) {
+  # this line will set the default value of output_type to be "numeric"
+  # and will only allow options provided in the default vector
+  output_type <- match.arg(output_type)
+  
+  # stop condition if x or y are not numeric
+  if (!is.numeric(x) | !is.numeric(y)) {
+    stop("'x' and 'y' must be numeric")
+  }
+  
+  # computing my result
+  result <- x + 2 * y
+  
+  # returning result in the format specified by output_type
+  if (output_type == "numeric") {
+    return(result)
+  } else if (output_type == "character") {
+    return(as.character(result))
+  }
+  
+}
+
+
+
# apply add_x2y() to x = 2 and y = 3 and output_type = "character"
+add_x2y(x = 2, y = 3, output_type = "character")
+
+
[1] "8"
+
+
+
+
# apply add_x2y() to x = 2 and y = 3 with no output_type specified
+add_x2y(2, 3)
+
+
[1] 8
+
+
+
+
# apply add_x2y() to x = 2 and y = 3 and output_type = "logical" 
+add_x2y(2, 3, output_type = "logical")
+
+
Error in match.arg(output_type): 'arg' should be one of "numeric", "character"
+
+
+
+

Exercise

+

Write a function called calculate_area() that will calculate the area of the shape specified in the argument shape, which has options “circle”, “square”, and “triangle”. Your function will need to have the following additional arguments:

+
    +

  • radius for computing the area of a circle (pi * radius^2),

    • +

  • side for computing the area of a square (side^2),

    • +

  • base and height for computing the area of a triangle (height * base / 2).

    • +
+

Arguments that are not always required should have a default value of NULL. Your function should throw an error when you fail any value other than “circle”, “square” or “triangle” for the shape argument (you can use match.arg() to do this!).

+

Your function should throw an error when:

+
    +

  1. the ‘radius’ argument is not provided when shape == "circle"

    2. +

  2. the ‘side’ argument is not provided when shape == "square"

    3. +

  3. the ‘base’ and ‘height’ arguments are not provided when shape == "triangle"

    4. +
+
+
calculate_area <- function(shape = c("circle", "square", "triangle"),
+                           radius = NULL,
+                           side = NULL,
+                           base = NULL,
+                           height = NULL) {
+  
+  shape = match.arg(shape)
+  # error statements
+  if (shape == "circle" & is.na(radius)) {
+    stop("'radius' required for 'circle' shape")
+  } 
+  if (shape == "square" & is.na(side)) {
+    stop("'side' required for 'square' shape")
+  }
+  if (shape == "triangle" & (is.na(base) | is.na(height))) {
+    stop("'base' and 'height' required for 'triangle' shape")
+  }
+  
+  # compute the area
+  if (shape == "circle") {
+    area <- pi * radius^2
+  } else if (shape == "square") {
+    area <- side^2
+  } else if (shape == "triangle") {
+    area <- base * height / 2
+  }
+  
+  return(area)
+  
+}
+
+
+
+
+

Tidy evaluation for writing tidyverse-style functions

+

Sometimes you want to write a function whose argument is a column of a data frame without quotes (i.e., in the tidyverse style) so that you can use it in a tidyverse function.

+
+
# load in the tidyverse and demographics NHANES data
+library(tidyverse)
+
+
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
+✔ dplyr     1.1.4     ✔ readr     2.1.5
+✔ forcats   1.0.0     ✔ stringr   1.5.1
+✔ ggplot2   3.5.1     ✔ tibble    3.2.1
+✔ lubridate 1.9.3     ✔ tidyr     1.3.1
+✔ purrr     1.0.2     
+── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
+✖ dplyr::filter() masks stats::filter()
+✖ dplyr::lag()    masks stats::lag()
+ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
+
+
demographics <- read_csv("data/demographics.csv")
+
+
Rows: 10175 Columns: 19
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (5): interview_examination, gender, race, marital_status, pregnant
+dbl (9): respondent_id, age_years, age_months_sc_0_2yr, six_month_period, ag...
+lgl (5): served_active_duty_us, served_active_duty_foreign, born_usa, citize...
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
+
+
+
+
# take a look at the demographics data
+head(demographics)
+
+
# A tibble: 6 × 19
+  respondent_id interview_examination gender age_years age_months_sc_0_2yr race 
+          <dbl> <chr>                 <chr>      <dbl>               <dbl> <chr>
+1         73557 both interview and e… male          69                  NA black
+2         73558 both interview and e… male          54                  NA white
+3         73559 both interview and e… male          72                  NA white
+4         73560 both interview and e… male           9                  NA white
+5         73561 both interview and e… female        73                  NA white
+6         73562 both interview and e… male          56                  NA mexi…
+# ℹ 13 more variables: six_month_period <dbl>, age_months_ex_0_19yr <dbl>,
+#   served_active_duty_us <lgl>, served_active_duty_foreign <lgl>,
+#   born_usa <lgl>, citizen_usa <lgl>, time_in_us <dbl>, education_youth <dbl>,
+#   education <dbl>, marital_status <chr>, pregnant <chr>,
+#   language_english <lgl>, household_income <dbl>
+
+
+

Notice that when we refer to the variables from our data frame in the context of the tidyverse (including ggplot2), we do not use quotes around the column names:

+
+
# compute boxplots for the age_years distribution across different levels of the language_english variable
+demographics |> ggplot() +
+  geom_boxplot(aes(x = language_english,
+                   y = age_years))
+
+
+
+

+
+
+
+
+

Let’s try and turn this into a function so we can create boxplots comparing the age distribution across all of the levels of other categorical variables without having to copy-and-paste the code over and over again.

+

In this first attempt, we use variable_name as the argument:

+
+
# turn the above boxplot code into a function called createBoxplots()
+createBoxplots <- function(variable_name) {
+  
+  demographics |> ggplot() +
+    geom_boxplot(aes(x = variable_name,
+                     y = age_years)) 
+  
+}
+
+
+
# try to apply createBoxplots() to the language_english column 
+createBoxplots(language_english)
+
+
Error in `geom_boxplot()`:
+! Problem while computing aesthetics.
+ℹ Error occurred in the 1st layer.
+Caused by error:
+! object 'language_english' not found
+
+
createBoxplots("language_english")
+
+
+
+

+
+
+
+
+

The issue is that ggplot wants us to refer to the column names without strings, but our custom function doesn’t know how to find our column name variable that we provide.

+

We can use tidy evaluation ({ var_name }) to solve this problem.

+
+
# update our createBoxplots() function so that it uses tidy_evaluation
+createBoxplots <- function(variable_name) {
+  demographics |> ggplot() +
+    geom_boxplot(aes(x = {{ variable_name }},
+                     y = age_years)) 
+}
+
+

And now it works:

+
+
# apply createBoxplots() to the language_english column
+createBoxplots(language_english)
+
+
+
+

+
+
+
+
+

Let’s use our function on a few different columns to make sure:

+
+
# apply createBoxplots() to the marital_status column
+createBoxplots(marital_status)
+
+
+
+

+
+
+
+
# apply createBoxplots() to the pregnant column
+createBoxplots(pregnant)
+
+
+
+

+
+
+
+
+
+

Tip: Using patchwork to patch together plots

+

The patchwork library can be used to create custom grids of ggplot objects (be sure to expand your plot window if the plots aren’t showing up properly):

+
+
# load the patchwork library
+library(patchwork)
+# create a grid of the language_english and marital_status boxplots
+createBoxplots(language_english) + createBoxplots(marital_status)
+
+
+
+

+
+
+
+
+
+
# create a grid of the language_english and pregnant boxplots 
+# on top with the marital_status boxplots underneath
+(createBoxplots(language_english) + createBoxplots(pregnant)) /   createBoxplots(marital_status)
+
+
+
+

+
+
+
+
+
+
+

Exercise

+

Create a function called createOrderedBars() that takes a categorical column from demographics as its argument and creates a bar chart for the average age for each level of the variable.

+

Hint: Some example code for computing the average age for each level of the marital_status variable and creating a bar chart is shown below:

+
+
demographics |> 
+  group_by(marital_status) |>
+  summarize(mean_age = mean(age_years)) |>
+  ggplot() +
+  geom_col(aes(x = marital_status, 
+               y = mean_age))
+
+
+
+

+
+
+
+
+

Challenge activity: Arrange the bars in ascending order, and provide an argument called ascending that allows the user to specify whether or not the bars will be arranged in ascending order.

+
+

Solution

+

Note that you’ll want to use geom_col() instead of geom_bar() to create bar charts where the bars have the specific height provided in the y-variable.

+
+
createOrderedBars <- function(variable_name) {
+  demographics |> 
+    # group by the column provided
+    group_by({{ variable_name }}) |>
+    # compute the mean age
+    summarize(mean_age = mean(age_years)) |>
+    # create the bar plot
+    ggplot() +
+    geom_col(aes(x = {{ variable_name }}, 
+                 y = mean_age))
+}
+
+
+
createOrderedBars(marital_status)
+
+
+
+

+
+
+
+
+
+
+

Challenge solution

+

To arrange the bars in ascending order of mean_age, you first need to convert the categorical variable itself to a factor whose levels are in the order that you want the bars to appear. You can do this by arranging the rows of your data frame in order of mean_age and then using fct_inorder() to convert your variable to a factor with levels match the increasing order of mean_age.

+
+
createOrderedBars <- function(variable_name, ascending = TRUE) {  
+  mean_age <- demographics |> 
+    # group by the column provided
+    group_by({{ variable_name }}) |>
+    # compute the mean age
+    summarize(mean_age = mean(age_years))
+  
+  if (ascending) {
+    mean_age <- mean_age |>
+      # arrange in increasing order of mean_age 
+      arrange(mean_age) |>
+      # modify selected_variable so that it is a factor whose levels are in 
+      # increasing order of mean_age  
+      mutate(selected_variable = fct_inorder({{ variable_name }})) 
+  } else {
+    mean_age <- mean_age |>
+      mutate(selected_variable = {{ variable_name }}) 
+  }
+  
+  # create the bar plot
+  mean_age |>
+    ggplot() +
+    geom_col(aes(x = selected_variable, 
+                 y = mean_age))
+}
+
+
+
createOrderedBars(marital_status, ascending = TRUE)
+
+
+
+

+
+
+
+
createOrderedBars(marital_status, ascending = FALSE)
+
+
+
+

+
+
+
+
createOrderedBars(marital_status)
+
+
+
+

+
+
+
+
+ + +
+
+
+ +
+ +
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zTsri-BY$6)+2{IuxmjeOu-pIMGWU4UD`Vs&lD}_GjE& + + + + + + + + +Iteration with purrr – Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +

    +
    + +
    + +
    + + + + +
    + +
    +
    +

    Iteration with purrr

    +
    + + + +
    + + + + +
    + + + +
    + + +

    The purpose of this lesson is to learn how to iteratively apply functions to all elements contained within an object, such as all columns in a data frame, or all entries in a vector.

    +

    The “purrr” R package that we will be using in this lesson is included in the tidyverse package.

    +
    +
    # load the tidyverse and demographics dataset
+library(tidyverse)
    +
    +
    ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
+✔ dplyr     1.1.4     ✔ readr     2.1.5
+✔ forcats   1.0.0     ✔ stringr   1.5.1
+✔ ggplot2   3.5.1     ✔ tibble    3.2.1
+✔ lubridate 1.9.3     ✔ tidyr     1.3.1
+✔ purrr     1.0.2     
+── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
+✖ dplyr::filter() masks stats::filter()
+✖ dplyr::lag()    masks stats::lag()
+ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
    +
    +
    demographics <- read_csv("data/demographics.csv")
    +
    +
    Rows: 10175 Columns: 19
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (5): interview_examination, gender, race, marital_status, pregnant
+dbl (9): respondent_id, age_years, age_months_sc_0_2yr, six_month_period, ag...
+lgl (5): served_active_duty_us, served_active_duty_foreign, born_usa, citize...
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
    +
    +

    The function that we want to iterate first is the n_distinct() function from the tidyverse.

    +

    Recall that to pull up the help page for a function, you can use the following syntax:

    +
    +
    # pull up the help page for n_distinct
+?n_distinct
    +
    +

    n_distinct() counts the number of unique values in a vector.

    +
    +
    # apply n_distinct to the "gender" column of demographics
+n_distinct(demographics$gender)
    +
    +
    [1] 2
    +
    +
    +

    The code below uses the map() function to apply n_distinct() to every column of the demographics data frame simultaneously:

    +
    +
    # use map() to apply n_distinct to every column of demographics
+map(demographics, n_distinct)
    +
    +
    $respondent_id
+[1] 10175
+
+$interview_examination
+[1] 2
+
+$gender
+[1] 2
+
+$age_years
+[1] 81
+
+$age_months_sc_0_2yr
+[1] 26
+
+$race
+[1] 6
+
+$six_month_period
+[1] 3
+
+$age_months_ex_0_19yr
+[1] 241
+
+$served_active_duty_us
+[1] 3
+
+$served_active_duty_foreign
+[1] 3
+
+$born_usa
+[1] 3
+
+$citizen_usa
+[1] 3
+
+$time_in_us
+[1] 10
+
+$education_youth
+[1] 16
+
+$education
+[1] 6
+
+$marital_status
+[1] 7
+
+$pregnant
+[1] 4
+
+$language_english
+[1] 2
+
+$household_income
+[1] 13
    +
    +
    +

    The output of the map() function is a list (more on that in a moment).

    +

    The following code shows a simpler example, this time applying the exp() function to all entries/elements in a simple numeric vector:

    +
    +
    # use map() to apply exp() to the vector c(4, 5, 6)
+map(c(4, 5, 6), exp)
    +
    +
    [[1]]
+[1] 54.59815
+
+[[2]]
+[1] 148.4132
+
+[[3]]
+[1] 403.4288
    +
    +
    +
    +

    Lists

    +

    Lists, like vectors, correspond to a collection of values contained in a single object.

    +

    You can use the list() function to define a list, for example:

    +
    +
    # define a list called my_list with three elements: 1, 4, and 7
+my_list <- list(1, 4, 7)
    +
    +

    You can extract elements from a list just as you would from a vector, using the square bracket notation. The code below extracts the third element from my_list:

    +
    +
    # extract the third entry from my_list using []
+my_list[3]
    +
    +
    [[1]]
+[1] 7
    +
    +
    # ask the class of the object above
+class(my_list[3])
    +
    +
    [1] "list"
    +
    +
    +

    However, the output above is a list itself.

    +

    If you want to extract the actual object/value contained within the third element of the list, then you need to use double square parentheses:

    +
    +
    # extract the third entry from my_list using [[]]
+my_list[[3]]
    +
    +
    [1] 7
    +
    +
    +

    Unlike vectors, lists are not vectorized.

    +
    +
    # try to add 1 to my_list
+my_list + 1
    +
    +
    Error in my_list + 1: non-numeric argument to binary operator
    +
    +
    +

    Why would we ever prefer lists to vectors? The reason is that lists are infinitely more flexible than vectors. While all entries in a vector must be a single value of the same type, entries of a list can be anything.

    +
    +
    # create a list my_complex_list containing 
+# (1) the head of demographics, 
+# (2) the value 2, and 
+# (3) a vector containing "a" and "b"
+my_complex_list <- list(head(demographics), 2, c("a", "b"))
+my_complex_list
    +
    +
    [[1]]
+# A tibble: 6 × 19
+  respondent_id interview_examination gender age_years age_months_sc_0_2yr race 
+          <dbl> <chr>                 <chr>      <dbl>               <dbl> <chr>
+1         73557 both interview and e… male          69                  NA black
+2         73558 both interview and e… male          54                  NA white
+3         73559 both interview and e… male          72                  NA white
+4         73560 both interview and e… male           9                  NA white
+5         73561 both interview and e… female        73                  NA white
+6         73562 both interview and e… male          56                  NA mexi…
+# ℹ 13 more variables: six_month_period <dbl>, age_months_ex_0_19yr <dbl>,
+#   served_active_duty_us <lgl>, served_active_duty_foreign <lgl>,
+#   born_usa <lgl>, citizen_usa <lgl>, time_in_us <dbl>, education_youth <dbl>,
+#   education <dbl>, marital_status <chr>, pregnant <chr>,
+#   language_english <lgl>, household_income <dbl>
+
+[[2]]
+[1] 2
+
+[[3]]
+[1] "a" "b"
    +
    +
    +

    You can also create a named list when defining it as if you are defining argument names:

    +
    +
    # create a named version of my_complex_list
+my_complex_list <- list(data = head(demographics), 
+                        value = 2, 
+                        vector = c("a", "b"))
+my_complex_list
    +
    +
    $data
+# A tibble: 6 × 19
+  respondent_id interview_examination gender age_years age_months_sc_0_2yr race 
+          <dbl> <chr>                 <chr>      <dbl>               <dbl> <chr>
+1         73557 both interview and e… male          69                  NA black
+2         73558 both interview and e… male          54                  NA white
+3         73559 both interview and e… male          72                  NA white
+4         73560 both interview and e… male           9                  NA white
+5         73561 both interview and e… female        73                  NA white
+6         73562 both interview and e… male          56                  NA mexi…
+# ℹ 13 more variables: six_month_period <dbl>, age_months_ex_0_19yr <dbl>,
+#   served_active_duty_us <lgl>, served_active_duty_foreign <lgl>,
+#   born_usa <lgl>, citizen_usa <lgl>, time_in_us <dbl>, education_youth <dbl>,
+#   education <dbl>, marital_status <chr>, pregnant <chr>,
+#   language_english <lgl>, household_income <dbl>
+
+$value
+[1] 2
+
+$vector
+[1] "a" "b"
    +
    +
    +

    You can then extract entries from the named list using $ or [[]]

    +
    +
    # extract one of the elements from my_complex_list using $
+my_complex_list$data
    +
    +
    # A tibble: 6 × 19
+  respondent_id interview_examination gender age_years age_months_sc_0_2yr race 
+          <dbl> <chr>                 <chr>      <dbl>               <dbl> <chr>
+1         73557 both interview and e… male          69                  NA black
+2         73558 both interview and e… male          54                  NA white
+3         73559 both interview and e… male          72                  NA white
+4         73560 both interview and e… male           9                  NA white
+5         73561 both interview and e… female        73                  NA white
+6         73562 both interview and e… male          56                  NA mexi…
+# ℹ 13 more variables: six_month_period <dbl>, age_months_ex_0_19yr <dbl>,
+#   served_active_duty_us <lgl>, served_active_duty_foreign <lgl>,
+#   born_usa <lgl>, citizen_usa <lgl>, time_in_us <dbl>, education_youth <dbl>,
+#   education <dbl>, marital_status <chr>, pregnant <chr>,
+#   language_english <lgl>, household_income <dbl>
    +
    +
    # extract one of the elements from my_complex_list using [[]]
+my_complex_list[["data"]]
    +
    +
    # A tibble: 6 × 19
+  respondent_id interview_examination gender age_years age_months_sc_0_2yr race 
+          <dbl> <chr>                 <chr>      <dbl>               <dbl> <chr>
+1         73557 both interview and e… male          69                  NA black
+2         73558 both interview and e… male          54                  NA white
+3         73559 both interview and e… male          72                  NA white
+4         73560 both interview and e… male           9                  NA white
+5         73561 both interview and e… female        73                  NA white
+6         73562 both interview and e… male          56                  NA mexi…
+# ℹ 13 more variables: six_month_period <dbl>, age_months_ex_0_19yr <dbl>,
+#   served_active_duty_us <lgl>, served_active_duty_foreign <lgl>,
+#   born_usa <lgl>, citizen_usa <lgl>, time_in_us <dbl>, education_youth <dbl>,
+#   education <dbl>, marital_status <chr>, pregnant <chr>,
+#   language_english <lgl>, household_income <dbl>
    +
    +
    +
    +
    +

    Exercise

    +

    Use map() to apply class() to every column in the demographics dataset, and extract the class of the household_income column.

    +
    +

    Solution

    +
    +
    demographics_class <- map(demographics, class)
    +
    +
    +
    demographics_class$household_income
    +
    +
    [1] "numeric"
    +
    +
    demographics_class[[ncol(demographics)]]
    +
    +
    [1] "numeric"
    +
    +
    demographics_class[["household_income"]]
    +
    +
    [1] "numeric"
    +
    +
    +
    +
    +
    +

    Using custom functions in purrr

    +

    To iterate using your own custom functions in a purrr map() function, you can define your function and provide it in the second argument of map().

    +
    +
    # define a function called exp_plus_one() that returns exp(x) + 1
+exp_plus_one <- function(x) {
+  return(exp(x) + 1)
+}
+
+# apply it to every entry in the vector c(1, 4, 5)
+map(c(1, 4, 5), exp_plus_one)
    +
    +
    [[1]]
+[1] 3.718282
+
+[[2]]
+[1] 55.59815
+
+[[3]]
+[1] 149.4132
    +
    +
    +

    For simple functions like this, we can define the function inside the map() function itself:

    +
    +
    # apply the function exp(x) + 1 to every entry in the vector c(1, 4, 5)
+# using an "anonymous" function
+map(c(1, 4, 5), function(x) exp(x) + 1)
    +
    +
    [[1]]
+[1] 3.718282
+
+[[2]]
+[1] 55.59815
+
+[[3]]
+[1] 149.4132
    +
    +
    +

    However, we can go one step further and forego the function(x) part entirely using what I call the “tilde-dot” shorthand syntax.

    +

    Here, we use the tilde ~ symbol to “start” an anonymous function and we use a . to represent the argument of our anonymous function.

    +
    +
    # apply the function exp(x) + 1 to every entry in the vector c(1, 4, 5)
+# using the "tilde-dot" syntax
+map(c(1, 4, 5), ~{exp(.) + 1})
    +
    +
    [[1]]
+[1] 3.718282
+
+[[2]]
+[1] 55.59815
+
+[[3]]
+[1] 149.4132
    +
    +
    +

    To decide what should go inside the ~{}, I typically use a representative value to test out my code first.

    +

    Let’s count the number of missing values in each column of demographics.

    +

    For example, below, I take a single column demographics$pregnant, and I write out the code that I want to apply to it:

    +
    +
    # compute the number of missing values in the "pregnant" column of demographics
+sum(is.na(demographics$pregnant))
    +
    +
    [1] 8866
    +
    +
    +

    Generalize this code for the map function:

    +
    +
    # use a map function to compute the number of missing values in every column
+map(demographics, ~{sum(is.na(.))})
    +
    +
    $respondent_id
+[1] 0
+
+$interview_examination
+[1] 0
+
+$gender
+[1] 0
+
+$age_years
+[1] 0
+
+$age_months_sc_0_2yr
+[1] 9502
+
+$race
+[1] 0
+
+$six_month_period
+[1] 362
+
+$age_months_ex_0_19yr
+[1] 5962
+
+$served_active_duty_us
+[1] 3915
+
+$served_active_duty_foreign
+[1] 9633
+
+$born_usa
+[1] 5
+
+$citizen_usa
+[1] 11
+
+$time_in_us
+[1] 8353
+
+$education_youth
+[1] 7373
+
+$education
+[1] 4413
+
+$marital_status
+[1] 4409
+
+$pregnant
+[1] 8866
+
+$language_english
+[1] 0
+
+$household_income
+[1] 783
    +
    +
    +
    +

    Exercise

    +

    Use the tilde-dot short-hand syntax to compute the number of values in each column that is equal to 1. Recall that if a vector has missing values, and you want to use sum(), you will want to provide an argument na.rm = TRUE to ignore missing values.

    +
    +

    Solution

    +

    First, the code below does the long-form version which defines a function and then provides that function in the second argument of the map() function:

    +
    +
    add_ones <- function(x) {
+  sum(x == 1, na.rm = TRUE)
+}
+
+map(demographics, add_ones)
    +
    +
    $respondent_id
+[1] 0
+
+$interview_examination
+[1] 0
+
+$gender
+[1] 0
+
+$age_years
+[1] 262
+
+$age_months_sc_0_2yr
+[1] 42
+
+$race
+[1] 0
+
+$six_month_period
+[1] 4823
+
+$age_months_ex_0_19yr
+[1] 30
+
+$served_active_duty_us
+[1] 543
+
+$served_active_duty_foreign
+[1] 282
+
+$born_usa
+[1] 8262
+
+$citizen_usa
+[1] 9220
+
+$time_in_us
+[1] 0
+
+$education_youth
+[1] 237
+
+$education
+[1] 455
+
+$marital_status
+[1] 0
+
+$pregnant
+[1] 0
+
+$language_english
+[1] 9100
+
+$household_income
+[1] 0
    +
    +
    +

    Then I make this more concise by taking the body of my add_ones() function above, and placing it inside ~{}, and replace the x argument with a .:

    +
    +
    map(demographics, ~{sum(. == 1, na.rm = TRUE)})
    +
    +
    $respondent_id
+[1] 0
+
+$interview_examination
+[1] 0
+
+$gender
+[1] 0
+
+$age_years
+[1] 262
+
+$age_months_sc_0_2yr
+[1] 42
+
+$race
+[1] 0
+
+$six_month_period
+[1] 4823
+
+$age_months_ex_0_19yr
+[1] 30
+
+$served_active_duty_us
+[1] 543
+
+$served_active_duty_foreign
+[1] 282
+
+$born_usa
+[1] 8262
+
+$citizen_usa
+[1] 9220
+
+$time_in_us
+[1] 0
+
+$education_youth
+[1] 237
+
+$education
+[1] 455
+
+$marital_status
+[1] 0
+
+$pregnant
+[1] 0
+
+$language_english
+[1] 9100
+
+$household_income
+[1] 0
    +
    +
    +
    +
    +
    +
    +

    Alternative map functions for outputting doubles, characters and data frames

    +

    Recall our map() function previously that we used to count the number of missing values in each column of the demographics data.

    +
    +
    map(demographics, ~sum(is.na(.)))
    +
    +
    $respondent_id
+[1] 0
+
+$interview_examination
+[1] 0
+
+$gender
+[1] 0
+
+$age_years
+[1] 0
+
+$age_months_sc_0_2yr
+[1] 9502
+
+$race
+[1] 0
+
+$six_month_period
+[1] 362
+
+$age_months_ex_0_19yr
+[1] 5962
+
+$served_active_duty_us
+[1] 3915
+
+$served_active_duty_foreign
+[1] 9633
+
+$born_usa
+[1] 5
+
+$citizen_usa
+[1] 11
+
+$time_in_us
+[1] 8353
+
+$education_youth
+[1] 7373
+
+$education
+[1] 4413
+
+$marital_status
+[1] 4409
+
+$pregnant
+[1] 8866
+
+$language_english
+[1] 0
+
+$household_income
+[1] 783
    +
    +
    +

    A list may not be the most useful format for this information…

    +
    +

    Outputting numeric vectors

    +

    The map_dbl() function will output a “double” (numeric) vector.

    +
    +
    # use map_dbl to count the number of missing values in each column and
+# output a numeric vector
+map_dbl(demographics, ~sum(is.na(.)))
    +
    +
                 respondent_id      interview_examination 
+                         0                          0 
+                    gender                  age_years 
+                         0                          0 
+       age_months_sc_0_2yr                       race 
+                      9502                          0 
+          six_month_period       age_months_ex_0_19yr 
+                       362                       5962 
+     served_active_duty_us served_active_duty_foreign 
+                      3915                       9633 
+                  born_usa                citizen_usa 
+                         5                         11 
+                time_in_us            education_youth 
+                      8353                       7373 
+                 education             marital_status 
+                      4413                       4409 
+                  pregnant           language_english 
+                      8866                          0 
+          household_income 
+                       783
    +
    +
    +
    +
    +

    Outputting character vectors

    +

    The map_chr() function can output a character vector.

