In most real-world research data, we have multiple categorical variables. Though we can summarize these variables using cross-tabulation, if we want to visualize this through the bar chart, we can do so easily. In this recipe, we will see how we can produce a bar chart in order to visualize cross-tabulation.
To produce a bar chart from cross-tabulation, we will add two new variables with the dataset that we used in the first two recipes. The new variable will represent the sex and economic status. Here is the code that prepares the dataset:
# Set a seed value to make the data reproducible
set.seed(12345)
cross_tabulation_data <-data.frame(disA=rnorm(n=100,mean=20,sd=3),
disB=rnorm(n=100,mean=25,sd=4),
disC=rnorm(n=100,mean=15,sd=1.5),
age=sample((c(1,2,3,4)),size=100,replace=T),
sex=sample(c("Male","Female"),size=100,replace=T),
econ_status=sample...