chipotle.Rmd

---
title: "chipotle.Rmd"
author: "minnawin"
date: "June 21, 2015"
output: html_document
---
Data from GrubHub for Chipotle Restaurant order.July-December 2012 for Washington, D.C. and East Lansing, MI.  Data provided by the *The New York Times*, for the article *"At Chipotle, How Many Calories Do People Really Eat"*        
------

***
```{r read_and_process,echo=FALSE}
      #library(dplyr)
      library(reshape2)
      ##Read and Process Data
      df <- read.csv("./orders.tsv",sep="\t")
      #print(head(df,10))
      #print(tail(df,10))
     # print(names(df))

      #Convert item_price from char string to float, first remove the $
      prices <- gsub("\\$","",df$item_price)
      df$item_price<-as.numeric(prices)
```

####**Total in sales for this data: $**`r format(sum(df$item_price), digits=12,decimal.mark=".",big.mark=", ", small.mark=".", small.interval=3)`  

****
```{r most_ordered}
    #Most ordered item
    items.factors <- factor(df$item_name)
    ux <- unique(items.factors)
    most.ordered <-ux[which.max(tabulate(match(items.factors,ux)))]
```

####**Most ordered item for this study: **  *`r most.ordered`*

****
```{r avg_num_items}
    #Average number of items per order
    melted.df <- melt(df,id=c("order_id"),measure=c("quantity"))
    sum.quantity.by.orderid <- dcast(melted.df, order_id ~ variable,sum)

    #Now get the average of all the quantities over the order_ids
    average.order.qty <- mean(sum.quantity.by.orderid$quantity)
```  


####**Average number of items per order** *(i.e. how many things make up a typical order)*:  `r format(average.order.qty,digits=2,nsmall=2 )`

****
```{r avg_order_total}
   #First, calculate each order total
   melted.order.cost <- melt(df,id=c("order_id"),measure=c("item_price"))
   sum.order.totals <- dcast(melted.order.cost, order_id ~ variable, sum )
   avg.order.totals <- mean(sum.order.totals$item_price)

```    

####**Average total for order:** $ `r format(avg.order.totals,digits=2,nsmall=2)`

****
Determine how many vegetarian-based/veggie-based items are selected/ordered
```{r veggie}
   #subset the data frame based on any item_name that looks like "veg", "VEG"...
   
```