    +
    +
    # use map_chr to apply class to every column and output a character vector
+map_chr(demographics, class)
    +
    +
                 respondent_id      interview_examination 
+                 "numeric"                "character" 
+                    gender                  age_years 
+               "character"                  "numeric" 
+       age_months_sc_0_2yr                       race 
+                 "numeric"                "character" 
+          six_month_period       age_months_ex_0_19yr 
+                 "numeric"                  "numeric" 
+     served_active_duty_us served_active_duty_foreign 
+                 "logical"                  "logical" 
+                  born_usa                citizen_usa 
+                 "logical"                  "logical" 
+                time_in_us            education_youth 
+                 "numeric"                  "numeric" 
+                 education             marital_status 
+                 "numeric"                "character" 
+                  pregnant           language_english 
+               "character"                  "logical" 
+          household_income 
+                 "numeric"
    +
    +
    +
    +
    +

    Outputting data frames

    +

    One of the most versatile functions is the map_df() function, which outputs a data frame.

    +
    +
    # apply map_df to demographics to determine the class of each column, outputting a "wide" data frame
+map_df(demographics, class)
    +
    +
    # A tibble: 1 × 19
+  respondent_id interview_examination gender age_years age_months_sc_0_2yr race 
+  <chr>         <chr>                 <chr>  <chr>     <chr>               <chr>
+1 numeric       character             chara… numeric   numeric             char…
+# ℹ 13 more variables: six_month_period <chr>, age_months_ex_0_19yr <chr>,
+#   served_active_duty_us <chr>, served_active_duty_foreign <chr>,
+#   born_usa <chr>, citizen_usa <chr>, time_in_us <chr>, education_youth <chr>,
+#   education <chr>, marital_status <chr>, pregnant <chr>,
+#   language_english <chr>, household_income <chr>
    +
    +
    +

    If you want your output to be in a “long” format, the function you are applying must output a single-column tibble/data frame.

    +
    +
    # use tibble() to create a single-column tibble containing the class of demographics$pregnant
+tibble(col_class = class(demographics$pregnant))
    +
    +
    # A tibble: 1 × 1
+  col_class
+  <chr>    
+1 character
    +
    +
    # modify this code to be the function call in map_df to create a 
+# long-form data frame
+map_df(demographics, ~tibble(col_class = class(.)))
    +
    +
    # A tibble: 19 × 1
+   col_class
+   <chr>    
+ 1 numeric  
+ 2 character
+ 3 character
+ 4 numeric  
+ 5 numeric  
+ 6 character
+ 7 numeric  
+ 8 numeric  
+ 9 logical  
+10 logical  
+11 logical  
+12 logical  
+13 numeric  
+14 numeric  
+15 numeric  
+16 character
+17 character
+18 logical  
+19 numeric
    +
    +
    # provide an .id argument to include the original column names as a variable
+map_df(demographics, ~tibble(col_class = class(.)), .id = "variable_name")
    +
    +
    # A tibble: 19 × 2
+   variable_name              col_class
+   <chr>                      <chr>    
+ 1 respondent_id              numeric  
+ 2 interview_examination      character
+ 3 gender                     character
+ 4 age_years                  numeric  
+ 5 age_months_sc_0_2yr        numeric  
+ 6 race                       character
+ 7 six_month_period           numeric  
+ 8 age_months_ex_0_19yr       numeric  
+ 9 served_active_duty_us      logical  
+10 served_active_duty_foreign logical  
+11 born_usa                   logical  
+12 citizen_usa                logical  
+13 time_in_us                 numeric  
+14 education_youth            numeric  
+15 education                  numeric  
+16 marital_status             character
+17 pregnant                   character
+18 language_english           logical  
+19 household_income           numeric
    +
    +
    +
    +
    +

    Example

    +

    This long-format is very useful if you want to create a plot, such as a bar chart for the number of missing values.

    +
    +
    # create a bar chart of the number of missing values in each column
+# use factors to order the columns by the number of missing values
+map_df(demographics, 
+       ~tibble(n_missing = sum(is.na(.))), 
+       .id = "variable_name") |>
+  arrange(n_missing) |>
+  mutate(variable_name = fct_inorder(variable_name)) |>
+  ggplot() +
+  geom_col(aes(x = variable_name, y = n_missing)) +
+  scale_y_continuous(expand = c(0, 0)) +
+  theme_classic() +
+  theme(axis.text.x = element_text(angle = 90, 
+                                   hjust = 1,
+                                   vjust = 0.5))
    +
    +
    +
    +

    +
    +
    +
    +
    +

    An alternative approach is to use map_dbl() and enframe()

    +
    +
    # use map_dbl() and enframe() to create a long data frame of the 
+# number of missing values in each column
+map_dbl(demographics, ~sum(is.na(.))) |>
+  enframe()
    +
    +
    # A tibble: 19 × 2
+   name                       value
+   <chr>                      <dbl>
+ 1 respondent_id                  0
+ 2 interview_examination          0
+ 3 gender                         0
+ 4 age_years                      0
+ 5 age_months_sc_0_2yr         9502
+ 6 race                           0
+ 7 six_month_period             362
+ 8 age_months_ex_0_19yr        5962
+ 9 served_active_duty_us       3915
+10 served_active_duty_foreign  9633
+11 born_usa                       5
+12 citizen_usa                   11
+13 time_in_us                  8353
+14 education_youth             7373
+15 education                   4413
+16 marital_status              4409
+17 pregnant                    8866
+18 language_english               0
+19 household_income             783
    +
    +
    + + +
    +
    + +
    + +
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    +

    Across

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    In this lesson, we will introduce the across() function, which can be used to apply dplyr functions like mutate, summarize, select, etc to subsets of columns that satisfy certain criteria, such as to all numeric columns, or all columns that start with age_.

    +
    +
    # load the tidyverse and demographics dataset
+library(tidyverse)
    +
    +
    ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
+✔ dplyr     1.1.4     ✔ readr     2.1.5
+✔ forcats   1.0.0     ✔ stringr   1.5.1
+✔ ggplot2   3.5.1     ✔ tibble    3.2.1
+✔ lubridate 1.9.3     ✔ tidyr     1.3.1
+✔ purrr     1.0.2     
+── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
+✖ dplyr::filter() masks stats::filter()
+✖ dplyr::lag()    masks stats::lag()
+ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
    +
    +
    demographics <- read_csv("data/demographics.csv")
    +
    +
    Rows: 10175 Columns: 19
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (5): interview_examination, gender, race, marital_status, pregnant
+dbl (9): respondent_id, age_years, age_months_sc_0_2yr, six_month_period, ag...
+lgl (5): served_active_duty_us, served_active_duty_foreign, born_usa, citize...
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
    +
    head(demographics)
    +
    +
    # A tibble: 6 × 19
+  respondent_id interview_examination gender age_years age_months_sc_0_2yr race 
+          <dbl> <chr>                 <chr>      <dbl>               <dbl> <chr>
+1         73557 both interview and e… male          69                  NA black
+2         73558 both interview and e… male          54                  NA white
+3         73559 both interview and e… male          72                  NA white
+4         73560 both interview and e… male           9                  NA white
+5         73561 both interview and e… female        73                  NA white
+6         73562 both interview and e… male          56                  NA mexi…
+# ℹ 13 more variables: six_month_period <dbl>, age_months_ex_0_19yr <dbl>,
+#   served_active_duty_us <lgl>, served_active_duty_foreign <lgl>,
+#   born_usa <lgl>, citizen_usa <lgl>, time_in_us <dbl>, education_youth <dbl>,
+#   education <dbl>, marital_status <chr>, pregnant <chr>,
+#   language_english <lgl>, household_income <dbl>
    +
    +
    +

    Let’s suppose that our task is to convert all character columns of the demographics data to upper-case.

    +
    +
    # apply toupper() to the string value "abc"
+toupper("abc")
    +
    +
    [1] "ABC"
    +
    +
    +

    Before introducing across, let’s first see one way that we could do this using the map() functions that we have just learned:

    +
    +
    # create a copy of demographics
+demographics_tmp <- demographics
+# create a logical vector for identifying character columns using map_chr()
+character_cols <- map_chr(demographics_tmp, class) == "character"
+# re-assign the character columns to an upper-case version of themselves 
+# using map_df() applied to demographics_tmp[character_cols] with toupper()
+demographics_tmp[character_cols] <- map_df(demographics_tmp[character_cols], toupper)
+
+# look at demographics_tmp
+demographics_tmp
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 BOTH INTERVIEW AND EXAM MALE          69                  NA
+ 2         73558 BOTH INTERVIEW AND EXAM MALE          54                  NA
+ 3         73559 BOTH INTERVIEW AND EXAM MALE          72                  NA
+ 4         73560 BOTH INTERVIEW AND EXAM MALE           9                  NA
+ 5         73561 BOTH INTERVIEW AND EXAM FEMALE        73                  NA
+ 6         73562 BOTH INTERVIEW AND EXAM MALE          56                  NA
+ 7         73563 BOTH INTERVIEW AND EXAM MALE           0                   5
+ 8         73564 BOTH INTERVIEW AND EXAM FEMALE        61                  NA
+ 9         73565 INTERVIEW ONLY          MALE          42                  NA
+10         73566 BOTH INTERVIEW AND EXAM FEMALE        56                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    # look at demographics (it should still have lowercase)
+demographics
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +

    While this works, it is fairly convoluted, is hard to read, and involves defining an intermediate variable (character_cols) – in the tidyverse style, it is generally recommended to avoid defining intermediate variables whenever possible.

    +
    +

    Introducing across()

    +

    We could instead do this kind of operation using a mutate() operation in conjunction with across().

    +

    Let’s figure out the code for just one column first

    +
    +
    # apply toupper to interview_examination with mutate
+demographics |> mutate(interview_examination = toupper(interview_examination))
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 BOTH INTERVIEW AND EXAM male          69                  NA
+ 2         73558 BOTH INTERVIEW AND EXAM male          54                  NA
+ 3         73559 BOTH INTERVIEW AND EXAM male          72                  NA
+ 4         73560 BOTH INTERVIEW AND EXAM male           9                  NA
+ 5         73561 BOTH INTERVIEW AND EXAM female        73                  NA
+ 6         73562 BOTH INTERVIEW AND EXAM male          56                  NA
+ 7         73563 BOTH INTERVIEW AND EXAM male           0                   5
+ 8         73564 BOTH INTERVIEW AND EXAM female        61                  NA
+ 9         73565 INTERVIEW ONLY          male          42                  NA
+10         73566 BOTH INTERVIEW AND EXAM female        56                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +

    To do this for all character columns, you need to provide across() to the argument of your mutate function. The across() function has two arguments:

    +
      +

    • The first argument is a “select statement” that specifies which columns you want to apply your function to.

      • +

    • The second argument is the function name, toupper, that we want to apply to all columns that are selected as a result of the first argument.

      • +
    +

    The result is that toupper() is applied to all columns “where” is.character() would result in TRUE:

    +
    +
    # use across inside mutate to apply toupper() to all columns 
+# where(is.character) is TRUE...
+demographics |> mutate(across(where(is.character), toupper))
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 BOTH INTERVIEW AND EXAM MALE          69                  NA
+ 2         73558 BOTH INTERVIEW AND EXAM MALE          54                  NA
+ 3         73559 BOTH INTERVIEW AND EXAM MALE          72                  NA
+ 4         73560 BOTH INTERVIEW AND EXAM MALE           9                  NA
+ 5         73561 BOTH INTERVIEW AND EXAM FEMALE        73                  NA
+ 6         73562 BOTH INTERVIEW AND EXAM MALE          56                  NA
+ 7         73563 BOTH INTERVIEW AND EXAM MALE           0                   5
+ 8         73564 BOTH INTERVIEW AND EXAM FEMALE        61                  NA
+ 9         73565 INTERVIEW ONLY          MALE          42                  NA
+10         73566 BOTH INTERVIEW AND EXAM FEMALE        56                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +
    +
    +

    More across examples

    +
    +

    Add 100 to all age_ columns

    +

    If we were to do this to just the age_years column, our code would look like:

    +
    +
    # use mutate to add 100 to age_years
+demographics |> mutate(age_years = age_years + 100)
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male         169                  NA
+ 2         73558 both interview and exam male         154                  NA
+ 3         73559 both interview and exam male         172                  NA
+ 4         73560 both interview and exam male         109                  NA
+ 5         73561 both interview and exam female       173                  NA
+ 6         73562 both interview and exam male         156                  NA
+ 7         73563 both interview and exam male         100                   5
+ 8         73564 both interview and exam female       161                  NA
+ 9         73565 interview only          male         142                  NA
+10         73566 both interview and exam female       156                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +

    To generalize this to all columns that start with age_ using across(), we can use the starts_with() select helper, and apply the anonymous function ~{. + 100}:

    +
    +
    # use across inside mutate to apply ~{. + 100} to all columns 
+# that starts_with("age_")...
+demographics |> mutate(across(starts_with("age_"), ~{. + 100}))
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male         169                  NA
+ 2         73558 both interview and exam male         154                  NA
+ 3         73559 both interview and exam male         172                  NA
+ 4         73560 both interview and exam male         109                  NA
+ 5         73561 both interview and exam female       173                  NA
+ 6         73562 both interview and exam male         156                  NA
+ 7         73563 both interview and exam male         100                 105
+ 8         73564 both interview and exam female       161                  NA
+ 9         73565 interview only          male         142                  NA
+10         73566 both interview and exam female       156                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +
    +
    +

    Convert born_usa and citizen_usa to numeric (binary) columns using ends_with()

    +
    +
    # take a look at born_usa and citizen_use using select()
+demographics |> select(born_usa, citizen_usa)
    +
    +
    # A tibble: 10,175 × 2
+   born_usa citizen_usa
+   <lgl>    <lgl>      
+ 1 TRUE     TRUE       
+ 2 TRUE     TRUE       
+ 3 TRUE     TRUE       
+ 4 TRUE     TRUE       
+ 5 TRUE     TRUE       
+ 6 TRUE     TRUE       
+ 7 TRUE     TRUE       
+ 8 TRUE     TRUE       
+ 9 TRUE     TRUE       
+10 TRUE     TRUE       
+# ℹ 10,165 more rows
    +
    +
    +
    +
    # use across inside mutate to apply as.numeric to all columns 
+# that ends_with("_usa")...
+demographics |> mutate(across(ends_with("_usa"), as.numeric)) |> 
+  print(width = Inf)
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+   race             six_month_period age_months_ex_0_19yr served_active_duty_us
+   <chr>                       <dbl>                <dbl> <lgl>                
+ 1 black                           1                   NA TRUE                 
+ 2 white                           1                   NA FALSE                
+ 3 white                           2                   NA TRUE                 
+ 4 white                           1                  119 NA                   
+ 5 white                           1                   NA FALSE                
+ 6 mexican american                1                   NA TRUE                 
+ 7 white                           2                    6 NA                   
+ 8 white                           2                   NA FALSE                
+ 9 other hispanic                 NA                   NA FALSE                
+10 white                           1                   NA FALSE                
+   served_active_duty_foreign born_usa citizen_usa time_in_us education_youth
+   <lgl>                         <dbl>       <dbl>      <dbl>           <dbl>
+ 1 TRUE                              1           1         NA              NA
+ 2 NA                                1           1         NA              NA
+ 3 TRUE                              1           1         NA              NA
+ 4 NA                                1           1         NA               3
+ 5 NA                                1           1         NA              NA
+ 6 FALSE                             1           1         NA              NA
+ 7 NA                                1           1         NA              NA
+ 8 NA                                1           1         NA              NA
+ 9 NA                                1           1         NA              NA
+10 NA                                1           1         NA              NA
+   education marital_status pregnant language_english household_income
+       <dbl> <chr>          <chr>    <lgl>                       <dbl>
+ 1         3 separated      <NA>     TRUE                        17500
+ 2         3 married        <NA>     TRUE                        40000
+ 3         4 married        <NA>     TRUE                        70000
+ 4        NA <NA>           <NA>     TRUE                        60000
+ 5         5 married        <NA>     TRUE                       100000
+ 6         4 divorced       <NA>     TRUE                        60000
+ 7        NA <NA>           <NA>     TRUE                       100000
+ 8         5 widowed        <NA>     TRUE                        70000
+ 9         3 married        <NA>     TRUE                       100000
+10         3 divorced       <NA>     TRUE                        17500
+# ℹ 10,165 more rows
    +
    +
    +
    +
    +

    Convert born_usa and citizen_usa to numeric (binary) columns using a vector of column names

    +

    Suppose we had a vector of column names that we wanted to modify using mutate():

    +
    +
    # define a vector selected_columns with "born_usa" and "citizen_usa"
+selected_cols <- c("born_usa", "citizen_usa")
    +
    +

    Then we could use all_of(selected_cols) in across() to apply the function to all columns listed in the selected_cols vector as follows:

    +
    +
    # use across inside mutate to apply as.numeric to all_of(selected_columns)
+demographics |> mutate(across(all_of(selected_cols), as.numeric)) |>
+  print(width = Inf)
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+   race             six_month_period age_months_ex_0_19yr served_active_duty_us
+   <chr>                       <dbl>                <dbl> <lgl>                
+ 1 black                           1                   NA TRUE                 
+ 2 white                           1                   NA FALSE                
+ 3 white                           2                   NA TRUE                 
+ 4 white                           1                  119 NA                   
+ 5 white                           1                   NA FALSE                
+ 6 mexican american                1                   NA TRUE                 
+ 7 white                           2                    6 NA                   
+ 8 white                           2                   NA FALSE                
+ 9 other hispanic                 NA                   NA FALSE                
+10 white                           1                   NA FALSE                
+   served_active_duty_foreign born_usa citizen_usa time_in_us education_youth
+   <lgl>                         <dbl>       <dbl>      <dbl>           <dbl>
+ 1 TRUE                              1           1         NA              NA
+ 2 NA                                1           1         NA              NA
+ 3 TRUE                              1           1         NA              NA
+ 4 NA                                1           1         NA               3
+ 5 NA                                1           1         NA              NA
+ 6 FALSE                             1           1         NA              NA
+ 7 NA                                1           1         NA              NA
+ 8 NA                                1           1         NA              NA
+ 9 NA                                1           1         NA              NA
+10 NA                                1           1         NA              NA
+   education marital_status pregnant language_english household_income
+       <dbl> <chr>          <chr>    <lgl>                       <dbl>
+ 1         3 separated      <NA>     TRUE                        17500
+ 2         3 married        <NA>     TRUE                        40000
+ 3         4 married        <NA>     TRUE                        70000
+ 4        NA <NA>           <NA>     TRUE                        60000
+ 5         5 married        <NA>     TRUE                       100000
+ 6         4 divorced       <NA>     TRUE                        60000
+ 7        NA <NA>           <NA>     TRUE                       100000
+ 8         5 widowed        <NA>     TRUE                        70000
+ 9         3 married        <NA>     TRUE                       100000
+10         3 divorced       <NA>     TRUE                        17500
+# ℹ 10,165 more rows
    +
    +
    +
    +
    +
    +

    Select helpers summary

    +

    So far we have seen the following “select helpers” that can be used to specify the columns inside across():

    +
      +

    • where() – across to all columns that satisfy a logical condition (across(where(is.character), fun))

      • +

    • starts_with() and ends_with() – across all columns that start or ends with a specified string (across(starts_with("abc"), fun))

      • +

    • contains() – across all columns that contain a specified string (across(contains("abc"), fun))

      • +

    • all_of() and any_of() – across all columns whose names are contained in a character vector, where all_of() requires all columns in the vector be present. (across(all_of(vec_names), fun))

      • +

    • everything() – across all columns

      • +
    +

    These can also be used within select()

    +
    +
    # select all columns that contain "age"
+demographics |> select(contains("age"))
    +
    +
    # A tibble: 10,175 × 4
+   age_years age_months_sc_0_2yr age_months_ex_0_19yr language_english
+       <dbl>               <dbl>                <dbl> <lgl>           
+ 1        69                  NA                   NA TRUE            
+ 2        54                  NA                   NA TRUE            
+ 3        72                  NA                   NA TRUE            
+ 4         9                  NA                  119 TRUE            
+ 5        73                  NA                   NA TRUE            
+ 6        56                  NA                   NA TRUE            
+ 7         0                   5                    6 TRUE            
+ 8        61                  NA                   NA TRUE            
+ 9        42                  NA                   NA TRUE            
+10        56                  NA                   NA TRUE            
+# ℹ 10,165 more rows
    +
    +
    # select all columns that start with "age"
+demographics |> select(starts_with("age"))
    +
    +
    # A tibble: 10,175 × 3
+   age_years age_months_sc_0_2yr age_months_ex_0_19yr
+       <dbl>               <dbl>                <dbl>
+ 1        69                  NA                   NA
+ 2        54                  NA                   NA
+ 3        72                  NA                   NA
+ 4         9                  NA                  119
+ 5        73                  NA                   NA
+ 6        56                  NA                   NA
+ 7         0                   5                    6
+ 8        61                  NA                   NA
+ 9        42                  NA                   NA
+10        56                  NA                   NA
+# ℹ 10,165 more rows
    +
    +
    # select all columns that have a logical type
+demographics |> select(where(is.logical))
    +
    +
    # A tibble: 10,175 × 5
+   served_active_duty_us served_active_duty_foreign born_usa citizen_usa
+   <lgl>                 <lgl>                      <lgl>    <lgl>      
+ 1 TRUE                  TRUE                       TRUE     TRUE       
+ 2 FALSE                 NA                         TRUE     TRUE       
+ 3 TRUE                  TRUE                       TRUE     TRUE       
+ 4 NA                    NA                         TRUE     TRUE       
+ 5 FALSE                 NA                         TRUE     TRUE       
+ 6 TRUE                  FALSE                      TRUE     TRUE       
+ 7 NA                    NA                         TRUE     TRUE       
+ 8 FALSE                 NA                         TRUE     TRUE       
+ 9 FALSE                 NA                         TRUE     TRUE       
+10 FALSE                 NA                         TRUE     TRUE       
+# ℹ 10,165 more rows
+# ℹ 1 more variable: language_english <lgl>
    +
    +
    +
    +

    Exercise

    +
      +

    1. For all columns that contain the word “education” (education_youth and education), add the number 5 to each value

      2. +

    2. For all numeric columns, standardize the values by subtracting the mean and dividing by the standard deviation

      3. +

    3. Compute the average age across all columns that start with age_ (Hint: use across() within summarize())

      4. +

    4. Compute the total number of TRUE values in the born_usa, citizen_usa, and language_english columns (Hint: use across() within summarize())

      5. +
    +
    +

    Solution

    +
      +
    1. +
    +
    +
    demographics |> mutate(
+  across(
+    contains("education"), 
+    ~{. + 5}
+  )
+) |> 
+  print(width = Inf)
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+   race             six_month_period age_months_ex_0_19yr served_active_duty_us
+   <chr>                       <dbl>                <dbl> <lgl>                
+ 1 black                           1                   NA TRUE                 
+ 2 white                           1                   NA FALSE                
+ 3 white                           2                   NA TRUE                 
+ 4 white                           1                  119 NA                   
+ 5 white                           1                   NA FALSE                
+ 6 mexican american                1                   NA TRUE                 
+ 7 white                           2                    6 NA                   
+ 8 white                           2                   NA FALSE                
+ 9 other hispanic                 NA                   NA FALSE                
+10 white                           1                   NA FALSE                
+   served_active_duty_foreign born_usa citizen_usa time_in_us education_youth
+   <lgl>                      <lgl>    <lgl>            <dbl>           <dbl>
+ 1 TRUE                       TRUE     TRUE                NA              NA
+ 2 NA                         TRUE     TRUE                NA              NA
+ 3 TRUE                       TRUE     TRUE                NA              NA
+ 4 NA                         TRUE     TRUE                NA               8
+ 5 NA                         TRUE     TRUE                NA              NA
+ 6 FALSE                      TRUE     TRUE                NA              NA
+ 7 NA                         TRUE     TRUE                NA              NA
+ 8 NA                         TRUE     TRUE                NA              NA
+ 9 NA                         TRUE     TRUE                NA              NA
+10 NA                         TRUE     TRUE                NA              NA
+   education marital_status pregnant language_english household_income
+       <dbl> <chr>          <chr>    <lgl>                       <dbl>
+ 1         8 separated      <NA>     TRUE                        17500
+ 2         8 married        <NA>     TRUE                        40000
+ 3         9 married        <NA>     TRUE                        70000
+ 4        NA <NA>           <NA>     TRUE                        60000
+ 5        10 married        <NA>     TRUE                       100000
+ 6         9 divorced       <NA>     TRUE                        60000
+ 7        NA <NA>           <NA>     TRUE                       100000
+ 8        10 widowed        <NA>     TRUE                        70000
+ 9         8 married        <NA>     TRUE                       100000
+10         8 divorced       <NA>     TRUE                        17500
+# ℹ 10,165 more rows
    +
    +
    +
      +
    1. +
    +
    +
    # standardize all numeric columns
+demographics |> mutate(
+  across(
+    where(is.numeric), 
+    ~{(. - mean(., na.rm = TRUE)) / sd(., na.rm = TRUE)}
+  )
+)
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         -1.73 both interview and exam male       1.54               NA    
+ 2         -1.73 both interview and exam male       0.922              NA    
+ 3         -1.73 both interview and exam male       1.66               NA    
+ 4         -1.73 both interview and exam male      -0.921              NA    
+ 5         -1.73 both interview and exam female     1.70               NA    
+ 6         -1.73 both interview and exam male       1.00               NA    
+ 7         -1.73 both interview and exam male      -1.29               -0.776
+ 8         -1.73 both interview and exam female     1.21               NA    
+ 9         -1.73 interview only          male       0.431              NA    
+10         -1.73 both interview and exam female     1.00               NA    
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +
      +
    1. +
    +
    +
    # compute average age across all age columns
+demographics |> summarize(
+  across(
+    starts_with("age"), 
+    ~mean(., na.rm = TRUE)
+  )
+)
    +
    +
    # A tibble: 1 × 3
+  age_years age_months_sc_0_2yr age_months_ex_0_19yr
+      <dbl>               <dbl>                <dbl>
+1      31.5                10.3                 107.
    +
    +
    +
      +
    1. +
    +
    +
    # compute the total in the `born_usa`, `citizen_usa`, and `language_english`
+demographics |> summarise(
+  across(
+    any_of(c("born_usa", "citizen_usa", "language_english")),
+    ~sum(., na.rm = TRUE)
+  )
+)
    +
    +
    # A tibble: 1 × 3
+  born_usa citizen_usa language_english
+     <int>       <int>            <int>
+1     8262        9220             9100
    +
    +
    + + +
    +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/content/complete/04_recoding_variables_complete.html b/docs/content/complete/04_recoding_variables_complete.html new file mode 100644 index 0000000..cb763f8 --- /dev/null +++ b/docs/content/complete/04_recoding_variables_complete.html @@ -0,0 +1,844 @@ + + + + + + + + + +Recoding variables using if_else and case_when – Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + +
    + +
    + + + + +
    + +
    +
    +

    Recoding variables using if_else and case_when

    +
    + + + +
    + + + + +
    + + + +
    + + +
    +
    # load the tidyverse and demographics dataset
+library(tidyverse)
    +
    +
    ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
+✔ dplyr     1.1.4     ✔ readr     2.1.5
+✔ forcats   1.0.0     ✔ stringr   1.5.1
+✔ ggplot2   3.5.1     ✔ tibble    3.2.1
+✔ lubridate 1.9.3     ✔ tidyr     1.3.1
+✔ purrr     1.0.2     
+── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
+✖ dplyr::filter() masks stats::filter()
+✖ dplyr::lag()    masks stats::lag()
+ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
    +
    +
    demographics <- read_csv("data/demographics.csv")
    +
    +
    Rows: 10175 Columns: 19
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (5): interview_examination, gender, race, marital_status, pregnant
+dbl (9): respondent_id, age_years, age_months_sc_0_2yr, six_month_period, ag...
+lgl (5): served_active_duty_us, served_active_duty_foreign, born_usa, citize...
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
    +
    head(demographics)
    +
    +
    # A tibble: 6 × 19
+  respondent_id interview_examination gender age_years age_months_sc_0_2yr race 
+          <dbl> <chr>                 <chr>      <dbl>               <dbl> <chr>
+1         73557 both interview and e… male          69                  NA black
+2         73558 both interview and e… male          54                  NA white
+3         73559 both interview and e… male          72                  NA white
+4         73560 both interview and e… male           9                  NA white
+5         73561 both interview and e… female        73                  NA white
+6         73562 both interview and e… male          56                  NA mexi…
+# ℹ 13 more variables: six_month_period <dbl>, age_months_ex_0_19yr <dbl>,
+#   served_active_duty_us <lgl>, served_active_duty_foreign <lgl>,
+#   born_usa <lgl>, citizen_usa <lgl>, time_in_us <dbl>, education_youth <dbl>,
+#   education <dbl>, marital_status <chr>, pregnant <chr>,
+#   language_english <lgl>, household_income <dbl>
    +
    +
    +

    In this document, you will learn how to “recode” variables by replacing values in a variable with other values of your choice, e.g., converting numerically-encoded variables to categorical/character versions, and vice versa.

