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Hi all, I have 630 columns and can't get it to work. My code is;
library(corrr) brand_data <- read.csv("data.csv", header = TRUE) df <- correlate(brand_data) df %>% fashion() df %>% network_plot(min_cor=0) df %>% rplot
The error is Error in stats::cmdscale(abs(distance)) : NA values not allowed in 'd'
Error in stats::cmdscale(abs(distance)) : NA values not allowed in 'd'
However, when I run;
df <- brand_data %>% correlate() %>% focus(var1, var2, var3, var4, mirror = TRUE)
It works just fine. Is this due to a limitation in the amount of columns corrr can process?
The text was updated successfully, but these errors were encountered:
Hi, can you try?
df %>% select_if(is.numeric) %>% filter_all(all_vars(!is.na(.) == TRUE)) %>% correlate()
Sorry, something went wrong.
filter_all(all_vars(!is.na(.))) %>% correlate() works
filter_all(all_vars(!is.na(.))) %>% correlate()
filter_all(all_vars(!is.na(.) == TRUE)) %>% correlate()
doesnt
This reprex hangs:
library(corrr) library(dplyr) data(pd_speech, package = "modeldata") df <- correlate(pd_speech %>% select(-class)) corr_info <- df %>% fashion() corr_network <- df %>% network_plot(min_cor=0) corr_plot <- df %>% rplot
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Hi all, I have 630 columns and can't get it to work. My code is;
The error is
Error in stats::cmdscale(abs(distance)) : NA values not allowed in 'd'
However, when I run;
df <- brand_data %>% correlate() %>% focus(var1, var2, var3, var4, mirror = TRUE)
It works just fine. Is this due to a limitation in the amount of columns corrr can process?
The text was updated successfully, but these errors were encountered: