Calculating Ratios within a Variable by Group in DataFrames

Introduction

Calculating ratios within a variable by group is a common task in data analysis, particularly when working with datasets that have categorical variables and numerical values. In this article, we will explore how to calculate the ratio of an item’s price to its total household expenses for each household, considering specific items as ’temptation goods'.

Problem Statement

Suppose we have a DataFrame df containing information about households and their purchases:

We want to calculate the percentage of each household’s total expenses that consists of ’temptation goods’, i.e., items with a specific price.

Solution Overview

To solve this problem, we will use the dcast function from the data.table package in R. This function allows us to reshape and transform data while preserving their structure.

Step 1: Load Required Libraries and Create Data

First, let’s load the necessary libraries and create a sample DataFrame:

library(data.table)
library(scales)

df <- data.table(HouseholdID = c("1", "2","2", "3", "3", "4"),
                 ItemNo  = c("23", "25", "23", "26", "23", "24"),
                 ItemPrice= c(200, 300, 200, 500, 200, 900),
                 TotalHouseholdExpenses = c(200, 500, 500, 700, 700, 900))

Step 2: Calculate Ratios using dcast

Next, we’ll use the dcast function to reshape our data and calculate the desired ratios:

# Create a new column for 'temptation goods'
df$TemptationGoods <- c(TRUE, TRUE, FALSE, FALSE, TRUE, TRUE)

# Define the transformation using dcast
transformed_df <- dcast(df, HouseholdID + TotalHouseholdExpenses ~ ItemNo,
                      value.var = "ItemPrice") %>%
  mutate(across(3:(2+length(unique(ItemNo))), 
               function(x) ifelse(TemptationGoods == TRUE, x / TotalHouseholdExpenses, NA)))

Alternatively, you can use the dcast function with a more concise syntax:

transformed_df <- dcast(df, HouseholdID + TotalHouseholdExpenses ~ ItemNo,
                      value.var = "ItemPrice") %>%
  mutate(across((3:length(unique(ItemNo))) - 2:1,
                function(x) ifelse(TemptationGoods == TRUE, x / TotalHouseholdExpenses, NA)))

Step 3: Format Ratios as Percentage

To format the ratios as percentages, you can use the scales library:

# Apply label_percent() to formats ratios as percentage
transformed_df <- transformed_df %>%
  mutate(across((3:length(unique(ItemNo))) - 2:1,
                ~ label_percent(.x / TotalHouseholdExpenses)))

Output

The final transformed DataFrame will have the desired ratios in the new columns:

By following these steps, you can calculate the ratio of an item’s price to its total household expenses for each household, considering specific items as ’temptation goods'.

Last modified on 2024-04-18