    +

    We will introduce two functions for doing this:

    +
      +

    • if_else() which can be used to create binary variables (variables with just two distinct values) based on a logical “condition”

      • +

    • case_when() which can be used to create variables with many different values.

      • +
    +
    +

    if_else

    +
    +
    # apply count() to interview_examination
+demographics |> count(interview_examination)
    +
    +
    # A tibble: 2 × 2
+  interview_examination       n
+  <chr>                   <int>
+1 both interview and exam  9813
+2 interview only            362
    +
    +
    +

    Let’s convert it to a numeric format using if_else().

    +
    +
    # use mutate() to create a new column called interview_examination_numeric
+# which is 2 if interview_examination is "both interview and exam"
+# and 1 otherwise
+# then select just interview_examination and interview_examination_numeric
+demographics |> 
+  mutate(interview_examination_numeric = if_else(
+    interview_examination == "both interview and exam", 
+    true = 2, 
+    false = 1)
+  ) |>
+  select(interview_examination, interview_examination_numeric)
    +
    +
    # A tibble: 10,175 × 2
+   interview_examination   interview_examination_numeric
+   <chr>                                           <dbl>
+ 1 both interview and exam                             2
+ 2 both interview and exam                             2
+ 3 both interview and exam                             2
+ 4 both interview and exam                             2
+ 5 both interview and exam                             2
+ 6 both interview and exam                             2
+ 7 both interview and exam                             2
+ 8 both interview and exam                             2
+ 9 interview only                                      1
+10 both interview and exam                             2
+# ℹ 10,165 more rows
    +
    +
    +
    +

    Exercise

    +

    Use if_else() to create a variable called completed_high_school, which has the values "yes" if education is equal to at least 3, and "no" otherwise.

    +

    A link to the documentation for the demographics data can be found here.

    +
    +

    Solution

    +

    Our condition is education >= 3 and we want to replace all values for which this condition is true with "yes", and all other values with "no":

    +
    +
    demographics |> 
+  mutate(completed_high_school = if_else(
+    education >= 3, 
+    true = "yes", 
+    false = "no")) |>
+  select(education, completed_high_school) |>
+  sample_n(10)
    +
    +
    # A tibble: 10 × 2
+   education completed_high_school
+       <dbl> <chr>                
+ 1        NA <NA>                 
+ 2        NA <NA>                 
+ 3         4 yes                  
+ 4         5 yes                  
+ 5         4 yes                  
+ 6         3 yes                  
+ 7         4 yes                  
+ 8         2 no                   
+ 9        NA <NA>                 
+10         5 yes
    +
    +
    +
    +
    +
    +
    +

    case_when

    +

    The case_when() function is similar to if_else(), but it allows you to have an unlimited number of conditions and corresponding recoded values.

    +

    In this section we will work with the marital_status column of the demographics data:

    +
    +
    # apply count() to the marital_status column
+demographics |> count(marital_status)
    +
    +
    # A tibble: 7 × 2
+  marital_status          n
+  <chr>               <int>
+1 divorced              659
+2 living_with_partner   417
+3 married              2965
+4 never_married        1112
+5 separated             177
+6 widowed               436
+7 <NA>                 4409
    +
    +
    +

    Let’s create a new variable based on marital_status that replaces

    +
      +

    • "married" with 3

      • +

    • "living_with_partner" with 2

      • +

    • "divorced", "widowed", "never_married", and "separated" with 1

      • +
    +
    +
    # use mutate and case_when() to create marital_status_numeric 
+# with the values above
+demographics |> mutate(marital_status_numeric = case_when(
+  marital_status == "married" ~ 3,
+  marital_status == "living_with_partner" ~ 2,
+  marital_status %in% c("divorced", "widowed", "never_married", "separated") ~ 1)) |>
+  select(marital_status, marital_status_numeric)
    +
    +
    # A tibble: 10,175 × 2
+   marital_status marital_status_numeric
+   <chr>                           <dbl>
+ 1 separated                           1
+ 2 married                             3
+ 3 married                             3
+ 4 <NA>                               NA
+ 5 married                             3
+ 6 divorced                            1
+ 7 <NA>                               NA
+ 8 widowed                             1
+ 9 married                             3
+10 divorced                            1
+# ℹ 10,165 more rows
    +
    +
    +
    +
    +

    Execise

    +

    Use case_when() to convert born_usa and citizen_usa to “yes” and “no”. Bonus points: use across().

    +
    +

    Solution

    +

    To do this without across(), you can write:

    +
    +
    demographics |> mutate(born_usa_chr = case_when(born_usa ~ "yes",
+                                                !born_usa ~ "no"),
+                       citizen_usa_chr = case_when(citizen_usa ~ "yes",
+                                                   !citizen_usa ~ "no")) |>
+  select(born_usa, born_usa_chr, citizen_usa, citizen_usa_chr) |> 
+  sample_n(10)
    +
    +
    # A tibble: 10 × 4
+   born_usa born_usa_chr citizen_usa citizen_usa_chr
+   <lgl>    <chr>        <lgl>       <chr>          
+ 1 TRUE     yes          TRUE        yes            
+ 2 TRUE     yes          TRUE        yes            
+ 3 TRUE     yes          TRUE        yes            
+ 4 TRUE     yes          TRUE        yes            
+ 5 FALSE    no           FALSE       no             
+ 6 FALSE    no           TRUE        yes            
+ 7 TRUE     yes          TRUE        yes            
+ 8 TRUE     yes          TRUE        yes            
+ 9 FALSE    no           TRUE        yes            
+10 TRUE     yes          TRUE        yes
    +
    +
    +

    Note that born_usa ~ "yes" is equivalent to born_usa == TRUE ~ "yes", but the == TRUE is redundant because born_usa is itself a logical variable. Similarly, !citizen_usa ~ "no" is equivalent to citizen_usa == FALSE ~ "no".

    +

    To use across(), the relevant select helper is something like ends_with("_usa") or contains("usa"), and you provide a ~ before case_when() to start an anonymous function, and you need to replace the column name with . (again, you don’t need the == TRUE for this particular example in the condition, but that’s just because the columns we’re applying the case_when() function to are logical).

    +
    +
    demographics |> mutate(across(ends_with("_usa"), 
+                              ~case_when(. == TRUE ~ "yes",
+                                         . == FALSE ~ "no"),
+                              .names = "{.col}_chr")) |>
+  select(contains("_usa")) |> 
+  sample_n(10)
    +
    +
    # A tibble: 10 × 4
+   born_usa citizen_usa born_usa_chr citizen_usa_chr
+   <lgl>    <lgl>       <chr>        <chr>          
+ 1 TRUE     TRUE        yes          yes            
+ 2 TRUE     TRUE        yes          yes            
+ 3 FALSE    TRUE        no           yes            
+ 4 TRUE     TRUE        yes          yes            
+ 5 TRUE     TRUE        yes          yes            
+ 6 TRUE     TRUE        yes          yes            
+ 7 TRUE     TRUE        yes          yes            
+ 8 TRUE     TRUE        yes          yes            
+ 9 TRUE     TRUE        yes          yes            
+10 TRUE     TRUE        yes          yes
    +
    +
    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/content/complete/05_pivoting_complete.html b/docs/content/complete/05_pivoting_complete.html new file mode 100644 index 0000000..207cd61 --- /dev/null +++ b/docs/content/complete/05_pivoting_complete.html @@ -0,0 +1,786 @@ + + + + + + + + + +Reshaping (Pivoting) Data – Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + +
    + +
    + + + + +
    + +
    +
    +

    Reshaping (Pivoting) Data

    +
    + + + +
    + + + + +
    + + + +
    + + +

    In this lesson, we will be working with a new NHANES table that contains urine albumin and creatinine lab data.

    +
    +
    # load the tidyverse and the urine_albumin_creatinine NHANES data
+library(tidyverse)
    +
    +
    ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
+✔ dplyr     1.1.4     ✔ readr     2.1.5
+✔ forcats   1.0.0     ✔ stringr   1.5.1
+✔ ggplot2   3.5.1     ✔ tibble    3.2.1
+✔ lubridate 1.9.3     ✔ tidyr     1.3.1
+✔ purrr     1.0.2     
+── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
+✖ dplyr::filter() masks stats::filter()
+✖ dplyr::lag()    masks stats::lag()
+ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
    +
    +
    labs_data <- read.csv("data/urine_albumin_creatinine.csv")
    +
    +
    +
    # take a look at the first 10 rows
+head(labs_data, 10)
    +
    +
       respondent_id                         lab measurement
+1          73557            ur_albumin_ug_ml        4.30
+2          73557             ur_albumin_mg_l        4.30
+3          73557         ur_creatinine_mg_dl       39.00
+4          73557        ur_creatinine_umol_l     3447.60
+5          73557 ur_albumin_creatinine_ratio       11.03
+6          73558            ur_albumin_ug_ml      153.00
+7          73558             ur_albumin_mg_l      153.00
+8          73558         ur_creatinine_mg_dl       50.00
+9          73558        ur_creatinine_umol_l     4420.00
+10         73558 ur_albumin_creatinine_ratio      306.00
    +
    +
    +

    This data is in a long format–there are multiple rows for each observational unit, each corresponding to a different variable being measured (in this case, the different labs).

    +

    A wide format, on the other hand, will only have one row for each observational unit (respondent), and each of the individual variables being measured (the labs) will have their own column, each containing the values for the corresponding lab.

    +

    You can convert from a long format to a wide format using the pivor_wider() function.

    +

    The code below creates a wide-form version of the labs data, and saves it as a new data frame called labs_data_wide:

    +
    +
    # use pivot_wider() to convert the labs data from a 
+# long format to a wide format. 
+# arguments are `names_from` and `values_from`
+# save the wide data as `labs_data_wide`.
+labs_data_wide <- labs_data |> 
+  pivot_wider(names_from = "lab", values_from = "measurement")
+labs_data_wide
    +
    +
    # A tibble: 8,291 × 6
+   respondent_id ur_albumin_ug_ml ur_albumin_mg_l ur_creatinine_mg_dl
+           <int>            <dbl>           <dbl>               <dbl>
+ 1         73557              4.3             4.3                  39
+ 2         73558            153             153                    50
+ 3         73559             11.9            11.9                 113
+ 4         73560             16              16                    76
+ 5         73561            255             255                   147
+ 6         73562            123             123                    74
+ 7         73564             19              19                   242
+ 8         73566              1.3             1.3                  18
+ 9         73567             35              35                   215
+10         73568             25              25                    31
+# ℹ 8,281 more rows
+# ℹ 2 more variables: ur_creatinine_umol_l <dbl>,
+#   ur_albumin_creatinine_ratio <dbl>
    +
    +
    +

    If you want to convert from a wide format dataset into a longer-format dataset, you can instead use the pivot_longer() function.

    +
    +
    # use pivot_longer() to convert labs_data_wide back to along format
+# arguments are `cols` (use a select helper!), `names_to` and `values_to`
+labs_data_wide |> 
+  pivot_longer(cols = starts_with("ur_"), 
+               names_to = "lab",
+               values_to = "measurement")
    +
    +
    # A tibble: 41,455 × 3
+   respondent_id lab                         measurement
+           <int> <chr>                             <dbl>
+ 1         73557 ur_albumin_ug_ml                    4.3
+ 2         73557 ur_albumin_mg_l                     4.3
+ 3         73557 ur_creatinine_mg_dl                39  
+ 4         73557 ur_creatinine_umol_l             3448. 
+ 5         73557 ur_albumin_creatinine_ratio        11.0
+ 6         73558 ur_albumin_ug_ml                  153  
+ 7         73558 ur_albumin_mg_l                   153  
+ 8         73558 ur_creatinine_mg_dl                50  
+ 9         73558 ur_creatinine_umol_l             4420  
+10         73558 ur_albumin_creatinine_ratio       306  
+# ℹ 41,445 more rows
    +
    +
    +

    Use-case for long-format: creating a visualization that compares the different variables using ggplot2.

    +
    +
    # create boxplots using the long format for the measurements from each lab
+# maybe add a log-scale to the y-axis
+labs_data |> ggplot() + 
+  geom_boxplot(aes(x = lab, y = measurement)) +
+  scale_y_log10()
    +
    +
    Warning: Removed 1195 rows containing non-finite outside the scale range
+(`stat_boxplot()`).
    +
    +
    +
    +
    +

    +
    +
    +
    +
    +
    +

    Exercise

    +

    Load the demographics data and use select() to select just the respondent_id, gender, marital_status and race columns and then use pivot_longer() to create the following long-format table (below are just the first 10 rows).

    +

    respondent_id name value
    +
    +1 73557 gender male
    +2 73557 marital_status separated 3 73557 race black
    +4 73558 gender male
    +5 73558 marital_status married
    +6 73558 race white
    +7 73559 gender male
    +8 73559 marital_status married
    +9 73559 race white
    +10 73560 gender male

    +
    +

    Solution

    +
    +
    demographics <- read_csv("data/demographics.csv")
    +
    +
    Rows: 10175 Columns: 19
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (5): interview_examination, gender, race, marital_status, pregnant
+dbl (9): respondent_id, age_years, age_months_sc_0_2yr, six_month_period, ag...
+lgl (5): served_active_duty_us, served_active_duty_foreign, born_usa, citize...
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
    +
    demographics
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +
    +
    demographics |> 
+  select(respondent_id, gender, marital_status, race) |>
+  pivot_longer(cols = all_of(c("gender", "marital_status", "race")))
    +
    +
    # A tibble: 30,525 × 3
+   respondent_id name           value    
+           <dbl> <chr>          <chr>    
+ 1         73557 gender         male     
+ 2         73557 marital_status separated
+ 3         73557 race           black    
+ 4         73558 gender         male     
+ 5         73558 marital_status married  
+ 6         73558 race           white    
+ 7         73559 gender         male     
+ 8         73559 marital_status married  
+ 9         73559 race           white    
+10         73560 gender         male     
+# ℹ 30,515 more rows
    +
    +
    + + +
    +
    + +
    + +
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    +
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    + +
    + + + + +
    + +
    +
    +

    Joining Data Together

    +
    + + + +
    + + + + +
    + + + +
    + + +

    This lesson introduces techniques for “joining” multiple data tables together using a “key” variable

    +

    A really helpful resource for learning about joins is the R for Data Science book (specifically the chapter about “Relational Data”).

    +

    At the end of this lesson we will have created a single data frame that contains the information from both the demographics data and the urine albumin and creatinine labs data.

    +
    +
    # load the tidyverse, the demographics, and the urine_albumin_creatinine data
+library(tidyverse)
    +
    +
    ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
+✔ dplyr     1.1.4     ✔ readr     2.1.5
+✔ forcats   1.0.0     ✔ stringr   1.5.1
+✔ ggplot2   3.5.1     ✔ tibble    3.2.1
+✔ lubridate 1.9.3     ✔ tidyr     1.3.1
+✔ purrr     1.0.2     
+── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
+✖ dplyr::filter() masks stats::filter()
+✖ dplyr::lag()    masks stats::lag()
+ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
    +
    +
    demographics <- read_csv("data/demographics.csv")
    +
    +
    Rows: 10175 Columns: 19
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (5): interview_examination, gender, race, marital_status, pregnant
+dbl (9): respondent_id, age_years, age_months_sc_0_2yr, six_month_period, ag...
+lgl (5): served_active_duty_us, served_active_duty_foreign, born_usa, citize...
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
    +
    labs <- read_csv("data/urine_albumin_creatinine.csv")
    +
    +
    Rows: 41455 Columns: 3
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (1): lab
+dbl (2): respondent_id, measurement
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
    +
    +
    +

    Determining what kind of join to do

    +

    There are four kinds of joins that you might want to use for combining two tables into a single table:

    +
    +
    +

    +
    Diagram of joins
    +
    +
    +
      +

    • An inner join, which will keep only the data for the observational units that appear in both tables

      • +

    • A left join, which will keep all of the data for the observational units in the first (left) table, and will add missing values when there is no available data in the second table.

      • +

    • A right join, which will keep all of the data for the observational units in the second (right) table, and will add missing values when there is no available data in the first table.

      • +

    • A full join, which will keep all of the data for the observational units in both the first (left) table, and will add missing values when there is no available data in the other table.

      • +
    +

    The kind of join that you will implement will depend on what you want to use your joined data for.

    +
    +

    Checking the uniqueness of the key ID variables

    +

    Below, we see that the respondent_id column is indeed unique for demographics:

    +
    +
    # check whether the respondent ID values in demographics are unique?
+identical(unique(demographics$respondent_id), demographics$respondent_id)
    +
    +
    [1] TRUE
    +
    +
    +

    But not for labs:

    +
    +
    # check whether the respondent ID values in labs are unique?
+identical(unique(labs$respondent_id), labs$respondent_id)
    +
    +
    [1] FALSE
    +
    +
    +
    +
    +

    Checking overlap between tables

    +

    Are there any observations in the demographics table that do not appear in the labs table?

    +
    +
    # Compute the proportion of people in demographics who are also in labs
+sum(unique(demographics$respondent_id) %in% unique(labs$respondent_id)) / n_distinct(demographics$respondent_id)
    +
    +
    [1] 0.8148403
    +
    +
    +

    The calculation above shows that around 81% of observations in the demographics table have available labs data.

    +

    Are there any observations in the labs table that do not appear in the demographics table?

    +
    +
    # proportion of people in labs who are also in demographics
+sum(unique(labs$respondent_id) %in% unique(demographics$respondent_id)) / n_distinct(labs$respondent_id)
    +
    +
    [1] 1
    +
    +
    +

    The calculation above shows that 100% of observations in the labs table have available demographics data.

    +
    +
    +
    +

    Joining demographics and labs

    +

    Our two options for to join demographics (left) and labs (right) are:

    +
      +

    • An inner or right join will only keep the 81% of people in demographics who have available labs data

      • +

    • A left or full join will keep all people in demographics data, and join missing values for those who don’t have labs data available

      • +
    +

    Since we don’t want to discard any data, we will choose the left/full join.

    +
    +
    # perform a left/full join of demographics and labs
+print(left_join(demographics, labs, by = "respondent_id"), width = Inf)
    +
    +
    # A tibble: 43,339 × 21
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73557 both interview and exam male          69                  NA
+ 3         73557 both interview and exam male          69                  NA
+ 4         73557 both interview and exam male          69                  NA
+ 5         73557 both interview and exam male          69                  NA
+ 6         73558 both interview and exam male          54                  NA
+ 7         73558 both interview and exam male          54                  NA
+ 8         73558 both interview and exam male          54                  NA
+ 9         73558 both interview and exam male          54                  NA
+10         73558 both interview and exam male          54                  NA
+   race  six_month_period age_months_ex_0_19yr served_active_duty_us
+   <chr>            <dbl>                <dbl> <lgl>                
+ 1 black                1                   NA TRUE                 
+ 2 black                1                   NA TRUE                 
+ 3 black                1                   NA TRUE                 
+ 4 black                1                   NA TRUE                 
+ 5 black                1                   NA TRUE                 
+ 6 white                1                   NA FALSE                
+ 7 white                1                   NA FALSE                
+ 8 white                1                   NA FALSE                
+ 9 white                1                   NA FALSE                
+10 white                1                   NA FALSE                
+   served_active_duty_foreign born_usa citizen_usa time_in_us education_youth
+   <lgl>                      <lgl>    <lgl>            <dbl>           <dbl>
+ 1 TRUE                       TRUE     TRUE                NA              NA
+ 2 TRUE                       TRUE     TRUE                NA              NA
+ 3 TRUE                       TRUE     TRUE                NA              NA
+ 4 TRUE                       TRUE     TRUE                NA              NA
+ 5 TRUE                       TRUE     TRUE                NA              NA
+ 6 NA                         TRUE     TRUE                NA              NA
+ 7 NA                         TRUE     TRUE                NA              NA
+ 8 NA                         TRUE     TRUE                NA              NA
+ 9 NA                         TRUE     TRUE                NA              NA
+10 NA                         TRUE     TRUE                NA              NA
+   education marital_status pregnant language_english household_income
+       <dbl> <chr>          <chr>    <lgl>                       <dbl>
+ 1         3 separated      <NA>     TRUE                        17500
+ 2         3 separated      <NA>     TRUE                        17500
+ 3         3 separated      <NA>     TRUE                        17500
+ 4         3 separated      <NA>     TRUE                        17500
+ 5         3 separated      <NA>     TRUE                        17500
+ 6         3 married        <NA>     TRUE                        40000
+ 7         3 married        <NA>     TRUE                        40000
+ 8         3 married        <NA>     TRUE                        40000
+ 9         3 married        <NA>     TRUE                        40000
+10         3 married        <NA>     TRUE                        40000
+   lab                         measurement
+   <chr>                             <dbl>
+ 1 ur_albumin_ug_ml                    4.3
+ 2 ur_albumin_mg_l                     4.3
+ 3 ur_creatinine_mg_dl                39  
+ 4 ur_creatinine_umol_l             3448. 
+ 5 ur_albumin_creatinine_ratio        11.0
+ 6 ur_albumin_ug_ml                  153  
+ 7 ur_albumin_mg_l                   153  
+ 8 ur_creatinine_mg_dl                50  
+ 9 ur_creatinine_umol_l             4420  
+10 ur_albumin_creatinine_ratio       306  
+# ℹ 43,329 more rows
    +
    +
    print(full_join(demographics, labs, by = "respondent_id"), width = Inf)
    +
    +
    # A tibble: 43,339 × 21
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73557 both interview and exam male          69                  NA
+ 3         73557 both interview and exam male          69                  NA
+ 4         73557 both interview and exam male          69                  NA
+ 5         73557 both interview and exam male          69                  NA
+ 6         73558 both interview and exam male          54                  NA
+ 7         73558 both interview and exam male          54                  NA
+ 8         73558 both interview and exam male          54                  NA
+ 9         73558 both interview and exam male          54                  NA
+10         73558 both interview and exam male          54                  NA
+   race  six_month_period age_months_ex_0_19yr served_active_duty_us
+   <chr>            <dbl>                <dbl> <lgl>                
+ 1 black                1                   NA TRUE                 
+ 2 black                1                   NA TRUE                 
+ 3 black                1                   NA TRUE                 
+ 4 black                1                   NA TRUE                 
+ 5 black                1                   NA TRUE                 
+ 6 white                1                   NA FALSE                
+ 7 white                1                   NA FALSE                
+ 8 white                1                   NA FALSE                
+ 9 white                1                   NA FALSE                
+10 white                1                   NA FALSE                
+   served_active_duty_foreign born_usa citizen_usa time_in_us education_youth
+   <lgl>                      <lgl>    <lgl>            <dbl>           <dbl>
+ 1 TRUE                       TRUE     TRUE                NA              NA
+ 2 TRUE                       TRUE     TRUE                NA              NA
+ 3 TRUE                       TRUE     TRUE                NA              NA
+ 4 TRUE                       TRUE     TRUE                NA              NA
+ 5 TRUE                       TRUE     TRUE                NA              NA
+ 6 NA                         TRUE     TRUE                NA              NA
+ 7 NA                         TRUE     TRUE                NA              NA
+ 8 NA                         TRUE     TRUE                NA              NA
+ 9 NA                         TRUE     TRUE                NA              NA
+10 NA                         TRUE     TRUE                NA              NA
+   education marital_status pregnant language_english household_income
+       <dbl> <chr>          <chr>    <lgl>                       <dbl>
+ 1         3 separated      <NA>     TRUE                        17500
+ 2         3 separated      <NA>     TRUE                        17500
+ 3         3 separated      <NA>     TRUE                        17500
+ 4         3 separated      <NA>     TRUE                        17500
+ 5         3 separated      <NA>     TRUE                        17500
+ 6         3 married        <NA>     TRUE                        40000
+ 7         3 married        <NA>     TRUE                        40000
+ 8         3 married        <NA>     TRUE                        40000
+ 9         3 married        <NA>     TRUE                        40000
+10         3 married        <NA>     TRUE                        40000
+   lab                         measurement
+   <chr>                             <dbl>
+ 1 ur_albumin_ug_ml                    4.3
+ 2 ur_albumin_mg_l                     4.3
+ 3 ur_creatinine_mg_dl                39  
+ 4 ur_creatinine_umol_l             3448. 
+ 5 ur_albumin_creatinine_ratio        11.0
+ 6 ur_albumin_ug_ml                  153  
+ 7 ur_albumin_mg_l                   153  
+ 8 ur_creatinine_mg_dl                50  
+ 9 ur_creatinine_umol_l             4420  
+10 ur_albumin_creatinine_ratio       306  
+# ℹ 43,329 more rows
    +
    +
    +

    Look at the results above, does something look wrong to you?

    +

    If your key ID variable has repeated values, your joined data will too.

    +

    A good check after completing a join is to make sure that the number of rows in the resulting joined data matches what you expect

    +
    +
    # check the number of rows in the joined data
+nrow(left_join(demographics, labs, by = "respondent_id"))
    +
    +
    [1] 43339
    +
    +
    # check the number of rows in demographics
+nrow(demographics)
    +
    +
    [1] 10175
    +
    +
    +

    Therefore, to ensure that we have just one row per observational unit (i.e., per respondent_id value), we need to join the wide-format labs_wide data instead of the long-format labs data.

