Chapter 5 Missing data

Superheat deals with missing values gracefully by filling them in with a color of your choice (the default is grey).

library(superheat)
# replace some values with missing values
mtcars.missing <- mtcars
mtcars.missing[sample(1:nrow(mtcars), 5),
               sample(1:ncol(mtcars), 5)] <- NA

superheat(mtcars.missing,
          # scale the matrix
          scale = T)

5.1 Color

You can set the color of missing values by setting heat.na.col to a color of your choice.

superheat(mtcars.missing,
          # scale the matrix
          scale = T,
          
          # change color of missing values
          heat.na.col = "white")