12.3. Special Charts

12.3.1. Missing Data Map

While doing exploratory data analysis, it is important to identify variables which have a lot of missing data.

Let’s see the variation of missing data in air quality dataset:

> sapply(airquality, function(x){sum(is.na(x))})
  Ozone Solar.R    Wind    Temp   Month     Day
     37       7       0       0       0       0

Amelia library provides a function to visualize this:

> require(Amelia)
> mismap(airquality)