    +
    +
    # compute the wide format of the labs data
+labs_wide <- labs |> 
+  pivot_wider(names_from = "lab", 
+              values_from = "measurement")
+labs_wide
    +
    +
    # A tibble: 8,291 × 6
+   respondent_id ur_albumin_ug_ml ur_albumin_mg_l ur_creatinine_mg_dl
+           <dbl>            <dbl>           <dbl>               <dbl>
+ 1         73557              4.3             4.3                  39
+ 2         73558            153             153                    50
+ 3         73559             11.9            11.9                 113
+ 4         73560             16              16                    76
+ 5         73561            255             255                   147
+ 6         73562            123             123                    74
+ 7         73564             19              19                   242
+ 8         73566              1.3             1.3                  18
+ 9         73567             35              35                   215
+10         73568             25              25                    31
+# ℹ 8,281 more rows
+# ℹ 2 more variables: ur_creatinine_umol_l <dbl>,
+#   ur_albumin_creatinine_ratio <dbl>
    +
    +
    +
    +
    # join demographics and labs_wide
+print(left_join(demographics, labs_wide, by = "respondent_id"), width = Inf)
    +
    +
    # A tibble: 10,175 × 24
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+   race             six_month_period age_months_ex_0_19yr served_active_duty_us
+   <chr>                       <dbl>                <dbl> <lgl>                
+ 1 black                           1                   NA TRUE                 
+ 2 white                           1                   NA FALSE                
+ 3 white                           2                   NA TRUE                 
+ 4 white                           1                  119 NA                   
+ 5 white                           1                   NA FALSE                
+ 6 mexican american                1                   NA TRUE                 
+ 7 white                           2                    6 NA                   
+ 8 white                           2                   NA FALSE                
+ 9 other hispanic                 NA                   NA FALSE                
+10 white                           1                   NA FALSE                
+   served_active_duty_foreign born_usa citizen_usa time_in_us education_youth
+   <lgl>                      <lgl>    <lgl>            <dbl>           <dbl>
+ 1 TRUE                       TRUE     TRUE                NA              NA
+ 2 NA                         TRUE     TRUE                NA              NA
+ 3 TRUE                       TRUE     TRUE                NA              NA
+ 4 NA                         TRUE     TRUE                NA               3
+ 5 NA                         TRUE     TRUE                NA              NA
+ 6 FALSE                      TRUE     TRUE                NA              NA
+ 7 NA                         TRUE     TRUE                NA              NA
+ 8 NA                         TRUE     TRUE                NA              NA
+ 9 NA                         TRUE     TRUE                NA              NA
+10 NA                         TRUE     TRUE                NA              NA
+   education marital_status pregnant language_english household_income
+       <dbl> <chr>          <chr>    <lgl>                       <dbl>
+ 1         3 separated      <NA>     TRUE                        17500
+ 2         3 married        <NA>     TRUE                        40000
+ 3         4 married        <NA>     TRUE                        70000
+ 4        NA <NA>           <NA>     TRUE                        60000
+ 5         5 married        <NA>     TRUE                       100000
+ 6         4 divorced       <NA>     TRUE                        60000
+ 7        NA <NA>           <NA>     TRUE                       100000
+ 8         5 widowed        <NA>     TRUE                        70000
+ 9         3 married        <NA>     TRUE                       100000
+10         3 divorced       <NA>     TRUE                        17500
+   ur_albumin_ug_ml ur_albumin_mg_l ur_creatinine_mg_dl ur_creatinine_umol_l
+              <dbl>           <dbl>               <dbl>                <dbl>
+ 1              4.3             4.3                  39                3448.
+ 2            153             153                    50                4420 
+ 3             11.9            11.9                 113                9989.
+ 4             16              16                    76                6718.
+ 5            255             255                   147               12995.
+ 6            123             123                    74                6542.
+ 7             NA              NA                    NA                  NA 
+ 8             19              19                   242               21393.
+ 9             NA              NA                    NA                  NA 
+10              1.3             1.3                  18                1591.
+   ur_albumin_creatinine_ratio
+                         <dbl>
+ 1                       11.0 
+ 2                      306   
+ 3                       10.5 
+ 4                       21.0 
+ 5                      173.  
+ 6                      166.  
+ 7                       NA   
+ 8                        7.85
+ 9                       NA   
+10                        7.22
+# ℹ 10,165 more rows
    +
    +
    +
    +
    +

    Exercise

    +

    How many rows would you expect an inner join of demographics and labs_wide to have? Check your answer by conducting the join using inner_join()

    +
    +

    Solution

    +

    The number of rows should match the intersection of the two datasets. Since all people in labs_wide are also in demographics (but not the other way around), the join will have the same number of rows in labs_wide.

    +
    +
    nrow(labs_wide)
    +
    +
    [1] 8291
    +
    +
    +

    The join can be conducted using inner_join() and notice that the number of rows matches labs_wide.

    +
    +
    inner_join(demographics, labs_wide, by = "respondent_id")
    +
    +
    # A tibble: 8,291 × 24
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73564 both interview and exam female        61                  NA
+ 8         73566 both interview and exam female        56                  NA
+ 9         73567 both interview and exam male          65                  NA
+10         73568 both interview and exam female        26                  NA
+# ℹ 8,281 more rows
+# ℹ 19 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>, ur_albumin_ug_ml <dbl>, ur_albumin_mg_l <dbl>, …
    +
    +
    +

    Note that if there were observations in labs_wide that were not in demographics, then the resulting inner join will have fewer rows than both tables.

    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/content/complete/detailed/01_custom_functions.html b/docs/content/complete/detailed/01_custom_functions.html new file mode 100644 index 0000000..aaacd98 --- /dev/null +++ b/docs/content/complete/detailed/01_custom_functions.html @@ -0,0 +1,1327 @@ + + + + + + + + + +Custom functions – Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + +
    + +
    + + + + +
    + +
    +
    +

    Custom functions

    +
    + + + +
    + + + + +
    + + + +
    + + +
    +

    A simple custom function

    +

    In this notebook, you will learn how to define your own functions.

    +

    We will start with a very simple function, that we will call add_one(), which will add 1 to any value it is given.

    +

    The simplest way to define add_one() is

    +
    +
    add_one <- function(x) {
+  x + 1
+}
    +
    +

    The code that is run when you “call” your function is shown inside the curly parentheses. To “call” a function is to write the name of the function, followed by some parentheses inside which you provide a value for your argument, such as:

    +
    +
    add_one(5)
    +
    +
    [1] 6
    +
    +
    +

    What is happening when you call add_one(5) is that x is temporarily being assigned the value 5, and then the code inside the curly parentheses x + 1 is run, with the result being returned as the output of the function.

    +

    Note that by default, any custom R function you create will automatically return the final result that is computed. So for example, if your function contains multiple computations that would have output, such as the version below, when you call add_one(5), you will only see the final computed result (i.e., you will see the output of x + 1 but not x - 1.

    +
    +
    add_one <- function(x) {
+  x - 1
+  x + 1
+}
    +
    +
    +
    add_one(5)
    +
    +
    [1] 6
    +
    +
    +

    For this reason, it is common to explicitly provide a “return statement”, which specifies what you want the output of your function to be. In the example below, we explicitly specify that we want the output of add_one() to be the output of the first computation x - 1, rather than the second one, x + 1.

    +
    +
    add_one <- function(x) {
+  return(x - 1)
+  x + 1
+}
    +
    +
    +
    add_one(5)
    +
    +
    [1] 4
    +
    +
    +
    +
    +

    The general syntax of a custom function

    +

    The general syntax of a custom function is shown below:

    +
    +
    fn_name <- function(arg) {
+  # code involve arg
+  return(object)
+}
    +
    +
    +
    +

    Exercise

    +

    Write a function called “cube” that returns the cubic of the argument

    +
    +
    cube <- function(value) {
+  cubed_value = value^3
+  return(cubed_value)
+}
    +
    +
    +
    cube(value = 3)
    +
    +
    [1] 27
    +
    +
    +
    +
    +

    Multiple arguments

    +

    To create a function with multiple arguments, you need to provide two arguments inside the function definition, separated by a comma. The function below has two arguments: x and y:

    +
    +
    add_xy <- function(x, y) {
+  x + 2*y
+}
    +
    +

    When you call this add_xy(), you can then specify a value for each argument, separated by a comma:

    +
    +
    add_xy(2, 5)
    +
    +
    [1] 12
    +
    +
    +

    When you have multiple arguments, funny things can start to happen when you don’t name your arguments.

    +

    What do you think will happen if you first provide a named argument for the second argument y by specifying y = 2, and then provide an unnamed argument afterwards?

    +
    +
    add_xy(y = 2, 5)
    +
    +
    [1] 9
    +
    +
    +

    R will be clever and it will first apply the named arguments by assigning y to the value 2, and then it will start at the beginning of the argument list and fill in the remaining argument, so x will be assigned to the value 5.

    +

    However, so that your code is easy to read and you don’t have to remember which arguments appear in which order, it is good practice to always name your arguments.

    +
    +
    add_xy(x = 2, y = 5)
    +
    +
    [1] 12
    +
    +
    +

    Note that when you provide named arguments, it technically doesn’t matter which order you provide them in (but this is not true when you don’t provide named arguments!)

    +
    +
    add_xy(y = 5, x = 2)
    +
    +
    [1] 12
    +
    +
    +

    Again, note that even when you provide named arguments in a function call (e.g., in add_xy(y = 5, x = 2)), you are not defining a global version of the arguments, i.e., there is no y defined:

    +
    +
    y
    +
    +
    Error in eval(expr, envir, enclos): object 'y' not found
    +
    +
    +

    Before we move on, what do you think will happen when you call add_xy() without any arguments inside the parentheses?

    +
    +
    add_xy()
    +
    +
    Error in add_xy(): argument "x" is missing, with no default
    +
    +
    +

    You get an error, because we haven’t specified any default values for the arguments which the function will use when an argument is not provided.

    +
    +

    Default values

    +

    To provide default values for your arguments, you can assign the argument inside the function definition. In the example below, both x and y are given the default values of 1.

    +
    +
    add_xy <- function(x = 1, y = 1) {
+  x + 2*y
+}
    +
    +

    Now if we run add_xy() without any arguments, we don’t get an error! We get the same thing that we would have got if we had run add_xy(x = 1, y = 1).

    +
    +
    add_xy()
    +
    +
    [1] 3
    +
    +
    +

    What do you think will happen if we run add_xy(4)?

    +
    +
    add_xy(4)
    +
    +
    [1] 6
    +
    +
    +

    What happens is that the value 4 is assigned to the first argument, x, and the argument y is assigned it’s default value of 1.

    +

    Similarly, if you provide a value for the argument y, the default value for x will be used:

    +
    +
    add_xy(y = 3)
    +
    +
    [1] 7
    +
    +
    +
    +
    +

    Exercise

    +

    Without using the mean() function, write a function called my_mean() that takes four values as its arguments and computes their mean. Ensure that each argument has a default of 0. Use your function to compute the mean of the values 4, 5, 2, 1.

    +
    +

    Solution

    +
    +
    my_mean <- function(a = 0, b = 0, c = 0, d = 0) {
+  return((a + b + c + d) / 4)
+}
    +
    +

    Note that when we run this function it is taking four separate arguments (rather than a vector, as the original mean function does):

    +
    +
    my_mean(4, 5, 2, 1)
    +
    +
    [1] 3
    +
    +
    +

    You can define a function that instead takes a single vector as its argument:

    +
    +
    my_mean_vec <- function(vec) {
+  return(sum(vec) / length(vec))
+}
    +
    +

    and then to run this function, you provide a vector by wrapping the four values inside c():

    +
    +
    my_mean_vec(c(4, 5, 2, 1))
    +
    +
    [1] 3
    +
    +
    +

    What happens if you apply your original my_mean() function to this vector?

    +
    +
    my_mean(c(4, 5, 2, 1))
    +
    +
    [1] 1.00 1.25 0.50 0.25
    +
    +
    +

    This is equivalent to assigning the argument a = c(4, 5, 2, 1), and then not providing any values for the b, c, and d arguments (so their default values are used). So the above code is equivalent to:

    +
    +
    # (a + b + c + d) / 4
+
+(c(4, 5, 2, 1) + 0 + 0 + 0) / 4
    +
    +
    [1] 1.00 1.25 0.50 0.25
    +
    +
    +

    The fact that we haven’t told any of our functions what type of object the arguments should be means that the function will simply take whatever object it is given and try and run the code. In the next lesson, you will learn how to specify options for arguments using if/else statements and by providing several argument defaults.

    +
    +
    +
    +
    +

    If/else statements

    +

    First, let’s explain what an if statement and an if/else statement is.

    +
    +

    If statements

    +

    Let’s start with a stand-alone “if” statement.

    +

    The following code defines a variable a, and then runs some conditional code that is only run if the condition a == 1 is TRUE. In this case, since a contains the value 5, the condition a == 1 is FALSE, and so the code "a is 1" is not run.

    +
    +
    a <- 5
+
+if (a == 1) {
+  "a is 1"
+}
    +
    +

    If instead, we assign a to 1, then the code "a is 1" will be run:

    +
    +
    a <- 1
+
+if (a == 1) {
+  "a is 1"
+}
    +
    +
    [1] "a is 1"
    +
    +
    +

    There is nothing special about the string value provided, it is just a simple piece of code. We could instead just run code containing a numeric value:

    +
    +
    a <- 1
+
+if (a == 1) {
+  3
+}
    +
    +
    [1] 3
    +
    +
    +

    Or even define a variable inside our “if” statement:

    +
    +
    a <- 1
+
+if (a == 1) {
+  y <- 3
+}
    +
    +

    Note that unlike for a function, this variable will have been defined in our “global” environment.

    +
    +
    y
    +
    +
    [1] 3
    +
    +
    +
    +
    +

    Else statemenets

    +

    While you can use a stand-alone “if” statement, you can also provide an “else” statement. The “else” part of the “if/else” statement provides some code that will be run if the “if” condition is not TRUE. For example, the following code will first ask if a equals 1, and if so, will assign y <- 3. If not, the statement will not run the y <- 3 code and will instead assign y <- 9:

    +
    +
    a <- 3
+if (a == 1) {
+  # if condition is true, run the following:
+  y <- 3
+} else {
+  # if condition is not true, run the following:
+  y <- 9
+}
    +
    +
    +
    # check what y was assigned to
+y
    +
    +
    [1] 9
    +
    +
    +
    +
    +

    Using “if” statements to provide custom errors when inappropriate arguments are provided

    +

    The following uses an “if” statement to add a “stop condition” that throws an error when the argument a is either non-numeric or does not have a length of 1:

    +
    +
    my_mean <- function(a = 0, b = 0, c = 0, d = 0) {
+  if (!is.numeric(a) | (length(a) != 1)) {
+    stop("'a' must be a numeric value of length 1")
+  }
+  
+  return((a + b + c + d) / 4)
+}
    +
    +
    +
    +

    Exercise

    +
      +
    1. Use an if/else statement that checks whether the value in a variable called age is at least 18. If so, your statement should return the character value of “You are eligible to vote” and if not, your statement should return “You are not eligible to vote”
      2. +
    +
    +
    age <- 21
+if (age >= 18) {
+  "You are eligible to vote"
+} else {
+  "You are not eligible to vote"
+}
    +
    +
    [1] "You are eligible to vote"
    +
    +
    +
      +
    1. Write a function that computes the area of a circle (area = pi * radius^2) given the radius as its argument and throws an error if a non-numeric or a negative radius value is given.
      2. +
    +
    +
    circle_area <- function(radius) {
+  if (!is.numeric(radius) | radius < 0) {
+    stop("'radius' must be a non-negative numeric value")
+  }
+  area <- pi * radius^2
+  return(area)
+}
    +
    +
    +
    # the following should throw an error:
+circle_area("4")
    +
    +
    Error in circle_area("4"): 'radius' must be a non-negative numeric value
    +
    +
    circle_area(-4)
    +
    +
    Error in circle_area(-4): 'radius' must be a non-negative numeric value
    +
    +
    +
    +
    +
    +

    Default argument options

    +
    +
    add_xy <- function(x = 1, y = 1, output_type = c("numeric", "character")) {
+  # this line will set the default value of output_type to be "numeric"
+  # and will only allow options provided in the default vector
+  output_type <- match.arg(output_type)
+  
+  # stop condition if x or y are not numeric
+  if (!is.numeric(x) | !is.numeric(y)) {
+    stop("'x' and 'y' must be numeric")
+  }
+  
+  # computing my result
+  result <- x + 2 * y
+  
+  # returning result in the format specified by output_type
+  if (output_type == "numeric") {
+    return(result)
+  } else if (output_type == "character") {
+    return(as.character(result))
+  }
+  
+}
    +
    +
    +
    add_xy(x = 2, y = 3, output_type = "character")
    +
    +
    [1] "8"
    +
    +
    +
    +
    add_xy(2, 3)
    +
    +
    [1] 8
    +
    +
    +
    +
    add_xy(2, 3, output_type = "charcter")
    +
    +
    Error in match.arg(output_type): 'arg' should be one of "numeric", "character"
    +
    +
    +
    +

    Exercise

    +

    Write a function called calculate_area() that will calculate the area of the shape specified in the argument shape, which has options “circle”, “square”, and “triangle”. Your function will need to have the following additional arguments:

    +
      +

    • radius for computing the area of a circle (pi * radius^2),

      • +

    • side for computing the area of a square (side^2),

      • +

    • base and height for computing the area of a triangle (height * base / 2).

      • +
    +

    Recall that arguments that are not always required should have a default value. Your function should throw an error when you fail to provide the arguments that are needed for the value specified in the shape argument.

    +
    +
    calculate_area <- function(shape = c("circle", "square", "triangle"),
+                           radius = NA,
+                           side = NA,
+                           base = NA,
+                           height = NA) {
+  shape = match.arg(shape)
+  # error statements
+  if (shape == "circle" & is.na(radius)) {
+    stop("'radius' required for 'circle' shape")
+  } 
+  if (shape == "square" & is.na(side)) {
+    stop("'side' required for 'square' shape")
+  }
+  if (shape == "triangle" & (is.na(base) | is.na(height))) {
+    stop("'base' and 'height' required for 'triangle' shape")
+  }
+  
+  # compute the area
+  if (shape == "circle") {
+    area <- pi * radius^2
+  } else if (shape == "square") {
+    area <- side^2
+  } else if (shape == "triangle") {
+    area <- base * height / 2
+  }
+  
+  return(area)
+  
+}
    +
    +
    +
    +
    +

    Tidy evaluation for writing tidyverse-style functions

    +

    Sometimes you want to write a function whose argument is a column of a data frame without quotes (i.e., in the tidyverse style) so that you can use it in a tidyverse function. Unfortunately this is more complicated than it should be, but in this lesson, you’ll learn how to implement “tidy evaluation” so that your function can take tidyverse-style column-name arguments to use in tidyverse functions.

    +

    First, we have to load in the tidyverse. And we will also load in the demographics data file from the NHANES study. You will need to make sure that your data/ folder and demographics.csv file are saved in the same location as this quarto document, and that your working directory is appropriate (if not, you can choose Session > Set Working Directory > To Source File Location). If you’re using a project, then your working directory should already be set to the correct location.

    +
    +
    library(tidyverse)
    +
    +
    ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
+✔ dplyr     1.1.4     ✔ readr     2.1.5
+✔ forcats   1.0.0     ✔ stringr   1.5.1
+✔ ggplot2   3.5.1     ✔ tibble    3.2.1
+✔ lubridate 1.9.3     ✔ tidyr     1.3.1
+✔ purrr     1.0.2     
+── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
+✖ dplyr::filter() masks stats::filter()
+✖ dplyr::lag()    masks stats::lag()
+ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
    +
    +
    demographics <- read_csv("data/demographics.csv")
    +
    +
    Rows: 10175 Columns: 19
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (5): interview_examination, gender, race, marital_status, pregnant
+dbl (9): respondent_id, age_years, age_months_sc_0_2yr, six_month_period, ag...
+lgl (5): served_active_duty_us, served_active_duty_foreign, born_usa, citize...
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
    +
    +
    +
    head(demographics)
    +
    +
    # A tibble: 6 × 19
+  respondent_id interview_examination gender age_years age_months_sc_0_2yr race 
+          <dbl> <chr>                 <chr>      <dbl>               <dbl> <chr>
+1         73557 both interview and e… male          69                  NA black
+2         73558 both interview and e… male          54                  NA white
+3         73559 both interview and e… male          72                  NA white
+4         73560 both interview and e… male           9                  NA white
+5         73561 both interview and e… female        73                  NA white
+6         73562 both interview and e… male          56                  NA mexi…
+# ℹ 13 more variables: six_month_period <dbl>, age_months_ex_0_19yr <dbl>,
+#   served_active_duty_us <lgl>, served_active_duty_foreign <lgl>,
+#   born_usa <lgl>, citizen_usa <lgl>, time_in_us <dbl>, education_youth <dbl>,
+#   education <dbl>, marital_status <chr>, pregnant <chr>,
+#   language_english <lgl>, household_income <dbl>
    +
    +
    +

    So a reminder of the kinds of things we will often do within the tidyverse is creating figures, such as boxplots, using ggplot2 based on a data frame. Notice that when we refer to the variables from our data frame in the context of the tidyverse (including ggplot2), we do not use quotes around the column names:

    +
    +
    demographics |> ggplot() +
+  geom_boxplot(aes(x = served_active_duty_us,
+                   y = age_years))
    +
    +
    +
    +

    +
    +
    +
    +
    +

    Here is another example using a different variable from the data (language_english), where we also add a “classic” theme, and some custom axis labels.

    +
    +
    demographics |> ggplot() +
+  geom_boxplot(aes(x = language_english,
+                   y = age_years)) + 
+  theme_classic() +
+  labs(x = "English language",
+       y = "Age (years)")
    +
    +
    +
    +

    +
    +
    +
    +
    +

    Let’s try and turn this into a function so we can create boxplots comparing the age distribution across all of the levels of any categorical varaible in our data that we like without having to copy-and-paste the code over and over again.

    +

    In this first attempt, we use variable_name as the argument:

    +
    +
    createBoxplots <- function(variable_name) {
+  demographics |> ggplot() +
+    geom_boxplot(aes(x = variable_name,
+                     y = age_years)) 
+}
    +
    +

    But this yields an error where R claims that it doesn’t know what language_english is. Which to be fair, since it isn’t the name of a variable in our space, it doesn’t!

    +
    +
    createBoxplots(language_english)
    +
    +
    Error in `geom_boxplot()`:
+! Problem while computing aesthetics.
+ℹ Error occurred in the 1st layer.
+Caused by error:
+! object 'language_english' not found
    +
    +
    +

    We can try and run it with a character/string verion of the column name by wrapping it in quotes, but then we just get one boxplot for the string value "language_english", which ggplot doesn’t know is supposed to be a column from our data.

    +
    +
    createBoxplots("language_english")
    +
    +
    +
    +

    +
    +
    +
    +
    +

    The issue is that ggplot wants us to refer to the column names without strings, but our custom function doesn’t know how to find our column name variable that we provide.

    +

    Fortunately, there is an easy fix, which involves something called “tidy evaluation”, which involves wrapping the argument inside two sets of curly parentheses inside the body of our function, which indicates to R that this argument should be used in the tidyverse style, without quotes:

    +
    +
    createBoxplots <- function(variable_name) {
+  demographics |> ggplot() +
+    geom_boxplot(aes(x = {{ variable_name }},
+                     y = age_years)) 
+}
    +
    +

    And now it works:

    +
    +
    createBoxplots(language_english)
    +
    +
    +
    +

    +
    +
    +
    +
    +

    Let’s use our function on a few different columns to make sure:

    +
    +
    createBoxplots(marital_status)
    +
    +
    +
    +

    +
    +
    +
    +
    +

    Notice that in the marital status plot, the x-axis tick labels are all smooshed into eachother. We deal with this by adding a theme layer to our plot which modifies the properties of the axis.text.x theme element. We can add this either to output of createBoxplots() (which outputs a ggplot2 object itself):

    +
    +
    createBoxplots(marital_status) + 
+  theme(axis.text.x = element_text(angle = 90, 
+                                   hjust = 1, 
+                                   vjust = 0.5))
    +
    +
    +
    +

    +
    +
    +
    +
    +

    Or we can apply it to all plots created with our createBoxplot() function by including it in the function body:

    +
    +
    createBoxplots <- function(variable_name) {
+  demographics |> ggplot() +
+    geom_boxplot(aes(x = {{ variable_name }},
+                     y = age_years)) + 
+    theme_classic() +
+    theme(axis.text.x = element_text(angle = 90, 
+                                   hjust = 1, 
+                                   vjust = 0.5))
+}
    +
    +
    +
    # now this version will have the 90-degree axis text
+createBoxplots(marital_status)
    +
    +
    +
    +

    +
    +
    +
    +
    +
    +

    Adding labels using column variable names

    +

    Sometimes you want to take the name of the column name that you are providing in the argument and use the actual text from the column name to create a nice label. The last line in the version of our function below converts the variable_name to a text-based object and uses the str_replace function from the tidyverse to replace the underscore with a space:

    +
    +
    createBoxplots <- function(variable_name) {
+  demographics |> ggplot() +
+    geom_boxplot(aes(x = {{ variable_name }},
+                     y = age_years)) + 
+    theme_classic() +
+    theme(axis.text.x = element_text(angle = 90, 
+                                   hjust = 1, 
+                                   vjust = 0.5)) +
+    labs(x = str_replace(as_label(enquo(variable_name)), "_", " "),
+         y = "Age (years)") 
+}
    +
    +
    +
    createBoxplots(marital_status)
    +
    +
    +
    +

    +
    +
    +
    +
    +
    +
    +

    Tip: Using patchwork to patch together plots

    +

    The patchwork library can be used to create custom grids of ggplot objects (be sure to expand your plot window if the plots aren’t showing up properly):

    +
    +
    library(patchwork)
+createBoxplots(language_english) + createBoxplots(marital_status)
    +
    +
    +
    +

    +
    +
    +
    +
    +
    +
    (createBoxplots(language_english) + createBoxplots(marital_status)) / createBoxplots(pregnant)
    +
    +
    +
    +

    +
    +
    +
    +
    +
    +
    +

    Exercise

    +

    Create a function called createOrderedBars() that takes a categorical column from demographics as its argument and creates a bar chart for the average age for each level of the variable.

    +

    Challenge mode: Arrange the bars in ascending order, and provide an argument called ascending that allows the user to specify whether or not the bars will be arranged in ascending order.

    +
    +

    Solution

    +

    Note that you’ll want to use geom_col() instead of geom_bar() to create bar charts where the bars have the specific height provided in the y-variable.

    +
    +
    createOrderedBars <- function(variable_name) {
+  demographics |> 
+    # group by the column provided
+    group_by({{ variable_name }}) |>
+    # compute the mean age
+    summarize(mean_age = mean(age_years)) |>
+  # create the bar plot
+    ggplot() +
+    geom_col(aes(x = {{ variable_name }}, 
+                y = mean_age))
+}
    +
    +
    +
    createOrderedBars(marital_status)
    +
    +
    +
    +

    +
    +
    +
    +
    +
    +
    +

    Challenge solution

    +

    To arrange the bars in ascending order of mean_age, you first need to convert the categorical variable itself to a factor whose levels are in the order that you want the bars to appear. You can do this by arranging the rows of your data frame in order of mean_age and then using fct_inorder() to convert your variable to a factor with levels match the increasing order of mean_age.

