If I am working on data with a binary response, I like to use the GGally package for its ggpairs function. It provides a way to look at a lot of different data types at the same time but the setup and customization can be a little daunting. In this example, which leverages this crime data, I demonstrate how ggpairs can be used to reveal a lot of information in a single figure.

Purpose Today I review a data set containing information on approximately 8,000 customers of an insurance company. Each record contains two response variables that indicate whether a customer was in a car crash or not and how much said car-crash cost. library(tidyverse) library(stargazer) library(GGally) library(kableExtra) library(ResourceSelection) library(RCurl) library(pROC) clr_dollar <- function(x){ # cleans out commas and $ of string-formatted currency return(as.numeric(gsub('[$,]','',x))) } # Mappings to clean-up data entries for easier manipulation and analysis job_map <- data.