correlation matrix of a bunch of categorical variables in R

Question

I have about 20 variables about different cities labeled "Y" or "N" and are factors. The variables are like "has co-op" and the such. I want to find some correlations and possibly use the corrplot package to display the connections between all these variables. But for some reason I cannot coerce the variables so that they are read in a way corrplot or even cor() likes so that I can get them in a matrix. I tried:

 M <- cor(model.matrix(~.-1,data=mydata[c(25:44)]))

but the results in corrplot came out really weird. Does anyone have a fast way to turn a bunch of Y/N answers into a correlation matrix? Thanks!

Answer 1

You can use the sjp.corr function or sjt.corr function for graphical or tabular output, both from the sjPlot-package.

DF <- data.frame(v1 = sample(c("Y","N"), 100, T),
                 v2 = sample(c("Y","N"), 100, T),
                 v3 = sample(c("Y","N"), 100, T),
                 v4 = sample(c("Y","N"), 100, T),
                 v5 = sample(c("Y","N"), 100, T))
DF[] <- lapply(DF,as.integer)
library(sjPlot)
sjp.corr(DF)
sjt.corr(DF)

The plot:

The table (in RStudio viewer pane):

You can use many parameters to modify the appearance of the plot or table, see some examples here.