    +
    +
    createOrderedBars <- function(variable_name) {
+  demographics |> 
+    # group by the column provided
+    group_by({{ variable_name }}) |>
+    # compute the mean age
+    summarize(mean_age = mean(age_years)) |>
+
+    # OPTIONAL CODE FOR CHALLENGE MODE:
+    # arrange in increasing order of mean_age 
+    arrange(mean_age) |>
+    # modify selected_variable so that it is a factor whose levels are in 
+    # increasing order of mean_age  
+    mutate(selected_variable = fct_inorder({{ variable_name }})) |>
+    
+  # create the bar plot
+    ggplot() +
+    geom_col(aes(x = selected_variable, 
+                y = mean_age))
+}
    +
    + + +
    +
    +
    + +
    + +
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Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +

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    Iteration with purrr

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    The purpose of this lesson is to learn how to iteratively apply functions to all elements contained within an object, such as all columns in a data frame, or all entries in a vector.

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    Since we will be continuing with the demographics NHANES data we were using previously, we will first need to load in that dataset. To do that, we will also need to load the tidyverse library.

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    Note that the “purrr” R package that we will be using in this lesson is included in the tidyverse package, so that it it not necessary to also load the purrr package separately.

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    library(tidyverse)
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    ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
+✔ dplyr     1.1.4     ✔ readr     2.1.5
+✔ forcats   1.0.0     ✔ stringr   1.5.1
+✔ ggplot2   3.5.1     ✔ tibble    3.2.1
+✔ lubridate 1.9.3     ✔ tidyr     1.3.1
+✔ purrr     1.0.2     
+── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
+✖ dplyr::filter() masks stats::filter()
+✖ dplyr::lag()    masks stats::lag()
+ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
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    #library(purrr)
+demographics <- read_csv("data/demographics.csv")
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    Rows: 10175 Columns: 19
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (5): interview_examination, gender, race, marital_status, pregnant
+dbl (9): respondent_id, age_years, age_months_sc_0_2yr, six_month_period, ag...
+lgl (5): served_active_duty_us, served_active_duty_foreign, born_usa, citize...
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
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    +

    To start with, the function that we want to iterate first is the n_distinct() function from the tidyverse.

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    Recall that to pull up the help page for a function, you can use the following syntax:

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    ?n_distinct
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    n_distinct() counts the number of unique values in a vector. For example, if we want to apply n_distinct() to count the number of unique values in the gender column from the demographics data frame, we can first extract it as a vector using demographics$gender and then apply n_distinct() to it:

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    n_distinct(demographics$gender)
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    [1] 2
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    +
    +

    What if we want to do this simultaneously to all columns. Rather than repeating our code above over and over again, we can instead use the map() function.

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    The map() function takes two arguments. The first is the object whose elements that we want to iterate over and the second is the function that we want to apply to each element in our object.

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    When our object is a data frame, the elements being iterated over are the columns of the data frame.

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    The code below uses the map() function to apply n_distinct() to every column of the demographics data frame simultanesouly:

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    map(demographics, n_distinct)
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    $respondent_id
+[1] 10175
+
+$interview_examination
+[1] 2
+
+$gender
+[1] 2
+
+$age_years
+[1] 81
+
+$age_months_sc_0_2yr
+[1] 26
+
+$race
+[1] 6
+
+$six_month_period
+[1] 3
+
+$age_months_ex_0_19yr
+[1] 241
+
+$served_active_duty_us
+[1] 3
+
+$served_active_duty_foreign
+[1] 3
+
+$born_usa
+[1] 3
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+$citizen_usa
+[1] 3
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+$time_in_us
+[1] 10
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+$education_youth
+[1] 16
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+$education
+[1] 6
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+$marital_status
+[1] 7
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+$pregnant
+[1] 4
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+$language_english
+[1] 2
+
+$household_income
+[1] 13
    +
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    The output of the map() function is a list (more on that in a moment).

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    The following code shows another example, this time applying the exp() function to all entries/elements in a simple numeric vector:

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    map(c(4, 5, 6), exp)
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    [[1]]
+[1] 54.59815
+
+[[2]]
+[1] 148.4132
+
+[[3]]
+[1] 403.4288
    +
    +
    +

    Again, the output of the map() function is a list.

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    Lists

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    Let’s talk about lists. Lists, like vectors, correspond to a collection of values contained in a single object.

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    You can use the list() function to define a list, for example:

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    my_list <- list(1, 4, 7)
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    You can extract elements from a list just as you would from a vector, using the square bracket notation. The code below extracts the third element from my_list:

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    my_list[3]
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    [[1]]
+[1] 7
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    However, note that the output above is also a list itself.

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    If you want to extract the actual object/value contained within the third element of the list, then you need to use double square parentheses:

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    my_list[[3]]
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    [1] 7
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    Note that unlike vectors, lists are not vectorized. This means that you cannot conduct operations like adding 1 to a list. For a vector, this would add 1 to each element of the vector. But for a list, you just get an error:

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    my_list + 1
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    Error in my_list + 1: non-numeric argument to binary operator
    +
    +
    +

    Why would we ever prefer lists to vectors? The reason is that lists are infinitely more flexible than vectors. While all entries in a vector must be a single value of the same type, entries of a list can be anything.

    +

    For example, the code below creates a list that contains three entries: the head of the demographics data frame, the value 2, and a vector of the character values “a” and “b”:

    +
    +
    my_complex_list <- list(head(demographics), 2, c("a", "b"))
+my_complex_list
    +
    +
    [[1]]
+# A tibble: 6 × 19
+  respondent_id interview_examination gender age_years age_months_sc_0_2yr race 
+          <dbl> <chr>                 <chr>      <dbl>               <dbl> <chr>
+1         73557 both interview and e… male          69                  NA black
+2         73558 both interview and e… male          54                  NA white
+3         73559 both interview and e… male          72                  NA white
+4         73560 both interview and e… male           9                  NA white
+5         73561 both interview and e… female        73                  NA white
+6         73562 both interview and e… male          56                  NA mexi…
+# ℹ 13 more variables: six_month_period <dbl>, age_months_ex_0_19yr <dbl>,
+#   served_active_duty_us <lgl>, served_active_duty_foreign <lgl>,
+#   born_usa <lgl>, citizen_usa <lgl>, time_in_us <dbl>, education_youth <dbl>,
+#   education <dbl>, marital_status <chr>, pregnant <chr>,
+#   language_english <lgl>, household_income <dbl>
+
+[[2]]
+[1] 2
+
+[[3]]
+[1] "a" "b"
    +
    +
    +

    You can also create a named list when defining it as if you are defining argument names:

    +
    +
    my_complex_list <- list(data = head(demographics), value = 2, vector = c("a", "b"))
+my_complex_list
    +
    +
    $data
+# A tibble: 6 × 19
+  respondent_id interview_examination gender age_years age_months_sc_0_2yr race 
+          <dbl> <chr>                 <chr>      <dbl>               <dbl> <chr>
+1         73557 both interview and e… male          69                  NA black
+2         73558 both interview and e… male          54                  NA white
+3         73559 both interview and e… male          72                  NA white
+4         73560 both interview and e… male           9                  NA white
+5         73561 both interview and e… female        73                  NA white
+6         73562 both interview and e… male          56                  NA mexi…
+# ℹ 13 more variables: six_month_period <dbl>, age_months_ex_0_19yr <dbl>,
+#   served_active_duty_us <lgl>, served_active_duty_foreign <lgl>,
+#   born_usa <lgl>, citizen_usa <lgl>, time_in_us <dbl>, education_youth <dbl>,
+#   education <dbl>, marital_status <chr>, pregnant <chr>,
+#   language_english <lgl>, household_income <dbl>
+
+$value
+[1] 2
+
+$vector
+[1] "a" "b"
    +
    +
    +
    +
    +

    Exercise

    +

    Use map() and class() to identify the type/class of each column in the demographics dataset, and extract the class of the household_income column.

    +
    +

    Solution

    +
    +
    demographics_class <- map(demographics, class)
    +
    +

    The household_income is the last column in the demographics data frame. There are several ways to extract it’s class from the demographics_class list object.

    +

    First is using numeric positional indexing inside square parentheses. Tip: You can use ncol(demographics) to extract the final column without having to actually know what integer position the final column corresponds to:

    +
    +
    demographics_class[ncol(demographics)]
    +
    +
    $household_income
+[1] "numeric"
    +
    +
    demographics_class[19]
    +
    +
    $household_income
+[1] "numeric"
    +
    +
    +

    You can also use named indexing, by providing the list element name as a character inside one or two square parentheses (depending if you want the output to be a list of length 1 or just the value contained in the list element):

    +
    +
    demographics_class[["household_income"]]
    +
    +
    [1] "numeric"
    +
    +
    +

    And you can also use the $ syntax with the list element name (without quotes).

    +
    +
    demographics_class$household_income
    +
    +
    [1] "numeric"
    +
    +
    +

    Note that these are the same techniques that you can use for extracting a column from a data frame. This is because a data frame is actually a special case of a list, where each element of the list is a vector corresponding to each column, and each of the vectors have the same length.

    +
    +
    +
    +

    Using custom functions in purrr

    +

    To iterate using your own custom functions in a purrr map() function, you can define your function and provide it in the second argument of map(). For example, below, we define the exp_plus_one() function, and we then apply this function iteratively to each of the values in the vector c(1, 4, 5) using map():

    +
    +
    exp_plus_one <- function(x) {
+  return(exp(x) + 1)
+}
+
+map(c(1, 4, 5), exp_plus_one)
    +
    +
    [[1]]
+[1] 3.718282
+
+[[2]]
+[1] 55.59815
+
+[[3]]
+[1] 149.4132
    +
    +
    +

    However, for simple functions like this one (e.g., functions that only involve a single line of code which is also the return statement), there is a shortcut that we can use which involves defining the function “on the fly” in the function argument of the map() function itself.

    +

    The code below does the same thing as the code in the previous chunk, but it doesn’t give the function a name. A temporary function defined inside an argument this way is called an “anonymous function”:

    +
    +
    map(c(1, 4, 5), function(x) exp(x) + 1)
    +
    +
    [[1]]
+[1] 3.718282
+
+[[2]]
+[1] 55.59815
+
+[[3]]
+[1] 149.4132
    +
    +
    +

    However, we can go one step further and forego the function(x) part entirely using what I call the “tilde-dot” shorthand syntax. Here, we use the tilde ~ symbol to “start” an anonymous function and we use a . to represent the argument of our anonymous function. The code below uses the tilde-dot shorthand syntax which is equivalent to the code in each of the chunks above, but is significantly more succinct.

    +
    +
    # tilde-dot syntax
+map(c(1, 4, 5), ~{exp(.) + 1})
    +
    +
    [[1]]
+[1] 3.718282
+
+[[2]]
+[1] 55.59815
+
+[[3]]
+[1] 149.4132
    +
    +
    +

    As another example of this shorthand syntax, we can use it to count the number of missing values in each column of the demographics data (which is defined/loaded in the first code chunk of this document).

    +

    To decide what should go inside the ~{}, I typically use a representative value to test out my code first. For example, below, I take a single column demographics$pregnant, and I write out the code that I want to apply to it:

    +
    +
    sum(is.na(demographics$pregnant))
    +
    +
    [1] 8866
    +
    +
    +

    Then I take this code and place it inside the body of ~{} and replace the test column demographics$pregnant with a . to apply this code to every column:

    +
    +
    map(demographics, ~{sum(is.na(.))})
    +
    +
    $respondent_id
+[1] 0
+
+$interview_examination
+[1] 0
+
+$gender
+[1] 0
+
+$age_years
+[1] 0
+
+$age_months_sc_0_2yr
+[1] 9502
+
+$race
+[1] 0
+
+$six_month_period
+[1] 362
+
+$age_months_ex_0_19yr
+[1] 5962
+
+$served_active_duty_us
+[1] 3915
+
+$served_active_duty_foreign
+[1] 9633
+
+$born_usa
+[1] 5
+
+$citizen_usa
+[1] 11
+
+$time_in_us
+[1] 8353
+
+$education_youth
+[1] 7373
+
+$education
+[1] 4413
+
+$marital_status
+[1] 4409
+
+$pregnant
+[1] 8866
+
+$language_english
+[1] 0
+
+$household_income
+[1] 783
    +
    +
    +
    +

    Exercise

    +

    Use the tilde-dot short-hand syntax to compute the number of values in each column that is equal to 1. Recall that if a vector has missing values, and you want to use sum(), you will want to provide an argument na.rm = TRUE to ignore missing values.

    +
    +

    Solution

    +

    First, the code below does the long-form version which defines a function and then provides that function in the second argument of the map() function:

    +
    +
    add_ones <- function(x) {
+  sum(x == 1, na.rm = TRUE)
+}
+
+map(demographics, add_ones)
    +
    +
    $respondent_id
+[1] 0
+
+$interview_examination
+[1] 0
+
+$gender
+[1] 0
+
+$age_years
+[1] 262
+
+$age_months_sc_0_2yr
+[1] 42
+
+$race
+[1] 0
+
+$six_month_period
+[1] 4823
+
+$age_months_ex_0_19yr
+[1] 30
+
+$served_active_duty_us
+[1] 543
+
+$served_active_duty_foreign
+[1] 282
+
+$born_usa
+[1] 8262
+
+$citizen_usa
+[1] 9220
+
+$time_in_us
+[1] 0
+
+$education_youth
+[1] 237
+
+$education
+[1] 455
+
+$marital_status
+[1] 0
+
+$pregnant
+[1] 0
+
+$language_english
+[1] 9100
+
+$household_income
+[1] 0
    +
    +
    +

    Then I make this more concise by taking the body of my add_ones() function above, and placing it inside ~{}, and replace the x argument with a .:

    +
    +
    map(demographics, ~{sum(. == 1, na.rm = TRUE)})
    +
    +
    $respondent_id
+[1] 0
+
+$interview_examination
+[1] 0
+
+$gender
+[1] 0
+
+$age_years
+[1] 262
+
+$age_months_sc_0_2yr
+[1] 42
+
+$race
+[1] 0
+
+$six_month_period
+[1] 4823
+
+$age_months_ex_0_19yr
+[1] 30
+
+$served_active_duty_us
+[1] 543
+
+$served_active_duty_foreign
+[1] 282
+
+$born_usa
+[1] 8262
+
+$citizen_usa
+[1] 9220
+
+$time_in_us
+[1] 0
+
+$education_youth
+[1] 237
+
+$education
+[1] 455
+
+$marital_status
+[1] 0
+
+$pregnant
+[1] 0
+
+$language_english
+[1] 9100
+
+$household_income
+[1] 0
    +
    +
    +
    +
    +
    +
    +

    Alternative map functions for outputting doubles, characters and data frames

    +

    Let’s explore some alternative map functions that have different output types (i.e., they do not output a list).

    +

    Recall our map() function previously that we used to count the number of missing values in each column of the demographics data.

    +
    +
    map(demographics, ~sum(is.na(.)))
    +
    +
    $respondent_id
+[1] 0
+
+$interview_examination
+[1] 0
+
+$gender
+[1] 0
+
+$age_years
+[1] 0
+
+$age_months_sc_0_2yr
+[1] 9502
+
+$race
+[1] 0
+
+$six_month_period
+[1] 362
+
+$age_months_ex_0_19yr
+[1] 5962
+
+$served_active_duty_us
+[1] 3915
+
+$served_active_duty_foreign
+[1] 9633
+
+$born_usa
+[1] 5
+
+$citizen_usa
+[1] 11
+
+$time_in_us
+[1] 8353
+
+$education_youth
+[1] 7373
+
+$education
+[1] 4413
+
+$marital_status
+[1] 4409
+
+$pregnant
+[1] 8866
+
+$language_english
+[1] 0
+
+$household_income
+[1] 783
    +
    +
    +

    It turns out that a list may not be the most useful format for this information. For instance, perhaps it would be more helpful to create a numeric vector instead.

    +
    +

    Outputting numeric vectors

    +

    The map_dbl() function will output a “double” vector, where a double is a type of numeric value. Below, is the same code from above, but using map_dbl() outputs a named numeric/double vector, instead of a list (where the name of each element is inherited from the column names of the original data frame).

    +
    +
    map_dbl(demographics, ~sum(is.na(.)))
    +
    +
                 respondent_id      interview_examination 
+                         0                          0 
+                    gender                  age_years 
+                         0                          0 
+       age_months_sc_0_2yr                       race 
+                      9502                          0 
+          six_month_period       age_months_ex_0_19yr 
+                       362                       5962 
+     served_active_duty_us served_active_duty_foreign 
+                      3915                       9633 
+                  born_usa                citizen_usa 
+                         5                         11 
+                time_in_us            education_youth 
+                      8353                       7373 
+                 education             marital_status 
+                      4413                       4409 
+                  pregnant           language_english 
+                      8866                          0 
+          household_income 
+                       783
    +
    +
    +
    +
    +

    Outputting character vectors

    +

    If you are applying a function whose output is a character value (not a numeric value), such as class(), then you can use the map_chr() function to output a named character vector instead.

    +
    +
    map_chr(demographics, class)
    +
    +
                 respondent_id      interview_examination 
+                 "numeric"                "character" 
+                    gender                  age_years 
+               "character"                  "numeric" 
+       age_months_sc_0_2yr                       race 
+                 "numeric"                "character" 
+          six_month_period       age_months_ex_0_19yr 
+                 "numeric"                  "numeric" 
+     served_active_duty_us served_active_duty_foreign 
+                 "logical"                  "logical" 
+                  born_usa                citizen_usa 
+                 "logical"                  "logical" 
+                time_in_us            education_youth 
+                 "numeric"                  "numeric" 
+                 education             marital_status 
+                 "numeric"                "character" 
+                  pregnant           language_english 
+               "character"                  "logical" 
+          household_income 
+                 "numeric"
    +
    +
    +
    +
    +

    Outputting data frames

    +

    One of the most versatile functions is the map_df() function, which outputs a data frame. The code below outputs the class of each column in a “wide” single-row data frame, where each column in the original data frame has its own column in the output here.

    +
    +
    map_df(demographics, class)
    +
    +
    # A tibble: 1 × 19
+  respondent_id interview_examination gender age_years age_months_sc_0_2yr race 
+  <chr>         <chr>                 <chr>  <chr>     <chr>               <chr>
+1 numeric       character             chara… numeric   numeric             char…
+# ℹ 13 more variables: six_month_period <chr>, age_months_ex_0_19yr <chr>,
+#   served_active_duty_us <chr>, served_active_duty_foreign <chr>,
+#   born_usa <chr>, citizen_usa <chr>, time_in_us <chr>, education_youth <chr>,
+#   education <chr>, marital_status <chr>, pregnant <chr>,
+#   language_english <chr>, household_income <chr>
    +
    +
    +

    Note that if you want your output to be in a “long” format, where you have one column for the output of your function, you need to have the function you are applying output a single-column tibble/data frame, and these values will then be stacked vertically as you iterate.

    +
    +
    map_df(demographics, ~tibble(col_class = class(.)))
    +
    +
    # A tibble: 19 × 1
+   col_class
+   <chr>    
+ 1 numeric  
+ 2 character
+ 3 character
+ 4 numeric  
+ 5 numeric  
+ 6 character
+ 7 numeric  
+ 8 numeric  
+ 9 logical  
+10 logical  
+11 logical  
+12 logical  
+13 numeric  
+14 numeric  
+15 numeric  
+16 character
+17 character
+18 logical  
+19 numeric
    +
    +
    +

    You can provide an .id argument to include the original column names as a variable in the output data frame too:

    +
    +
    map_df(demographics, ~tibble(col_class = class(.)), .id = "variable_name")
    +
    +
    # A tibble: 19 × 2
+   variable_name              col_class
+   <chr>                      <chr>    
+ 1 respondent_id              numeric  
+ 2 interview_examination      character
+ 3 gender                     character
+ 4 age_years                  numeric  
+ 5 age_months_sc_0_2yr        numeric  
+ 6 race                       character
+ 7 six_month_period           numeric  
+ 8 age_months_ex_0_19yr       numeric  
+ 9 served_active_duty_us      logical  
+10 served_active_duty_foreign logical  
+11 born_usa                   logical  
+12 citizen_usa                logical  
+13 time_in_us                 numeric  
+14 education_youth            numeric  
+15 education                  numeric  
+16 marital_status             character
+17 pregnant                   character
+18 language_english           logical  
+19 household_income           numeric
    +
    +
    +
    +
    +

    Example

    +

    This long-format is very useful if you want to create a plot, such as a bar chart for the number of missing values (recall that you will need to convert the variable_name column to a factor whose levels are in the order you want them to appear in your plot and you can add theme layers to customize the output of your plot).

    +
    +
    map_df(demographics, 
+       ~tibble(n_missing = sum(is.na(.))), 
+       .id = "variable_name") |>
+  arrange(n_missing) |>
+  mutate(variable_name = fct_inorder(variable_name)) |>
+  ggplot() +
+  geom_col(aes(x = variable_name, y = n_missing)) +
+  scale_y_continuous(expand = c(0, 0)) +
+  theme_classic() +
+  theme(axis.text.x = element_text(angle = 90, 
+                                   hjust = 1,
+                                   vjust = 0.5))
    +
    +
    +
    +

    +
    +
    +
    +
    + + +
    +
    + +
    + +
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    +
    + +
    + +
    + + + + +
    + +
    +
    +

    Across

    +
    + + + +
    + + + + +
    + + + +
    + + +

    In this lesson, we will introduce the across() function, which can be used to apply dplyr functions like mutate, summarize, select, etc to subsets of columns that satisfy certain criteria, such as to all numeric columns, or all columns that start with age_.

    +

    We will continue working with the demographics data, so let’s first load the tidyverse and load the demographics data object.

    +
    +
    library(tidyverse)
    +
    +
    ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
+✔ dplyr     1.1.4     ✔ readr     2.1.5
+✔ forcats   1.0.0     ✔ stringr   1.5.1
+✔ ggplot2   3.5.1     ✔ tibble    3.2.1
+✔ lubridate 1.9.3     ✔ tidyr     1.3.1
+✔ purrr     1.0.2     
+── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
+✖ dplyr::filter() masks stats::filter()
+✖ dplyr::lag()    masks stats::lag()
+ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
    +
    +
    demographics <- read_csv("data/demographics.csv")
    +
    +
    Rows: 10175 Columns: 19
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (5): interview_examination, gender, race, marital_status, pregnant
+dbl (9): respondent_id, age_years, age_months_sc_0_2yr, six_month_period, ag...
+lgl (5): served_active_duty_us, served_active_duty_foreign, born_usa, citize...
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
    +
    head(demographics)
    +
    +
    # A tibble: 6 × 19
+  respondent_id interview_examination gender age_years age_months_sc_0_2yr race 
+          <dbl> <chr>                 <chr>      <dbl>               <dbl> <chr>
+1         73557 both interview and e… male          69                  NA black
+2         73558 both interview and e… male          54                  NA white
+3         73559 both interview and e… male          72                  NA white
+4         73560 both interview and e… male           9                  NA white
+5         73561 both interview and e… female        73                  NA white
+6         73562 both interview and e… male          56                  NA mexi…
+# ℹ 13 more variables: six_month_period <dbl>, age_months_ex_0_19yr <dbl>,
+#   served_active_duty_us <lgl>, served_active_duty_foreign <lgl>,
+#   born_usa <lgl>, citizen_usa <lgl>, time_in_us <dbl>, education_youth <dbl>,
+#   education <dbl>, marital_status <chr>, pregnant <chr>,
+#   language_english <lgl>, household_income <dbl>
    +
    +
    +

    Let’s suppose that our task is to convert all character columns of the demographics data to upper-case. The function that we are trying to apply is the toupper() function.

    +
    +
    toupper("abc")
    +
    +
    [1] "ABC"
    +
    +
    +

    Before introducing across, let’s first see one way that we could do this using the map() functions that we have just learned (there are often multiple ways of doing the same thing):

    +
    +
    # one way to convert all character columns to uppercase
+# creating a boolean/logical vector for identifying character columns
+character_cols <- map_chr(demographics, class) == "character"
+# re-assinging the character columns to an upper-case version of themselves
+demographics[character_cols] <- map_df(demographics[character_cols], toupper)
+demographics
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 BOTH INTERVIEW AND EXAM MALE          69                  NA
+ 2         73558 BOTH INTERVIEW AND EXAM MALE          54                  NA
+ 3         73559 BOTH INTERVIEW AND EXAM MALE          72                  NA
+ 4         73560 BOTH INTERVIEW AND EXAM MALE           9                  NA
+ 5         73561 BOTH INTERVIEW AND EXAM FEMALE        73                  NA
+ 6         73562 BOTH INTERVIEW AND EXAM MALE          56                  NA
+ 7         73563 BOTH INTERVIEW AND EXAM MALE           0                   5
+ 8         73564 BOTH INTERVIEW AND EXAM FEMALE        61                  NA
+ 9         73565 INTERVIEW ONLY          MALE          42                  NA
+10         73566 BOTH INTERVIEW AND EXAM FEMALE        56                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +

    While this works, it is fairly convoluted, is hard to read, and involves defining an intermediate variable (character_cols) – in the tidyverse style, it is generally recommended to avoid defining intermediate variables whenever possible.

    +

    Since the code above modified our demographics data, let’s load it in again to revert demographics to the original unmodified version:

    +
    +
    demographics <- read_csv("data/demographics.csv")
    +
    +
    Rows: 10175 Columns: 19
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (5): interview_examination, gender, race, marital_status, pregnant
+dbl (9): respondent_id, age_years, age_months_sc_0_2yr, six_month_period, ag...
+lgl (5): served_active_duty_us, served_active_duty_foreign, born_usa, citize...
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
    +
    demographics
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +
    +

    Introducing across()

    +

    We could instead do this kind of operation using a mutate() operation in conjunction with across().

    +

    First, if we were to conduct our uppercase operation for just one character column, say, interview_examination, then we could do this using a mutate function as follows:

    +
    +
    # just for the interview_examination column
+demographics |> mutate(interview_examination = toupper(interview_examination))
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 BOTH INTERVIEW AND EXAM male          69                  NA
+ 2         73558 BOTH INTERVIEW AND EXAM male          54                  NA
+ 3         73559 BOTH INTERVIEW AND EXAM male          72                  NA
+ 4         73560 BOTH INTERVIEW AND EXAM male           9                  NA
+ 5         73561 BOTH INTERVIEW AND EXAM female        73                  NA
+ 6         73562 BOTH INTERVIEW AND EXAM male          56                  NA
+ 7         73563 BOTH INTERVIEW AND EXAM male           0                   5
+ 8         73564 BOTH INTERVIEW AND EXAM female        61                  NA
+ 9         73565 INTERVIEW ONLY          male          42                  NA
+10         73566 BOTH INTERVIEW AND EXAM female        56                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +

    To do this for all character columns, you need to provide across() to the argument of your mutate function. The across() function has two arguments:

    +
      +

    • The first argument is a “select statement” that specifies which columns you want to apply your function to. Since we want to apply our toupper function to all character columns, we use the where() function to provide a logical function, which, when applied to all columns, will only output TRUE for the character columns, resulting in them being selected for computation.

      • +

    • The second argument is the function name, toupper, that we want to apply to all columns that are selected as a result of the first argument.

      • +
    +

    The result is that toupper() is applied to all columns where is.character() would result in TRUE:

    +
    +
    demographics |> mutate(across(where(is.character), toupper))
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 BOTH INTERVIEW AND EXAM MALE          69                  NA
+ 2         73558 BOTH INTERVIEW AND EXAM MALE          54                  NA
+ 3         73559 BOTH INTERVIEW AND EXAM MALE          72                  NA
+ 4         73560 BOTH INTERVIEW AND EXAM MALE           9                  NA
+ 5         73561 BOTH INTERVIEW AND EXAM FEMALE        73                  NA
+ 6         73562 BOTH INTERVIEW AND EXAM MALE          56                  NA
+ 7         73563 BOTH INTERVIEW AND EXAM MALE           0                   5
+ 8         73564 BOTH INTERVIEW AND EXAM FEMALE        61                  NA
+ 9         73565 INTERVIEW ONLY          MALE          42                  NA
+10         73566 BOTH INTERVIEW AND EXAM FEMALE        56                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +
    +
    +

    More across examples

    +
    +

    Add 100 to all age_ columns

    +

    Let’s first look at another mutate() example, where this time, we want to add 100 to all columns whose name starts with age_.

    +

    If we were to do this to just the age_years column, our code would look like:

    +
    +
    demographics |> mutate(age_years = age_years + 100)
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male         169                  NA
+ 2         73558 both interview and exam male         154                  NA
+ 3         73559 both interview and exam male         172                  NA
+ 4         73560 both interview and exam male         109                  NA
+ 5         73561 both interview and exam female       173                  NA
+ 6         73562 both interview and exam male         156                  NA
+ 7         73563 both interview and exam male         100                   5
+ 8         73564 both interview and exam female       161                  NA
+ 9         73565 interview only          male         142                  NA
+10         73566 both interview and exam female       156                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +

    To generalize this to all columns that start with age_ using across(), we can use the starts_with() select helper, and apply the anonymous function ~{. + 100}:

    +
    +
    demographics |> mutate(across(starts_with("age_"), ~{. + 100}))
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male         169                  NA
+ 2         73558 both interview and exam male         154                  NA
+ 3         73559 both interview and exam male         172                  NA
+ 4         73560 both interview and exam male         109                  NA
+ 5         73561 both interview and exam female       173                  NA
+ 6         73562 both interview and exam male         156                  NA
+ 7         73563 both interview and exam male         100                 105
+ 8         73564 both interview and exam female       161                  NA
+ 9         73565 interview only          male         142                  NA
+10         73566 both interview and exam female       156                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +
    +
    +

    Convert born_usa and citizen_usa to numeric (binary) columns using ends_with()

    +

    The next example involves convert born_usa and citizen_usa to numeric (binary) columns.

    +
    +
    demographics |> select(born_usa, citizen_usa)
    +
    +
    # A tibble: 10,175 × 2
+   born_usa citizen_usa
+   <lgl>    <lgl>      
+ 1 TRUE     TRUE       
+ 2 TRUE     TRUE       
+ 3 TRUE     TRUE       
+ 4 TRUE     TRUE       
+ 5 TRUE     TRUE       
+ 6 TRUE     TRUE       
+ 7 TRUE     TRUE       
+ 8 TRUE     TRUE       
+ 9 TRUE     TRUE       
+10 TRUE     TRUE       
+# ℹ 10,165 more rows
    +
    +
    +

    Since both born_usa and citizen_usa end with _usa (and they are the only columns to do so), we can use the ends_with() select helper. In this case, to convert the logical TRUE/FALSE values to numeric 0/1 values, the function we are applying is as.numeric(). The code below uses across() to do this:

    +
    +
    demographics |> mutate(across(ends_with("_usa"), as.numeric)) |> 
+  print(width = Inf)
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+   race             six_month_period age_months_ex_0_19yr served_active_duty_us
+   <chr>                       <dbl>                <dbl> <lgl>                
+ 1 black                           1                   NA TRUE                 
+ 2 white                           1                   NA FALSE                
+ 3 white                           2                   NA TRUE                 
+ 4 white                           1                  119 NA                   
+ 5 white                           1                   NA FALSE                
+ 6 mexican american                1                   NA TRUE                 
+ 7 white                           2                    6 NA                   
+ 8 white                           2                   NA FALSE                
+ 9 other hispanic                 NA                   NA FALSE                
+10 white                           1                   NA FALSE                
+   served_active_duty_foreign born_usa citizen_usa time_in_us education_youth
+   <lgl>                         <dbl>       <dbl>      <dbl>           <dbl>
+ 1 TRUE                              1           1         NA              NA
+ 2 NA                                1           1         NA              NA
+ 3 TRUE                              1           1         NA              NA
+ 4 NA                                1           1         NA               3
+ 5 NA                                1           1         NA              NA
+ 6 FALSE                             1           1         NA              NA
+ 7 NA                                1           1         NA              NA
+ 8 NA                                1           1         NA              NA
+ 9 NA                                1           1         NA              NA
+10 NA                                1           1         NA              NA
+   education marital_status pregnant language_english household_income
+       <dbl> <chr>          <chr>    <lgl>                       <dbl>
+ 1         3 separated      <NA>     TRUE                        17500
+ 2         3 married        <NA>     TRUE                        40000
+ 3         4 married        <NA>     TRUE                        70000
+ 4        NA <NA>           <NA>     TRUE                        60000
+ 5         5 married        <NA>     TRUE                       100000
+ 6         4 divorced       <NA>     TRUE                        60000
+ 7        NA <NA>           <NA>     TRUE                       100000
+ 8         5 widowed        <NA>     TRUE                        70000
+ 9         3 married        <NA>     TRUE                       100000
+10         3 divorced       <NA>     TRUE                        17500
+# ℹ 10,165 more rows
    +
    +
    +
    +
    +

    Convert born_usa and citizen_usa to numeric (binary) columns using a vector of column names

    +

    Suppose we had a vector of column names that we wanted to modify using mutate():

    +
    +
    selected_cols <- c("born_usa", "citizen_usa")
    +
    +

    Then we could use all_of(selected_cols) in across() to apply the function to all columns listed in the selected_cols vector as follows:

    +
    +
    demographics |> mutate(across(all_of(selected_cols), as.numeric)) |>
+  print(width = Inf)
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+   race             six_month_period age_months_ex_0_19yr served_active_duty_us
+   <chr>                       <dbl>                <dbl> <lgl>                
+ 1 black                           1                   NA TRUE                 
+ 2 white                           1                   NA FALSE                
+ 3 white                           2                   NA TRUE                 
+ 4 white                           1                  119 NA                   
+ 5 white                           1                   NA FALSE                
+ 6 mexican american                1                   NA TRUE                 
+ 7 white                           2                    6 NA                   
+ 8 white                           2                   NA FALSE                
+ 9 other hispanic                 NA                   NA FALSE                
+10 white                           1                   NA FALSE                
+   served_active_duty_foreign born_usa citizen_usa time_in_us education_youth
+   <lgl>                         <dbl>       <dbl>      <dbl>           <dbl>
+ 1 TRUE                              1           1         NA              NA
+ 2 NA                                1           1         NA              NA
+ 3 TRUE                              1           1         NA              NA
+ 4 NA                                1           1         NA               3
+ 5 NA                                1           1         NA              NA
+ 6 FALSE                             1           1         NA              NA
+ 7 NA                                1           1         NA              NA
+ 8 NA                                1           1         NA              NA
+ 9 NA                                1           1         NA              NA
+10 NA                                1           1         NA              NA
+   education marital_status pregnant language_english household_income
+       <dbl> <chr>          <chr>    <lgl>                       <dbl>
+ 1         3 separated      <NA>     TRUE                        17500
+ 2         3 married        <NA>     TRUE                        40000
+ 3         4 married        <NA>     TRUE                        70000
+ 4        NA <NA>           <NA>     TRUE                        60000
+ 5         5 married        <NA>     TRUE                       100000
+ 6         4 divorced       <NA>     TRUE                        60000
+ 7        NA <NA>           <NA>     TRUE                       100000
+ 8         5 widowed        <NA>     TRUE                        70000
+ 9         3 married        <NA>     TRUE                       100000
+10         3 divorced       <NA>     TRUE                        17500
+# ℹ 10,165 more rows
    +
    +
    +

    We could also use any_of(selected_cols):

    +
    +
    demographics |> mutate(across(any_of(selected_cols), as.numeric)) |>
+  print(width = Inf)
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+   race             six_month_period age_months_ex_0_19yr served_active_duty_us
+   <chr>                       <dbl>                <dbl> <lgl>                
+ 1 black                           1                   NA TRUE                 
+ 2 white                           1                   NA FALSE                
+ 3 white                           2                   NA TRUE                 
+ 4 white                           1                  119 NA                   
+ 5 white                           1                   NA FALSE                
+ 6 mexican american                1                   NA TRUE                 
+ 7 white                           2                    6 NA                   
+ 8 white                           2                   NA FALSE                
+ 9 other hispanic                 NA                   NA FALSE                
+10 white                           1                   NA FALSE                
+   served_active_duty_foreign born_usa citizen_usa time_in_us education_youth
+   <lgl>                         <dbl>       <dbl>      <dbl>           <dbl>
+ 1 TRUE                              1           1         NA              NA
+ 2 NA                                1           1         NA              NA
+ 3 TRUE                              1           1         NA              NA
+ 4 NA                                1           1         NA               3
+ 5 NA                                1           1         NA              NA
+ 6 FALSE                             1           1         NA              NA
+ 7 NA                                1           1         NA              NA
+ 8 NA                                1           1         NA              NA
+ 9 NA                                1           1         NA              NA
+10 NA                                1           1         NA              NA
+   education marital_status pregnant language_english household_income
+       <dbl> <chr>          <chr>    <lgl>                       <dbl>
+ 1         3 separated      <NA>     TRUE                        17500
+ 2         3 married        <NA>     TRUE                        40000
+ 3         4 married        <NA>     TRUE                        70000
+ 4        NA <NA>           <NA>     TRUE                        60000
+ 5         5 married        <NA>     TRUE                       100000
+ 6         4 divorced       <NA>     TRUE                        60000
+ 7        NA <NA>           <NA>     TRUE                       100000
+ 8         5 widowed        <NA>     TRUE                        70000
+ 9         3 married        <NA>     TRUE                       100000
+10         3 divorced       <NA>     TRUE                        17500
+# ℹ 10,165 more rows
    +
    +
    +

    The difference between the two, is that when using all_of() all columns in selected_cols must be included in the data, whereas this is not necessary for any_of(). For example, if one of our columns in selected_cols did not exist, then all_of() would throw an error, whereas any_of() would not:

    +
    +
    selected_cols <- c("born_usa", "citizen_usa", "abc")
+demographics |> mutate(across(all_of(selected_cols), as.numeric))
    +
    +
    Error in `mutate()`:
+ℹ In argument: `across(all_of(selected_cols), as.numeric)`.
+Caused by error in `across()`:
+ℹ In argument: `all_of(selected_cols)`.
+Caused by error in `all_of()`:
+! Can't subset elements that don't exist.
+✖ Element `abc` doesn't exist.
    +
    +
    +

    We could also use any_of(selected_cols):

    +
    +
    demographics |> mutate(across(any_of(selected_cols), as.numeric))
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <dbl>, citizen_usa <dbl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +
    +
    +
    +

    Select helpers summary

    +

    So far we have seen the following “select helpers” that can be used to specify the columns inside across():

    +
      +

    • where() – across to all columns that satisfy a logical condition (is.character)

      • +

    • starts_with() and ends_with() – across all columns that start or ends with a specified string

      • +

    • all_of() and any_of() – across all columns whose names are contained in a character vector, where all_of() requires all columns in the vector be present.

      • +
    +

    Another common select helper is contains() which can be used to select all columns that contain a specified string.

    +
    +

    Exercise

    +
      +

    1. For all columns that contain the word “education” (education_youth and education), add the number 5 to each value

      2. +

    2. For all numeric columns, standardize the values by subtracting the mean and dividing by the standard deviation

      3. +

    3. Compute the average age across all columns that start with age_

      4. +

    4. Compute the total number of TRUE values in the born_usa, citizen_usa, and language_english columns

      5. +
    +
    +

    Solution

    +
      +
    1. +
    +
    +
    demographics |> mutate(across(contains("education"), ~. + 5)) |> 
+  print(width = Inf)
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+   race             six_month_period age_months_ex_0_19yr served_active_duty_us
+   <chr>                       <dbl>                <dbl> <lgl>                
+ 1 black                           1                   NA TRUE                 
+ 2 white                           1                   NA FALSE                
+ 3 white                           2                   NA TRUE                 
+ 4 white                           1                  119 NA                   
+ 5 white                           1                   NA FALSE                
+ 6 mexican american                1                   NA TRUE                 
+ 7 white                           2                    6 NA                   
+ 8 white                           2                   NA FALSE                
+ 9 other hispanic                 NA                   NA FALSE                
+10 white                           1                   NA FALSE                
+   served_active_duty_foreign born_usa citizen_usa time_in_us education_youth
+   <lgl>                      <lgl>    <lgl>            <dbl>           <dbl>
+ 1 TRUE                       TRUE     TRUE                NA              NA
+ 2 NA                         TRUE     TRUE                NA              NA
+ 3 TRUE                       TRUE     TRUE                NA              NA
+ 4 NA                         TRUE     TRUE                NA               8
+ 5 NA                         TRUE     TRUE                NA              NA
+ 6 FALSE                      TRUE     TRUE                NA              NA
+ 7 NA                         TRUE     TRUE                NA              NA
+ 8 NA                         TRUE     TRUE                NA              NA
+ 9 NA                         TRUE     TRUE                NA              NA
+10 NA                         TRUE     TRUE                NA              NA
+   education marital_status pregnant language_english household_income
+       <dbl> <chr>          <chr>    <lgl>                       <dbl>
+ 1         8 separated      <NA>     TRUE                        17500
+ 2         8 married        <NA>     TRUE                        40000
+ 3         9 married        <NA>     TRUE                        70000
+ 4        NA <NA>           <NA>     TRUE                        60000
+ 5        10 married        <NA>     TRUE                       100000
+ 6         9 divorced       <NA>     TRUE                        60000
+ 7        NA <NA>           <NA>     TRUE                       100000
+ 8        10 widowed        <NA>     TRUE                        70000
+ 9         8 married        <NA>     TRUE                       100000
+10         8 divorced       <NA>     TRUE                        17500
+# ℹ 10,165 more rows
    +
    +
    +
      +
    1. +
    +
    +
    # standardize all numeric columns
+demographics |> mutate(across(where(is.numeric), ~{(. - mean(., na.rm = TRUE)) / sd(., na.rm = TRUE)}))
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         -1.73 both interview and exam male       1.54               NA    
+ 2         -1.73 both interview and exam male       0.922              NA    
+ 3         -1.73 both interview and exam male       1.66               NA    
+ 4         -1.73 both interview and exam male      -0.921              NA    
+ 5         -1.73 both interview and exam female     1.70               NA    
+ 6         -1.73 both interview and exam male       1.00               NA    
+ 7         -1.73 both interview and exam male      -1.29               -0.776
+ 8         -1.73 both interview and exam female     1.21               NA    
+ 9         -1.73 interview only          male       0.431              NA    
+10         -1.73 both interview and exam female     1.00               NA    
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +
      +
    1. +
    +
    +
    # compute average age across all age columns
+demographics |> summarize(across(starts_with("age"), ~mean(., na.rm = TRUE)))
    +
    +
    # A tibble: 1 × 3
+  age_years age_months_sc_0_2yr age_months_ex_0_19yr
+      <dbl>               <dbl>                <dbl>
+1      31.5                10.3                 107.
    +
    +
    +
      +
    1. +
    +
    +
    # compute the total in the `born_usa`, `citizen_usa`, and `language_english`
+demographics |> summarise(across(any_of(c("born_usa", "citizen_usa", "language_english")), 
+                                 ~sum(., na.rm = TRUE)))
    +
    +
    # A tibble: 1 × 3
+  born_usa citizen_usa language_english
+     <int>       <int>            <int>
+1     8262        9220             9100
    +
    +
    + + +
    +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/content/complete/detailed/04_recoding_variables.html b/docs/content/complete/detailed/04_recoding_variables.html new file mode 100644 index 0000000..1d1759c --- /dev/null +++ b/docs/content/complete/detailed/04_recoding_variables.html @@ -0,0 +1,884 @@ + + + + + + + + + +Recoding variables using if_else and case_when – Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + +
    + +
    + + + + +
    + +
    +
    +

    Recoding variables using if_else and case_when

    +
    + + + +
    + + + + +
    + + + +
    + + +
    +
    library(tidyverse)
    +
    +
    ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
+✔ dplyr     1.1.4     ✔ readr     2.1.5
+✔ forcats   1.0.0     ✔ stringr   1.5.1
+✔ ggplot2   3.5.1     ✔ tibble    3.2.1
+✔ lubridate 1.9.3     ✔ tidyr     1.3.1
+✔ purrr     1.0.2     
+── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
+✖ dplyr::filter() masks stats::filter()
+✖ dplyr::lag()    masks stats::lag()
+ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
    +
    +
    demographics <- read_csv("data/demographics.csv")
    +
    +
    Rows: 10175 Columns: 19
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (5): interview_examination, gender, race, marital_status, pregnant
+dbl (9): respondent_id, age_years, age_months_sc_0_2yr, six_month_period, ag...
+lgl (5): served_active_duty_us, served_active_duty_foreign, born_usa, citize...
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
    +
    demographics
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +

    In this document, you will learn how to “recode” variables by replacing values in a variable with other values of your choice. The most common use-case is typically converting numerically-encoded variables to categorical/character versions, and vice versa.

    +

    We will introduce two functions for doing this:

    +
      +

    • if_else() which can be used to create binary variables (variables with just two distinct values) based on a logical “condition”

      • +

    • case_when() which can be used to create variables with many different values.

      • +
    +
    +

    if_else

    +

    Consider, for example, the interview_examination column. This variable has two distinct values "both interview and exam" and "interview only":

    +
    +
    demographics |> count(interview_examination)
    +
    +
    # A tibble: 2 × 2
+  interview_examination       n
+  <chr>                   <int>
+1 both interview and exam  9813
+2 interview only            362
    +
    +
    +

    If we wanted to do an analysis involving this column, we might need to convert it to a numeric format. We can do that using if_else(). The code below uses if_else() to create a column called interview_examination_numeric that converts all values in interview_examination that are equal to "both interview and exam" to 2, and converts all other values to 1.

    +
    +
    demographics |> 
+  mutate(interview_examination_numeric = if_else(interview_examination == "both interview and exam", 
+                                                 true = 2, 
+                                                 false = 1)) |>
+  select(interview_examination, interview_examination_numeric)
    +
    +
    # A tibble: 10,175 × 2
+   interview_examination   interview_examination_numeric
+   <chr>                                           <dbl>
+ 1 both interview and exam                             2
+ 2 both interview and exam                             2
+ 3 both interview and exam                             2
+ 4 both interview and exam                             2
+ 5 both interview and exam                             2
+ 6 both interview and exam                             2
+ 7 both interview and exam                             2
+ 8 both interview and exam                             2
+ 9 interview only                                      1
+10 both interview and exam                             2
+# ℹ 10,165 more rows
    +
    +
    +

    Note that you can use if_else() for columns of any type. The following code again creates the interview_examination_numeric column, and then creates a new column called interview_examination_revert that takes the numeric encoding and converts the values 2 and 1 to new character values, "both" and "just interview", respectively. We also use the select helper contains() inside our select function to view all of the resulting columns that contain the word "interview":

    +
    +
    demographics |> 
+  mutate(interview_examination_numeric = if_else(interview_examination == "both interview and exam", 
+                                                 true = 2, 
+                                                 false = 1)) |>
+  mutate(interview_examination_revert = if_else(interview_examination_numeric == 2,
+                                                true = "both",
+                                                false = "just interview")) |>
+  select(contains("interview"))
    +
    +
    # A tibble: 10,175 × 3
+   interview_examination   interview_examination_numeric interview_examination…¹
+   <chr>                                           <dbl> <chr>                  
+ 1 both interview and exam                             2 both                   
+ 2 both interview and exam                             2 both                   
+ 3 both interview and exam                             2 both                   
+ 4 both interview and exam                             2 both                   
+ 5 both interview and exam                             2 both                   
+ 6 both interview and exam                             2 both                   
+ 7 both interview and exam                             2 both                   
+ 8 both interview and exam                             2 both                   
+ 9 interview only                                      1 just interview         
+10 both interview and exam                             2 both                   
+# ℹ 10,165 more rows
+# ℹ abbreviated name: ¹​interview_examination_revert
    +
    +
    +
    +

    Exercise

    +

    Use if_else() to create a variable called completed_high_school, which has the values "yes" if education is equal to at least 3, and "no" otherwise.

    +

    A link to the documentation for the demographics data can be found here.

    +
    +

    Solution

    +

    Our condition is education >= 3 and we want to replace all values for which this condition is true with "yes", and all other values with "no":

    +
    +
    demographics |> 
+  mutate(completed_high_school = if_else(education >= 3, true = "yes", false = "no")) |>
+  select(education, completed_high_school) |>
+  sample_n(10)
    +
    +
    # A tibble: 10 × 2
+   education completed_high_school
+       <dbl> <chr>                
+ 1         1 no                   
+ 2        NA <NA>                 
+ 3         2 no                   
+ 4         3 yes                  
+ 5        NA <NA>                 
+ 6         3 yes                  
+ 7         1 no                   
+ 8         5 yes                  
+ 9        NA <NA>                 
+10        NA <NA>
    +
    +
    +
    +
    +
    +
    +

    case_when

    +

    The case_when() function is similar to if_else(), in that it allows you to recode values in a column of a DataFrames with different values DataFrame based on a condition, but unlike if_else() which only lets you provide one condition, and two value options, case_when() allows you to have an unlimited number of conditions and corresponding recoded values.

    +

    In this section we will work with the marital_status column of the demographics data:

    +
    +
    demographics |> count(marital_status)
    +
    +
    # A tibble: 7 × 2
+  marital_status          n
+  <chr>               <int>
+1 divorced              659
+2 living_with_partner   417
+3 married              2965
+4 never_married        1112
+5 separated             177
+6 widowed               436
+7 <NA>                 4409
    +
    +
    +

    To create a new variable based on marital_status that replaces "married" with 3, "living_with_partner" with 2, and each of "divorced", "widowed", "never_married", and "separated" with 1, you can use the following code (the select() function at the end just allows us to view the original and the new columns side-by-side).

    +
    +
    demographics |> mutate(marital_status_numeric = case_when(marital_status == "married" ~ 3,
+                                                          marital_status == "living_with_partner" ~ 2,
+                                                          marital_status == "divorced" ~ 1,
+                                                          marital_status == "widowed" ~ 1,
+                                                          marital_status == "never_married" ~ 1,
+                                                          marital_status == "separated" ~ 1)) |>
+  select(marital_status, marital_status_numeric)
    +
    +
    # A tibble: 10,175 × 2
+   marital_status marital_status_numeric
+   <chr>                           <dbl>
+ 1 separated                           1
+ 2 married                             3
+ 3 married                             3
+ 4 <NA>                               NA
+ 5 married                             3
+ 6 divorced                            1
+ 7 <NA>                               NA
+ 8 widowed                             1
+ 9 married                             3
+10 divorced                            1
+# ℹ 10,165 more rows
    +
    +
    +

    The argument syntax of case_when() is CONDITION ~ new_value, where for entries in the original column for which CONDITION is TRUE, the value new_value is returned. So in marital_status == "married" ~ 3, the CONDITION is marital_status == "married", and the new_value is 3.

    +

    Note that if you have multiple values that you want to recode as the same value, you can use the %in% vector syntax for asking whether a variable is contained %in% a vector of values:

    +
    +
    demographics |> 
+  mutate(marital_status_numeric = case_when(
+    marital_status == "married" ~ 3,
+    marital_status == "living_with_partner" ~ 2,
+    # replace the final four conditions with a single %in% condition:
+    marital_status %in% c("divorced", "widowed", "never_married", "separated") ~ 1)
+  ) |>
+  select(marital_status, marital_status_numeric)
    +
    +
    # A tibble: 10,175 × 2
+   marital_status marital_status_numeric
+   <chr>                           <dbl>
+ 1 separated                           1
+ 2 married                             3
+ 3 married                             3
+ 4 <NA>                               NA
+ 5 married                             3
+ 6 divorced                            1
+ 7 <NA>                               NA
+ 8 widowed                             1
+ 9 married                             3
+10 divorced                            1
+# ℹ 10,165 more rows
    +
    +
    +
    +
    +

    Execise

    +

    Use case_when() to convert born_usa and citizen_usa to “yes” and “no”. Bonus points: use across().

    +

    To do this without across(), you can write:

    +
    +
    demographics |> mutate(born_usa_chr = case_when(born_usa ~ "yes",
+                                                !born_usa ~ "no"),
+                       citizen_usa_chr = case_when(citizen_usa ~ "yes",
+                                                   !citizen_usa ~ "no")) |>
+  select(born_usa, born_usa_chr, citizen_usa, citizen_usa_chr) |> 
+  sample_n(10)
    +
    +
    # A tibble: 10 × 4
+   born_usa born_usa_chr citizen_usa citizen_usa_chr
+   <lgl>    <chr>        <lgl>       <chr>          
+ 1 FALSE    no           TRUE        yes            
+ 2 TRUE     yes          TRUE        yes            
+ 3 FALSE    no           FALSE       no             
+ 4 TRUE     yes          TRUE        yes            
+ 5 TRUE     yes          TRUE        yes            
+ 6 TRUE     yes          TRUE        yes            
+ 7 FALSE    no           FALSE       no             
+ 8 TRUE     yes          TRUE        yes            
+ 9 FALSE    no           TRUE        yes            
+10 TRUE     yes          TRUE        yes
    +
    +
    +

    Note that born_usa ~ "yes" is equivalent to born_usa == TRUE ~ "yes", but the == TRUE is redundant because born_usa is itself a logical variable. Similarly, !citizen_usa ~ "no" is equivalent to citizen_usa == FALSE ~ "no".

    +

    To use across(), the relevant select helper is something like ends_with("_usa") or contains("usa"), and you provide a ~ before case_when() to start an anonymous function, and you need to replace the column name with . (again, you don’t need the == TRUE for this particular example in the condition, but that’s just because the columns we’re applying the case_when() function to are logical).

    +
    +
    demographics |> mutate(across(ends_with("_usa"), 
+                              ~case_when(. == TRUE ~ "yes",
+                                         . == FALSE ~ "no"),
+                              .names = "{.col}_chr")) |>
+  select(contains("_usa")) |> 
+  sample_n(10)
    +
    +
    # A tibble: 10 × 4
+   born_usa citizen_usa born_usa_chr citizen_usa_chr
+   <lgl>    <lgl>       <chr>        <chr>          
+ 1 TRUE     TRUE        yes          yes            
+ 2 TRUE     TRUE        yes          yes            
+ 3 TRUE     TRUE        yes          yes            
+ 4 TRUE     TRUE        yes          yes            
+ 5 TRUE     TRUE        yes          yes            
+ 6 FALSE    TRUE        no           yes            
+ 7 FALSE    FALSE       no           no             
+ 8 TRUE     TRUE        yes          yes            
+ 9 TRUE     TRUE        yes          yes            
+10 FALSE    TRUE        no           yes
    +
    +
    + + +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/content/complete/detailed/05_pivoting.html b/docs/content/complete/detailed/05_pivoting.html new file mode 100644 index 0000000..4c1b356 --- /dev/null +++ b/docs/content/complete/detailed/05_pivoting.html @@ -0,0 +1,775 @@ + + + + + + + + + +Reshaping (Pivoting) Data – Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + +
    + +
    + + + + +
    + +
    +
    +

    Reshaping (Pivoting) Data

    +
    + + + +
    + + + + +
    + + + +
    + + +

    In this lesson, we will be working with a new NHANES table that contains urine albumin and creatinine lab data.

    +
    +
    library(tidyverse)
    +
    +
    ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
+✔ dplyr     1.1.4     ✔ readr     2.1.5
+✔ forcats   1.0.0     ✔ stringr   1.5.1
+✔ ggplot2   3.5.1     ✔ tibble    3.2.1
+✔ lubridate 1.9.3     ✔ tidyr     1.3.1
+✔ purrr     1.0.2     
+── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
+✖ dplyr::filter() masks stats::filter()
+✖ dplyr::lag()    masks stats::lag()
+ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
    +
    +
    labs_data <- read.csv("data/urine_albumin_creatinine.csv")
    +
    +

    Taking a look at the first 10 rows, it is clear that this data is in a long format. This means that each “observational unit” (in this case, each survey respondent) has multiple rows in the data, and the names of the variables being measured (the types of labs) are all contained in a single row (called labs) and the values of each of the variables being measured are all contained in a single row (called measurements). Note that each respondent has 5 rows each:

    +
    +
    head(labs_data, 10)
    +
    +
       respondent_id                         lab measurement
+1          73557            ur_albumin_ug_ml        4.30
+2          73557             ur_albumin_mg_l        4.30
+3          73557         ur_creatinine_mg_dl       39.00
+4          73557        ur_creatinine_umol_l     3447.60
+5          73557 ur_albumin_creatinine_ratio       11.03
+6          73558            ur_albumin_ug_ml      153.00
+7          73558             ur_albumin_mg_l      153.00
+8          73558         ur_creatinine_mg_dl       50.00
+9          73558        ur_creatinine_umol_l     4420.00
+10         73558 ur_albumin_creatinine_ratio      306.00
    +
    +
    +

    A wide format, on the other hand, will only have one row for each observational unit (respondent), and each of the individual variables being measured (the labs) will have their own column, each containing the values for the corresponding lab.

    +

    You can convert from a long format to a wide format using the pivor_wider() function. The main arguments that you need to provide is the name of the columns that you want to pivot, specifically, the column that contains the variable names (you provide this to the names_from argument) and the column that contains the variable measurements (you provide this to the values_from argument).

    +

    The code below creates a wide-form version of the labs data, and saves it as a new data frame called labs_data_wide:

    +
    +
    labs_data_wide <- labs_data |> 
+  pivot_wider(names_from = "lab", values_from = "measurement")
+labs_data_wide
    +
    +
    # A tibble: 8,291 × 6
+   respondent_id ur_albumin_ug_ml ur_albumin_mg_l ur_creatinine_mg_dl
+           <int>            <dbl>           <dbl>               <dbl>
+ 1         73557              4.3             4.3                  39
+ 2         73558            153             153                    50
+ 3         73559             11.9            11.9                 113
+ 4         73560             16              16                    76
+ 5         73561            255             255                   147
+ 6         73562            123             123                    74
+ 7         73564             19              19                   242
+ 8         73566              1.3             1.3                  18
+ 9         73567             35              35                   215
+10         73568             25              25                    31
+# ℹ 8,281 more rows
+# ℹ 2 more variables: ur_creatinine_umol_l <dbl>,
+#   ur_albumin_creatinine_ratio <dbl>
    +
    +
    +

    If you want to instead convert from a wide format dataset into a longer-format dataset, you can instead use the pivot_longer() function. The main argument you need to provide to pivot_longer() is cols which contains the names of the columns that will be pivoted into a single pair of name and value columns. You can change the names of the resulting name and value columns using the names_to and values_to arguments of pivot_longer().

    +

    The following code takes the wide-format version of the labs data and pivots it back into the original long-format version:

    +
    +
    labs_data_wide |> pivot_longer(cols = starts_with("ur_"), names_to = "lab", values_to = "measurement")
    +
    +
    # A tibble: 41,455 × 3
+   respondent_id lab                         measurement
+           <int> <chr>                             <dbl>
+ 1         73557 ur_albumin_ug_ml                    4.3
+ 2         73557 ur_albumin_mg_l                     4.3
+ 3         73557 ur_creatinine_mg_dl                39  
+ 4         73557 ur_creatinine_umol_l             3448. 
+ 5         73557 ur_albumin_creatinine_ratio        11.0
+ 6         73558 ur_albumin_ug_ml                  153  
+ 7         73558 ur_albumin_mg_l                   153  
+ 8         73558 ur_creatinine_mg_dl                50  
+ 9         73558 ur_creatinine_umol_l             4420  
+10         73558 ur_albumin_creatinine_ratio       306  
+# ℹ 41,445 more rows
    +
    +
    +

    It is not necessarily the case that either one of the long-format versus the wide-format is always better than the other. Which one makes more sense will depend on what you plan to do with the data. For example, if you plan to join your labs dataset onto the demographics data that we have been working with previously (you will see this in the next lesson), then you will need to have a single row for each observational unit, and therefore, the wide format is better.

    +

    However, if you want to create a visualization that compares the different variables using ggplot2, it is a lot easier if all of the variables appear in a long (name and value column) format. For example, it is much easier to create some boxplots comparing each of the lab measurement distributions using the original long format than the wide format:

    +
    +
    # create boxplots using the long format
+labs_data |> ggplot() + 
+  geom_boxplot(aes(x = lab, y = measurement))
    +
    +
    Warning: Removed 1195 rows containing non-finite outside the scale range
+(`stat_boxplot()`).
    +
    +
    +
    +
    +

    +
    +
    +
    +
    +
    +

    Exercise

    +

    Load the demographics data and use select() to select just the respondent_id, gender, marital_status and race columns and then use pivot_longer() to create the following long-format table (below are just the first 10 rows).

    +

    respondent_id name value
    +
    +1 73557 gender male
    +2 73557 marital_status separated 3 73557 race black
    +4 73558 gender male
    +5 73558 marital_status married
    +6 73558 race white
    +7 73559 gender male
    +8 73559 marital_status married
    +9 73559 race white
    +10 73560 gender male

    +
    +

    Solution

    +
    +
    demographics <- read_csv("data/demographics.csv")
    +
    +
    Rows: 10175 Columns: 19
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (5): interview_examination, gender, race, marital_status, pregnant
+dbl (9): respondent_id, age_years, age_months_sc_0_2yr, six_month_period, ag...
+lgl (5): served_active_duty_us, served_active_duty_foreign, born_usa, citize...
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
    +
    demographics
    +
    +
    # A tibble: 10,175 × 19
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+# ℹ 10,165 more rows
+# ℹ 14 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>
    +
    +
    +
    +
    demographics |> 
+  select(respondent_id, gender, marital_status, race) |>
+  pivot_longer(cols = all_of(c("gender", "marital_status", "race")))
    +
    +
    # A tibble: 30,525 × 3
+   respondent_id name           value    
+           <dbl> <chr>          <chr>    
+ 1         73557 gender         male     
+ 2         73557 marital_status separated
+ 3         73557 race           black    
+ 4         73558 gender         male     
+ 5         73558 marital_status married  
+ 6         73558 race           white    
+ 7         73559 gender         male     
+ 8         73559 marital_status married  
+ 9         73559 race           white    
+10         73560 gender         male     
+# ℹ 30,515 more rows
    +
    +
    + + +
    +
    + +
    + +
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    +

    Joining Data Together

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    + + +

    This lesson introduces techniques for “joining” multiple data tables together using a “key” variable that serves to identify the individual “observational units” in the data. In the NHANES data, each observational unit is an individual respondent of the survey.

    +

    A really helpful resource for learning about joins is the R for Data Science book (specifically the chapter about “Relational Data”).

    +

    At the end of this lesson we will have created a single data frame that contains the information from both the demographics data and the urine albumin and creatinine labs data that we load in below:

    +
    +
    library(tidyverse)
    +
    +
    ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
+✔ dplyr     1.1.4     ✔ readr     2.1.5
+✔ forcats   1.0.0     ✔ stringr   1.5.1
+✔ ggplot2   3.5.1     ✔ tibble    3.2.1
+✔ lubridate 1.9.3     ✔ tidyr     1.3.1
+✔ purrr     1.0.2     
+── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
+✖ dplyr::filter() masks stats::filter()
+✖ dplyr::lag()    masks stats::lag()
+ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
    +
    +
    demographics <- read_csv("data/demographics.csv")
    +
    +
    Rows: 10175 Columns: 19
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (5): interview_examination, gender, race, marital_status, pregnant
+dbl (9): respondent_id, age_years, age_months_sc_0_2yr, six_month_period, ag...
+lgl (5): served_active_duty_us, served_active_duty_foreign, born_usa, citize...
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
    +
    labs <- read_csv("data/urine_albumin_creatinine.csv")
    +
    +
    Rows: 41455 Columns: 3
+── Column specification ────────────────────────────────────────────────────────
+Delimiter: ","
+chr (1): lab
+dbl (2): respondent_id, measurement
+
+ℹ Use `spec()` to retrieve the full column specification for this data.
+ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
    +
    +
    +
    +

    Determining what kind of join to do

    +

    There are four kinds of joins that you might want to use for combining two tables into a single table:

    +
      +

    • An inner join, which will keep only the data for the observational units that appear in both tables

      • +

    • A left join, which will keep all of the data for the observational units in the first (left) table, and will add missing values when there is no available data in the second table.

      • +

    • A right join, which will keep all of the data for the observational units in the second (right) table, and will add missing values when there is no available data in the first table.

      • +

    • A full join, which will keep all of the data for the observational units in both the first (left) table, and will add missing values when there is no available data in the other table.

      • +
    +

    The kind of join that you will implement will depend on what you want to use your joined data for.

    +

    If you only want to keep observational units that have complete data (i.e., data available in both tables), then you will want to perform an inner join, but if you don’t want to discard observational that are missing from one of the tables, you will want to perform a full join.

    +

    Identifying the overlap between the two tables can help determine which type of join makes sense.

    +

    So let’s ask the question of Are there any observations in the demographics table that do not appear in the labs table?

    +
    +
    # proportion of people in demographics who are also in labs
+sum(unique(demographics$respondent_id) %in% unique(labs$respondent_id)) / n_distinct(demographics$respondent_id)
    +
    +
    [1] 0.8148403
    +
    +
    +

    The calculation above shows that around 81% of observations in the demographics table have available labs data.

    +

    We can also ask the converse question of Are there any observations in the labs table that do not appear in the demographics table?

    +
    +
    # proportion of people in labs who are also in demographics
+sum(unique(labs$respondent_id) %in% unique(demographics$respondent_id)) / n_distinct(labs$respondent_id)
    +
    +
    [1] 1
    +
    +
    +

    The calculation above shows that 100% of observations in the labs table have available demographics data.

    +

    This means that all of the people with labs data appear in the demographics data. Which, if our “left” table is demographics, and our “right” table is labs, means that an inner join will be the same as a full join. It also means that a full join will be the same as a left join.

    +
    +

    Checking the uniqueness of the key ID variables

    +

    It is also helpful to determine whether the key ID values are unique in each table. There are lots of ways to do this, one of which is using the identical() function to ask whether the unique() version of the respondent_id column is equal to the non-unique() version.

    +

    Below, we see that the respondent_id column is indeed unique for demographics:

    +
    +
    # are the respondent ID values in demographics unique?
+identical(unique(demographics$respondent_id), demographics$respondent_id)
    +
    +
    [1] TRUE
    +
    +
    +

    But not for labs:

    +
    +
    # are the respondent ID values in labs unique?
+identical(unique(labs$respondent_id), labs$respondent_id)
    +
    +
    [1] FALSE
    +
    +
    +
    +
    +
    +

    Joining demographics and labs

    +

    Our two options for to join demographics (left) and labs (right) are:

    +
      +

    • An inner or right join will only keep the 81% of people in demographics who have available labs data

      • +

    • A left or full join will keep all people in demographics data, and join missing values for those who don’t have labs data available

      • +
    +

    Since we don’t want to discard any data, we will choose the latter, a left/full join.

    +

    The following two pieces of code, one using left_join() and the other using full_join() are equivalent for this problem:

    +
    +
    print(left_join(demographics, labs, by = "respondent_id"), width = Inf)
    +
    +
    # A tibble: 43,339 × 21
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73557 both interview and exam male          69                  NA
+ 3         73557 both interview and exam male          69                  NA
+ 4         73557 both interview and exam male          69                  NA
+ 5         73557 both interview and exam male          69                  NA
+ 6         73558 both interview and exam male          54                  NA
+ 7         73558 both interview and exam male          54                  NA
+ 8         73558 both interview and exam male          54                  NA
+ 9         73558 both interview and exam male          54                  NA
+10         73558 both interview and exam male          54                  NA
+   race  six_month_period age_months_ex_0_19yr served_active_duty_us
+   <chr>            <dbl>                <dbl> <lgl>                
+ 1 black                1                   NA TRUE                 
+ 2 black                1                   NA TRUE                 
+ 3 black                1                   NA TRUE                 
+ 4 black                1                   NA TRUE                 
+ 5 black                1                   NA TRUE                 
+ 6 white                1                   NA FALSE                
+ 7 white                1                   NA FALSE                
+ 8 white                1                   NA FALSE                
+ 9 white                1                   NA FALSE                
+10 white                1                   NA FALSE                
+   served_active_duty_foreign born_usa citizen_usa time_in_us education_youth
+   <lgl>                      <lgl>    <lgl>            <dbl>           <dbl>
+ 1 TRUE                       TRUE     TRUE                NA              NA
+ 2 TRUE                       TRUE     TRUE                NA              NA
+ 3 TRUE                       TRUE     TRUE                NA              NA
+ 4 TRUE                       TRUE     TRUE                NA              NA
+ 5 TRUE                       TRUE     TRUE                NA              NA
+ 6 NA                         TRUE     TRUE                NA              NA
+ 7 NA                         TRUE     TRUE                NA              NA
+ 8 NA                         TRUE     TRUE                NA              NA
+ 9 NA                         TRUE     TRUE                NA              NA
+10 NA                         TRUE     TRUE                NA              NA
+   education marital_status pregnant language_english household_income
+       <dbl> <chr>          <chr>    <lgl>                       <dbl>
+ 1         3 separated      <NA>     TRUE                        17500
+ 2         3 separated      <NA>     TRUE                        17500
+ 3         3 separated      <NA>     TRUE                        17500
+ 4         3 separated      <NA>     TRUE                        17500
+ 5         3 separated      <NA>     TRUE                        17500
+ 6         3 married        <NA>     TRUE                        40000
+ 7         3 married        <NA>     TRUE                        40000
+ 8         3 married        <NA>     TRUE                        40000
+ 9         3 married        <NA>     TRUE                        40000
+10         3 married        <NA>     TRUE                        40000
+   lab                         measurement
+   <chr>                             <dbl>
+ 1 ur_albumin_ug_ml                    4.3
+ 2 ur_albumin_mg_l                     4.3
+ 3 ur_creatinine_mg_dl                39  
+ 4 ur_creatinine_umol_l             3448. 
+ 5 ur_albumin_creatinine_ratio        11.0
+ 6 ur_albumin_ug_ml                  153  
+ 7 ur_albumin_mg_l                   153  
+ 8 ur_creatinine_mg_dl                50  
+ 9 ur_creatinine_umol_l             4420  
+10 ur_albumin_creatinine_ratio       306  
+# ℹ 43,329 more rows
    +
    +
    print(full_join(demographics, labs, by = "respondent_id"), width = Inf)
    +
    +
    # A tibble: 43,339 × 21
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73557 both interview and exam male          69                  NA
+ 3         73557 both interview and exam male          69                  NA
+ 4         73557 both interview and exam male          69                  NA
+ 5         73557 both interview and exam male          69                  NA
+ 6         73558 both interview and exam male          54                  NA
+ 7         73558 both interview and exam male          54                  NA
+ 8         73558 both interview and exam male          54                  NA
+ 9         73558 both interview and exam male          54                  NA
+10         73558 both interview and exam male          54                  NA
+   race  six_month_period age_months_ex_0_19yr served_active_duty_us
+   <chr>            <dbl>                <dbl> <lgl>                
+ 1 black                1                   NA TRUE                 
+ 2 black                1                   NA TRUE                 
+ 3 black                1                   NA TRUE                 
+ 4 black                1                   NA TRUE                 
+ 5 black                1                   NA TRUE                 
+ 6 white                1                   NA FALSE                
+ 7 white                1                   NA FALSE                
+ 8 white                1                   NA FALSE                
+ 9 white                1                   NA FALSE                
+10 white                1                   NA FALSE                
+   served_active_duty_foreign born_usa citizen_usa time_in_us education_youth
+   <lgl>                      <lgl>    <lgl>            <dbl>           <dbl>
+ 1 TRUE                       TRUE     TRUE                NA              NA
+ 2 TRUE                       TRUE     TRUE                NA              NA
+ 3 TRUE                       TRUE     TRUE                NA              NA
+ 4 TRUE                       TRUE     TRUE                NA              NA
+ 5 TRUE                       TRUE     TRUE                NA              NA
+ 6 NA                         TRUE     TRUE                NA              NA
+ 7 NA                         TRUE     TRUE                NA              NA
+ 8 NA                         TRUE     TRUE                NA              NA
+ 9 NA                         TRUE     TRUE                NA              NA
+10 NA                         TRUE     TRUE                NA              NA
+   education marital_status pregnant language_english household_income
+       <dbl> <chr>          <chr>    <lgl>                       <dbl>
+ 1         3 separated      <NA>     TRUE                        17500
+ 2         3 separated      <NA>     TRUE                        17500
+ 3         3 separated      <NA>     TRUE                        17500
+ 4         3 separated      <NA>     TRUE                        17500
+ 5         3 separated      <NA>     TRUE                        17500
+ 6         3 married        <NA>     TRUE                        40000
+ 7         3 married        <NA>     TRUE                        40000
+ 8         3 married        <NA>     TRUE                        40000
+ 9         3 married        <NA>     TRUE                        40000
+10         3 married        <NA>     TRUE                        40000
+   lab                         measurement
+   <chr>                             <dbl>
+ 1 ur_albumin_ug_ml                    4.3
+ 2 ur_albumin_mg_l                     4.3
+ 3 ur_creatinine_mg_dl                39  
+ 4 ur_creatinine_umol_l             3448. 
+ 5 ur_albumin_creatinine_ratio        11.0
+ 6 ur_albumin_ug_ml                  153  
+ 7 ur_albumin_mg_l                   153  
+ 8 ur_creatinine_mg_dl                50  
+ 9 ur_creatinine_umol_l             4420  
+10 ur_albumin_creatinine_ratio       306  
+# ℹ 43,329 more rows
    +
    +
    +

    However, notice that the observations in demographics that have labs observations have all been duplicated to match the number of rows in the labs data for each respondent. There are now many more rows in our joined data than we had in our demographics data, which is not what we want!

    +

    An important lesson is learned here: if your key ID variable has repeated values, your joined data will too.

    +

    A good check after completing a join is to make sure that the number of rows in the resulting joined data matches what you expect

    +

    Therefore, to ensure that we have just one row per observational unit (i.e., per respondent_id value), we need to join the wide-format labs_wide data instead of the long-format labs data.

    +

    Below, we compute the wide-format labs data:

    +
    +
    labs_wide <- labs |> pivot_wider(names_from = "lab", values_from = "measurement")
+labs_wide
    +
    +
    # A tibble: 8,291 × 6
+   respondent_id ur_albumin_ug_ml ur_albumin_mg_l ur_creatinine_mg_dl
+           <dbl>            <dbl>           <dbl>               <dbl>
+ 1         73557              4.3             4.3                  39
+ 2         73558            153             153                    50
+ 3         73559             11.9            11.9                 113
+ 4         73560             16              16                    76
+ 5         73561            255             255                   147
+ 6         73562            123             123                    74
+ 7         73564             19              19                   242
+ 8         73566              1.3             1.3                  18
+ 9         73567             35              35                   215
+10         73568             25              25                    31
+# ℹ 8,281 more rows
+# ℹ 2 more variables: ur_creatinine_umol_l <dbl>,
+#   ur_albumin_creatinine_ratio <dbl>
    +
    +
    +

    Then we can see that joining this wide version of the labs data onto the demographics data with a left_join() yields a joined dataset with all of the demographics and labs_wide columns, and the number of rows matches the original demographics data.

    +
    +
    print(left_join(demographics, labs_wide, by = "respondent_id"), width = Inf)
    +
    +
    # A tibble: 10,175 × 24
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73563 both interview and exam male           0                   5
+ 8         73564 both interview and exam female        61                  NA
+ 9         73565 interview only          male          42                  NA
+10         73566 both interview and exam female        56                  NA
+   race             six_month_period age_months_ex_0_19yr served_active_duty_us
+   <chr>                       <dbl>                <dbl> <lgl>                
+ 1 black                           1                   NA TRUE                 
+ 2 white                           1                   NA FALSE                
+ 3 white                           2                   NA TRUE                 
+ 4 white                           1                  119 NA                   
+ 5 white                           1                   NA FALSE                
+ 6 mexican american                1                   NA TRUE                 
+ 7 white                           2                    6 NA                   
+ 8 white                           2                   NA FALSE                
+ 9 other hispanic                 NA                   NA FALSE                
+10 white                           1                   NA FALSE                
+   served_active_duty_foreign born_usa citizen_usa time_in_us education_youth
+   <lgl>                      <lgl>    <lgl>            <dbl>           <dbl>
+ 1 TRUE                       TRUE     TRUE                NA              NA
+ 2 NA                         TRUE     TRUE                NA              NA
+ 3 TRUE                       TRUE     TRUE                NA              NA
+ 4 NA                         TRUE     TRUE                NA               3
+ 5 NA                         TRUE     TRUE                NA              NA
+ 6 FALSE                      TRUE     TRUE                NA              NA
+ 7 NA                         TRUE     TRUE                NA              NA
+ 8 NA                         TRUE     TRUE                NA              NA
+ 9 NA                         TRUE     TRUE                NA              NA
+10 NA                         TRUE     TRUE                NA              NA
+   education marital_status pregnant language_english household_income
+       <dbl> <chr>          <chr>    <lgl>                       <dbl>
+ 1         3 separated      <NA>     TRUE                        17500
+ 2         3 married        <NA>     TRUE                        40000
+ 3         4 married        <NA>     TRUE                        70000
+ 4        NA <NA>           <NA>     TRUE                        60000
+ 5         5 married        <NA>     TRUE                       100000
+ 6         4 divorced       <NA>     TRUE                        60000
+ 7        NA <NA>           <NA>     TRUE                       100000
+ 8         5 widowed        <NA>     TRUE                        70000
+ 9         3 married        <NA>     TRUE                       100000
+10         3 divorced       <NA>     TRUE                        17500
+   ur_albumin_ug_ml ur_albumin_mg_l ur_creatinine_mg_dl ur_creatinine_umol_l
+              <dbl>           <dbl>               <dbl>                <dbl>
+ 1              4.3             4.3                  39                3448.
+ 2            153             153                    50                4420 
+ 3             11.9            11.9                 113                9989.
+ 4             16              16                    76                6718.
+ 5            255             255                   147               12995.
+ 6            123             123                    74                6542.
+ 7             NA              NA                    NA                  NA 
+ 8             19              19                   242               21393.
+ 9             NA              NA                    NA                  NA 
+10              1.3             1.3                  18                1591.
+   ur_albumin_creatinine_ratio
+                         <dbl>
+ 1                       11.0 
+ 2                      306   
+ 3                       10.5 
+ 4                       21.0 
+ 5                      173.  
+ 6                      166.  
+ 7                       NA   
+ 8                        7.85
+ 9                       NA   
+10                        7.22
+# ℹ 10,165 more rows
    +
    +
    +
    +
    +

    Exercise

    +

    How many rows would you expect an inner join of demographics and labs_wide to have? Check your answer by conducting the join using inner_join()

    +

    The number of rows should match the intersection of the two datasets. Since all people in labs_wide are also in demographics, the join will have the same number of rows in labs_wide.

    +
    +
    nrow(labs_wide)
    +
    +
    [1] 8291
    +
    +
    +

    The join can be conducted using inner_join() and notice that the number of rows matches labs_wide.

    +
    +
    inner_join(demographics, labs_wide, by = "respondent_id")
    +
    +
    # A tibble: 8,291 × 24
+   respondent_id interview_examination   gender age_years age_months_sc_0_2yr
+           <dbl> <chr>                   <chr>      <dbl>               <dbl>
+ 1         73557 both interview and exam male          69                  NA
+ 2         73558 both interview and exam male          54                  NA
+ 3         73559 both interview and exam male          72                  NA
+ 4         73560 both interview and exam male           9                  NA
+ 5         73561 both interview and exam female        73                  NA
+ 6         73562 both interview and exam male          56                  NA
+ 7         73564 both interview and exam female        61                  NA
+ 8         73566 both interview and exam female        56                  NA
+ 9         73567 both interview and exam male          65                  NA
+10         73568 both interview and exam female        26                  NA
+# ℹ 8,281 more rows
+# ℹ 19 more variables: race <chr>, six_month_period <dbl>,
+#   age_months_ex_0_19yr <dbl>, served_active_duty_us <lgl>,
+#   served_active_duty_foreign <lgl>, born_usa <lgl>, citizen_usa <lgl>,
+#   time_in_us <dbl>, education_youth <dbl>, education <dbl>,
+#   marital_status <chr>, pregnant <chr>, language_english <lgl>,
+#   household_income <dbl>, ur_albumin_ug_ml <dbl>, ur_albumin_mg_l <dbl>, …
    +
    +
    +

    Note that if there were observations in labs_wide that were not in demographics, then the resulting inner join will have fewer rows than both tables.

    + + +
    + +
    + +
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@@ -0,0 +1,914 @@ + + + + + + + + + +Custom functions – Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +

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    Custom functions

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    A simple custom function

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    In this notebook, you will learn how to define your own functions.

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    # define a function called `add_one()` that adds 1 to its argument, x
    +
    +

    The code that is run when you “call” your function is inside the curly parentheses.

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    # apply function add_one() to 5
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    +
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    # apply function add_one() to 5 using a *named argument*
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    +

    What happens when the body of your function contains two pieces of code?

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    # re-define add_one() with two lines of code: x - 1 and x + 1
    +
    +
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    # apply add_one to 5 again
    +
    +

    By default, any custom R function you create will automatically return the final result that is computed.

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    For this reason, it is common to explicitly provide a “return statement”.

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    +
    # redefine add_one() but apply the return statement to x - 1 only
    +
    +
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    # apply add_one to 5 again
    +
    +
    +
    +

    The general syntax of a custom function

    +

    The general syntax of a custom function is shown below:

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    +
    fn_name <- function(arg) {
+  # code involving arg
+  
+  return(object)
+}
    +
    +
    +
    +

    Exercise

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    Write a function called “cube” that returns the cubic (^3) of the argument

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    +
    # define function cube()
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    # apply cube() to 3
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    +
    +

    Multiple arguments

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    To create a function with multiple arguments, you need to provide two arguments inside the function definition, separated by a comma. The function below has two arguments: x and y:

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    # define a function called add_x2y that computes x + 2y
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    +

    When you call this add_x2y(), you can then specify a value for each argument, separated by a comma:

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    # apply add_x2y() to x = 2 and y = 5
    +
    +

    When you have multiple arguments, funny things can start to happen when you don’t name your arguments.

    +

    What do you think will happen if you first provide a named argument for the second argument y by specifying y = 2, and then provide an unnamed argument afterwards?

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    +
    add_x2y(y = 2, 5)
    +
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    Error in add_x2y(y = 2, 5): could not find function "add_x2y"
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    +

    R will be clever and it will first apply the named arguments by assigning y to the value 2, and then fill in the remaining argument, so x will be assigned to the value 5.

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    It is good practice to name your arguments if there is any chance for ambiguity.

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    # run add_x2y() with named arguments x = 2 and y = 5
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    +

    Note that when you provide named arguments, it technically doesn’t matter which order you provide them in (but this is not true when you don’t provide named arguments!)

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    # run add_x2y() with named arguments y = 5 and x = 2
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    +

    Again, note that even when you provide named arguments in a function call (e.g., in add_x2y(x = 2, y = 5)), you are not defining a global version of the arguments, i.e., there is no y defined:

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    What do you think will happen when you call add_x2y without any parentheses?

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    +
    # run add_x2y
    +
    +

    It will print out the definition of the function!

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    What do you think will happen when you call add_x2y with parentheses but no arguments?

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    # run add_x2y()
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    You get an error! We can fix this by providing “default” values for the arguments.

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    Default values

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    To provide default values for your arguments, you can assign the argument inside the function definition. In the example below, both x and y are given the default values of 1.

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    # redefine add_x2y() with default values for x and y (both 1)
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    # call add_x2y() without any arguments
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    What happens if we only provide some of the arguments?

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    # run add_x2y() with a single unnamed argument, 4
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    # run add_x2y() with a single argument: y = 3
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    +

    Exercise

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    Without using the mean() function, write a function called my_mean() that takes four values as its arguments and computes their mean. Ensure that each argument has a default of 0. Use your function to compute the mean of the values 4, 5, 2, 1.

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    How would you modify your function to take a single vector of length 4 as its argument instead of four separate arguments?

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    Solution

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    If/else statements

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    If statements

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    The following code defines a variable a, and then runs some conditional code that is only run if the condition a == 1 is TRUE.

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    # define a variable `a` containing 5
+
+# if `a` is equal to 1, print out some text
+
+
+
+# Then:
+# 1. try the code again, with `a` equal to 1
+# 2. replace the code that is run in the if statement with a mathematical computation
+# 3. replace the code that is run in the if statement with a variable definition (e.g., define y <- 3)
    +
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    Unlike for a function, if you define a variable inside an if statement, then this variable will have been defined in our “global” environment too.

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    # Does y exist globally?
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    Else statemenets

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    The “else” part of the “if/else” statement provides some code that will be run if the “if” condition is not TRUE.

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    # define a variable "a" containing 3
+
+# if "a" equals 1, define y <- 3, else define y <- 9
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    # check what y was assigned to
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    Using “if” statements to provide custom errors for a function

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    The following uses an “if” statement to add a “stop condition” that throws an error when innapropriate arguments are provided

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    # add an "if" condition to `my_mean()` to throw an error if the 
+# first argument `a` is either non-numeric OR 
+# if the length of `a` is greater than 1
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    Exercise

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    1. Write a standalone if/else statement that checks whether the value in a variable called age is at least 18. If the age variable is 18 or older, your statement should return the character value of “You are eligible to vote” and if not, your statement should return “You are not eligible to vote”
      2. +
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    1. Write a function, circle_area(), that computes the area of a circle (area = pi * radius^2) with the radius as its argument, and throws an error if a non-numeric or a negative radius value is given.
      2. +
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    Test your function on the following code

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    # the following should throw an error:
+circle_area("4")
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    Error in circle_area("4"): could not find function "circle_area"
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    circle_area(-4)
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    Error in circle_area(-4): could not find function "circle_area"
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    # the following should NOT throw an error:
+circle_area(4)
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    Error in circle_area(4): could not find function "circle_area"
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    Default argument options with match.arg()

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    Below, we give an example of providing multiple options to an argument.

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    # define a function add_x2y() with three arguments:
+# x: a numeric value with default value 1
+# y: a numeric value with default value 1
+# output_type: a character value with default value "numeric" and alternative option "character"
+
+# in the body of the function:
+# use match.arg() to ensure that output_type is one of the options provided
+# use an if statement to modify the output based on the value of output_type
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    # apply add_x2y() to x = 2 and y = 3 and output_type = "character"
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    # apply add_x2y() to x = 2 and y = 3 with no output_type specified
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    # apply add_x2y() to x = 2 and y = 3 and output_type = "logical"
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    Exercise

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    Write a function called calculate_area() that will calculate the area of the shape specified in the argument shape, which has options “circle”, “square”, and “triangle”. Your function will need to have the following additional arguments:

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    • radius for computing the area of a circle (pi * radius^2),

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    • side for computing the area of a square (side^2),

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    • base and height for computing the area of a triangle (height * base / 2).

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    Arguments that are not always required should have a default value of NULL. Your function should throw an error when you fail any value other than “circle”, “square” or “triangle” for the shape argument (you can use match.arg() to do this!).

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    Your function should throw an error when:

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    1. the ‘radius’ argument is not provided when shape == "circle"

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    2. the ‘side’ argument is not provided when shape == "square"

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    3. the ‘base’ and ‘height’ arguments are not provided when shape == "triangle"

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    Tidy evaluation for writing tidyverse-style functions

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    Sometimes you want to write a function whose argument is a column of a data frame without quotes (i.e., in the tidyverse style) so that you can use it in a tidyverse function.

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    # load in the tidyverse and demographics NHANES data
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    # take a look at the demographics data
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    Notice that when we refer to the variables from our data frame in the context of the tidyverse (including ggplot2), we do not use quotes around the column names:

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    # Use ggplot2 to compute boxplots for the age_years distribution across 
+# different levels of the language_english variable
    +
    +

    Let’s try and turn this into a function.

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    In this first attempt, we use variable_name as the argument:

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    # turn the above boxplot code into a function called createBoxplots()
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    # try to apply createBoxplots() to the language_english column
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    The issue is that ggplot wants us to refer to the column names without quotes, but our custom function doesn’t know how to find our column name variable that we provide.

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    We can use tidy evaluation ({ var_name }) to solve this problem.

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    +
    # update our createBoxplots() function so that it uses tidy_evaluation
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    And now it works:

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    # apply createBoxplots() to the language_english column
    +
    +

    Let’s use our function on a few different columns to make sure:

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    # apply createBoxplots() to the marital_status column
+
+# apply createBoxplots() to the pregnant column
    +
    +
    +

    Tip: Using patchwork to patch together plots

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    The patchwork library can be used to create custom grids of ggplot objects (be sure to expand your plot window if the plots aren’t showing up properly):

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    # load the patchwork library
+
+# create a grid of the language_english and marital_status boxplots
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    # create a grid of the language_english and pregnant boxplots on top 
+# with the marital_status boxplots underneath
    +
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    +
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    Exercise

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    Create a function called createOrderedBars() that takes a categorical column from demographics as its argument and creates a bar chart for the average age for each level of the variable.

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    Hint: Some example code for computing the average age for each level of the marital_status variable and creating a bar chart is shown below:

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    demographics |> 
+  group_by(marital_status) |>
+  summarize(mean_age = mean(age_years)) |>
+  ggplot() +
+  geom_col(aes(x = marital_status, 
+               y = mean_age))
    +
    +

    Challenge activity: Arrange the bars in ascending order, and provide an argument called ascending that allows the user to specify whether or not the bars will be arranged in ascending order.

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    Solution

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    Note that you’ll want to use geom_col() instead of geom_bar() to create bar charts where the bars have the specific height provided in the y-variable.

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    + + + + + \ No newline at end of file diff --git a/docs/content/incomplete/02_iteration_purrr.html b/docs/content/incomplete/02_iteration_purrr.html new file mode 100644 index 0000000..e4f6335 --- /dev/null +++ b/docs/content/incomplete/02_iteration_purrr.html @@ -0,0 +1,765 @@ + + + + + + + + + +Iteration with purrr – Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    Iteration with purrr

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    The purpose of this lesson is to learn how to iteratively apply functions to all elements contained within an object, such as all columns in a data frame, or all entries in a vector.

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    The “purrr” R package that we will be using in this lesson is included in the tidyverse package.

    +
    +
    # load the tidyverse and demographics dataset
    +
    +

    The function that we want to iterate first is the n_distinct() function from the tidyverse.

    +

    Recall that to pull up the help page for a function, you can use the following syntax:

    +
    +
    # pull up the help page for n_distinct
    +
    +

    n_distinct() counts the number of unique values in a vector.

    +
    +
    # apply n_distinct to the "gender" column of demographics
    +
    +

    The code below uses the map() function to apply n_distinct() to every column of the demographics data frame simultaneously:

    +
    +
    # use map() to apply n_distinct to every column of demographics
    +
    +

    The output of the map() function is a list (more on that in a moment).

    +

    The following code shows a simpler example, this time applying the exp() function to all entries/elements in a simple numeric vector:

    +
    +
    # use map() to apply exp() to the vector c(4, 5, 6)
    +
    +
    +

    Lists

    +

    Lists, like vectors, correspond to a collection of values contained in a single object.

    +

    You can use the list() function to define a list, for example:

    +
    +
    # define a list called my_list with three elements: 1, 4, and 7
    +
    +

    You can extract elements from a list just as you would from a vector, using the square bracket notation. The code below extracts the third element from my_list:

    +
    +
    # extract the third entry from my_list using []
+
+# ask the class of the object above
    +
    +

    However, the output above is a list itself.

    +

    If you want to extract the actual object/value contained within the third element of the list, then you need to use double square parentheses:

    +
    +
    # extract the third entry from my_list using [[]]
    +
    +

    Unlike vectors, lists are not vectorized.

    +
    +
    # try to add 1 to my_list
    +
    +

    Why would we ever prefer lists to vectors? The reason is that lists are infinitely more flexible than vectors. While all entries in a vector must be a single value of the same type, entries of a list can be anything.

    +
    +
    # create a list my_complex_list containing 
+# (1) the head of demographics, 
+# (2) the value 2, and 
+# (3) a vector containing "a" and "b"
    +
    +

    You can also create a named list when defining it as if you are defining argument names:

    +
    +
    # create a named version of my_complex_list
    +
    +

    You can then extract entries from the named list using $ or [[]]

    +
    +
    # extract one of the elements from my_complex_list using $
+
+# extract one of the elements from my_complex_list using [[]]
    +
    +
    +
    +

    Exercise

    +

    Use map() to apply class() to every column in the demographics dataset, and extract the class of the household_income column.

    +
    +
    +

    Using custom functions in purrr

    +

    To iterate using your own custom functions in a purrr map() function, you can define your function and provide it in the second argument of map().

    +
    +
    # define a function called exp_plus_one() that returns exp(x) + 1
+
+# apply it to every entry in the vector c(1, 4, 5)
    +
    +

    For simple functions like this, we can define the function inside the map() function itself:

    +
    +
    # apply the function exp(x) + 1 to every entry in the vector c(1, 4, 5)
+# using an "anonymous" function
    +
    +

    However, we can go one step further and forego the function(x) part entirely using what I call the “tilde-dot” shorthand syntax.

    +

    Here, we use the tilde ~ symbol to “start” an anonymous function and we use a . to represent the argument of our anonymous function.

    +
    +
    # apply the function exp(x) + 1 to every entry in the vector c(1, 4, 5)
+# using the "tilde-dot" syntax
    +
    +

    To decide what should go inside the ~{}, I typically use a representative value to test out my code first.

    +

    Let’s count the number of missing values in each column of demographics.

    +

    For example, below, I take a single column demographics$pregnant, and I write out the code that I want to apply to it:

    +
    +
    # compute the number of missing values in the "pregnant" column of demographics
    +
    +

    Generalize this code for the map function:

    +
    +
    # use a map function to compute the number of missing values in every column
    +
    +
    +

    Exercise

    +

    Use the tilde-dot short-hand syntax to compute the number of values in each column that is equal to 1. Recall that if a vector has missing values, and you want to use sum(), you will want to provide an argument na.rm = TRUE to ignore missing values.

    +
    +
    +
    +

    Alternative map functions for outputting doubles, characters and data frames

    +

    Recall our map() function previously that we used to count the number of missing values in each column of the demographics data.

    +
    +
    map(demographics, ~sum(is.na(.)))
    +
    +

    A list may not be the most useful format for this information…

    +
    +

    Outputting numeric vectors

    +

    The map_dbl() function will output a “double” (numeric) vector.

    +
    +
    # use map_dbl to count the number of missing values in each column and
+# output a numeric vector
    +
    +
    +
    +

    Outputting character vectors

    +

    The map_chr() function can output a character vector.

    +
    +
    # use map_chr to apply class to every column and output a character vector
    +
    +
    +
    +

    Outputting data frames

    +

    One of the most versatile functions is the map_df() function, which outputs a data frame.

    +
    +
    # apply map_df to demographics to determine the class of each column, outputting a "wide" data frame
    +
    +

    If you want your output to be in a “long” format, the function you are applying must output a single-column tibble/data frame.

    +
    +
    # use tibble() to create a single-column tibble containing the class of demographics$pregnant
+
+# modify this code to be the function call in map_df to create a 
+# long-form data frame
+
+# provide an .id argument to include the original column names as a variable
    +
    +
    +
    +

    Example

    +

    This long-format is very useful if you want to create a plot, such as a bar chart for the number of missing values.

    +
    +
    # create a bar chart of the number of missing values in each column
+# use factors to order the columns by the number of missing values
    +
    +

    An alternative approach is to map_df() is to use map_dbl() and enframe()

    +
    +
    # use map_dbl() and enframe() to create a long data frame of the 
+# number of missing values in each column
    +
    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/content/incomplete/03_across.html b/docs/content/incomplete/03_across.html new file mode 100644 index 0000000..a28dc15 --- /dev/null +++ b/docs/content/incomplete/03_across.html @@ -0,0 +1,715 @@ + + + + + + + + + +Across – Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + +
    + +
    + + + + +
    + +
    +
    +

    Across

    +
    + + + +
    + + + + +
    + + + +
    + + +

    In this lesson, we will introduce the across() function, which can be used to apply dplyr functions like mutate, summarize, select, etc to subsets of columns that satisfy certain criteria, such as to all numeric columns, or all columns that start with age_.

    +
    +
    # load the tidyverse and demographics dataset
    +
    +

    Let’s suppose that our task is to convert all character columns of the demographics data to upper-case.

    +
    +
    # apply toupper() to the string value "abc"
    +
    +

    Before introducing across, let’s first see one way that we could do this using the map() functions that we have just learned:

    +
    +
    # create a copy of demographics
+
+# create a logical vector for identifying character columns using map_chr()
+
+# re-assign the character columns to an upper-case version of themselves 
+# using map_df() applied to demographics_tmp[character_cols] with toupper()
+
+
+# look at demographics_tmp
+
+# look at demographics (it should still have lowercase)
    +
    +

    While this works, it is fairly convoluted, is hard to read, and involves defining an intermediate variable (character_cols) – in the tidyverse style, it is generally recommended to avoid defining intermediate variables whenever possible.

    +
    +

    Introducing across()

    +

    We could instead do this kind of operation using a mutate() operation in conjunction with across().

    +

    Let’s figure out the code for just one column first

    +
    +
    # apply toupper to interview_examination with mutate
    +
    +

    To do this for all character columns, you need to provide across() to the argument of your mutate function. The across() function has two arguments:

    +
      +

    • The first argument is a “select statement” that specifies which columns you want to apply your function to.

      • +

    • The second argument is the function name, toupper, that we want to apply to all columns that are selected as a result of the first argument.

      • +
    +

    The result is that toupper() is applied to all columns “where” is.character() would result in TRUE:

    +
    +
    # use across inside mutate to apply toupper() to all columns 
+# where(is.character) is TRUE...
    +
    +
    +
    +

    More across examples

    +
    +

    Add 100 to all age_ columns

    +

    If we were to do this to just the age_years column, our code would look like:

    +
    +
    # use mutate to add 100 to age_years
    +
    +

    To generalize this to all columns that start with age_ using across(), we can use the starts_with() select helper, and apply the anonymous function ~{. + 100}:

    +
    +
    # use across inside mutate to apply ~{. + 100} to all columns 
+# that starts_with("age_")...
    +
    +
    +
    +

    Convert born_usa and citizen_usa to numeric (binary) columns using ends_with()

    +
    +
    # take a look at born_usa and citizen_use using select()
    +
    +
    +
    # use across inside mutate to apply as.numeric to all columns 
+# that ends_with("_usa")...
    +
    +
    +
    +

    Convert born_usa and citizen_usa to numeric (binary) columns using a vector of column names

    +

    Suppose we had a vector of column names that we wanted to modify using mutate():

    +
    +
    # define a vector selected_columns with "born_usa" and "citizen_usa"
    +
    +

    Then we could use all_of(selected_cols) in across() to apply the function to all columns listed in the selected_cols vector as follows:

    +
    +
    # use across inside mutate to apply as.numeric to all_of(selected_columns)
    +
    +
    +
    +
    +

    Select helpers summary

    +

    So far we have seen the following “select helpers” that can be used to specify the columns inside across():

    +
      +

    • where() – across to all columns that satisfy a logical condition (across(where(is.character), fun))

      • +

    • starts_with() and ends_with() – across all columns that start or ends with a specified string (across(starts_with("abc"), fun))

      • +

    • contains() – across all columns that contain a specified string (across(contains("abc"), fun))

      • +

    • all_of() and any_of() – across all columns whose names are contained in a character vector, where all_of() requires all columns in the vector be present. (across(all_of(vec_names), fun))

      • +

    • everything() – across all columns

      • +
    +

    These can also be used within select()

    +
    +
    # select all columns that contain "age"
+
+# select all columns that start with "age"
+
+# select all columns that have a logical type
    +
    +
    +

    Exercise

    +
      +

    1. For all columns that contain the word “education” (education_youth and education), add the number 5 to each value

      2. +

    2. For all numeric columns, standardize the values by subtracting the mean and dividing by the standard deviation

      3. +

    3. Compute the average age across all columns that start with age_ (Hint: use across() within summarize())

      4. +

    4. Compute the total number of TRUE values in the born_usa, citizen_usa, and language_english columns (Hint: use across() within summarize())

      5. +
    + + +
    +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/content/incomplete/04_recoding_variables.html b/docs/content/incomplete/04_recoding_variables.html new file mode 100644 index 0000000..a86d383 --- /dev/null +++ b/docs/content/incomplete/04_recoding_variables.html @@ -0,0 +1,655 @@ + + + + + + + + + +Recoding variables using if_else and case_when – Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + +
    + +
    + + + + +
    + +
    +
    +

    Recoding variables using if_else and case_when

    +
    + + + +
    + + + + +
    + + + +
    + + +
    +
    # load the tidyverse and demographics dataset
    +
    +

    In this document, you will learn how to “recode” variables by replacing values in a variable with other values of your choice, e.g., converting numerically-encoded variables to categorical/character versions, and vice versa.

    +

    We will introduce two functions for doing this:

    +
      +

    • if_else() which can be used to create binary variables (variables with just two distinct values) based on a logical “condition”

      • +

    • case_when() which can be used to create variables with many different values.

      • +
    +
    +

    if_else

    +

    Take a look at interview_examination:

    +
    +
    # apply count() to interview_examination
    +
    +

    Let’s convert it to a numeric format using if_else().

    +
    +
    # use mutate() to create a new column called interview_examination_numeric
+# which is 2 if interview_examination is "both interview and exam"
+# and 1 otherwise
+# then select just interview_examination and interview_examination_numeric
    +
    +
    +

    Exercise

    +

    Use if_else() to create a variable called completed_high_school, which has the values "yes" if education is equal to at least 3, and "no" otherwise.

    +

    A link to the documentation for the demographics data can be found here.

    +
    +
    +
    +

    case_when

    +

    The case_when() function is similar to if_else(), but it allows you to have an unlimited number of conditions and corresponding recoded values.

    +

    Take a look at the marital_status column of the demographics data:

    +
    +
    # apply count() to the marital_status column
    +
    +

    Let’s create a new variable based on marital_status that replaces

    +
      +

    • "married" with 3

      • +

    • "living_with_partner" with 2

      • +

    • "divorced", "widowed", "never_married", and "separated" with 1

      • +
    +
    +
    # use mutate and case_when() to create marital_status_numeric 
+# with the values above
    +
    +
    +
    +

    Execise

    +

    Use case_when() to convert born_usa and citizen_usa to “yes” and “no”. Bonus points: use across().

    + + +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/content/incomplete/05_pivoting.html b/docs/content/incomplete/05_pivoting.html new file mode 100644 index 0000000..c4f0100 --- /dev/null +++ b/docs/content/incomplete/05_pivoting.html @@ -0,0 +1,642 @@ + + + + + + + + + +Reshaping (Pivoting) Data – Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + +
    + +
    + + + + +
    + +
    +
    +

    Reshaping (Pivoting) Data

    +
    + + + +
    + + + + +
    + + + +
    + + +

    In this lesson, we will be working with a new NHANES table that contains urine albumin and creatinine lab data.

    +
    +
    # load the tidyverse and the urine_albumin_creatinine NHANES data
    +
    +
    +
    # take a look at the first 10 rows
    +
    +

    This data is in a long format–there are multiple rows for each observational unit, each corresponding to a different variable being measured (in this case, the different labs).

    +

    A wide format, on the other hand, will only have one row for each observational unit (respondent), and each of the individual variables being measured (the labs) will have their own column, each containing the values for the corresponding lab.

    +

    You can convert from a long format to a wide format using the pivor_wider() function.

    +

    The code below creates a wide-form version of the labs data, and saves it as a new data frame called labs_data_wide:

    +
    +
    # use pivot_wider() to convert the labs data from a 
+# long format to a wide format. 
+# arguments are `names_from` and `values_from`
+# save the wide data as `labs_data_wide`.
    +
    +

    If you want to convert from a wide format dataset into a longer-format dataset, you can instead use the pivot_longer() function.

    +
    +
    # use pivot_longer() to convert labs_data_wide back to along format
+# arguments are `cols` (use a select helper!), `names_to` and `values_to`
    +
    +

    Use-case for long-format: creating a visualization that compares the different variables using ggplot2.

    +
    +
    # create boxplots using the long format for the measurements from each lab
+# maybe add a log-scale to the y-axis
    +
    +
    +

    Exercise

    +

    Load the demographics data and use select() to select just the respondent_id, gender, marital_status and race columns and then use pivot_longer() to create the following long-format table (below are just the first 10 rows).

    +

    respondent_id name value
    +
    +1 73557 gender male
    +2 73557 marital_status separated 3 73557 race black
    +4 73558 gender male
    +5 73558 marital_status married
    +6 73558 race white
    +7 73559 gender male
    +8 73559 marital_status married
    +9 73559 race white
    +10 73560 gender male

    + + +
    + +
    + +
    + + + + + \ No newline at end of file diff --git a/docs/content/incomplete/06_joining.html b/docs/content/incomplete/06_joining.html new file mode 100644 index 0000000..5b5949d --- /dev/null +++ b/docs/content/incomplete/06_joining.html @@ -0,0 +1,686 @@ + + + + + + + + + +Joining Data Together – Advanced R for Data Science + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + +
    + +
    + + + + +
    + +
    +
    +

    Joining Data Together

    +
    + + + +
    + + + + +
    + + + +
    + + +

    This lesson introduces techniques for “joining” multiple data tables together using a “key” variable

    +

    A really helpful resource for learning about joins is the R for Data Science book (specifically the chapter about “Relational Data”).

    +

    At the end of this lesson we will have created a single data frame that contains the information from both the demographics data and the urine albumin and creatinine labs data.

    +
    +
    # load the tidyverse, 
+# load the demographics, and
+# load the urine_albumin_creatinine labs data
    +
    +
    +

    Determining what kind of join to do

    +

    There are four kinds of joins that you might want to use for combining two tables into a single table:

    +
    +
    +

    +
    Diagram of joins
    +
    +
    +
      +

    • An inner join, which will keep only the data for the observational units that appear in both tables

      • +

    • A left join, which will keep all of the data for the observational units in the first (left) table, and will add missing values when there is no available data in the second table.

      • +

    • A right join, which will keep all of the data for the observational units in the second (right) table, and will add missing values when there is no available data in the first table.

      • +

    • A full join, which will keep all of the data for the observational units in both the first (left) table, and will add missing values when there is no available data in the other table.

      • +
    +

    The kind of join that you will implement will depend on what you want to use your joined data for.

    +
    +

    Checking the uniqueness of the key ID variables

    +

    Below, we see that the respondent_id column is indeed unique for demographics:

    +
    +
    # check whether the respondent ID values in demographics are unique?
    +
    +

    But not for labs:

    +
    +
    # check whether the respondent ID values in labs are unique?
    +
    +
    +
    +

    Checking overlap between tables

    +

    Are there any observations in the demographics table that do not appear in the labs table?

    +
    +
    # Compute the proportion of people in demographics who are also in labs
    +
    +

    The calculation above shows that around 81% of observations in the demographics table have available labs data.

    +

    Are there any observations in the labs table that do not appear in the demographics table?

    +
    +
    # proportion of people in labs who are also in demographics
    +
    +

    The calculation above shows that 100% of observations in the labs table have available demographics data.

    +
    +
    +
    +

    Joining demographics and labs

    +

    Our two options for to join demographics (left) and labs (right) are:

    +
      +

    • An inner or right join will only keep the 81% of people in demographics who have available labs data

      • +

    • A left or full join will keep all people in demographics data, and join missing values for those who don’t have labs data available

      • +
    +

    Since we don’t want to discard any data, we will choose the left/full join.

    +
    +
    # perform a left/full join of demographics and labs
    +
    +

    Look at the results above, does something look wrong to you?

    +

    If your key ID variable has repeated values, your joined data will too.

    +

    A good check after completing a join is to make sure that the number of rows in the resulting joined data matches what you expect

    +
    +
    # check the number of rows in the joined data
+
+# check the number of rows in demographics
    +
    +

    Therefore, to ensure that we have just one row per observational unit (i.e., per respondent_id value), we need to join the wide-format labs_wide data instead of the long-format labs data.

    +
    +
    # compute the wide format of the labs data
    +
    +
    +
    # join demographics and labs_wide
    +
    +
    +
    +

    Exercise

    +

    How many rows would you expect an inner join of demographics and labs_wide to have? Check your answer by conducting the join using inner_join()

    + + +
    + +
    + +
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Analysis – Advanced R for Data Science