Aggregation plot
The aggregation plot provides the answer to the basic question one may ask about an incomplete dataset: in which combinations of variables the data are missing, and how often? It is very useful for gaining a high-level overview of the missingness patterns. For example, it makes it immediately visible if there is some combination of variables that are often missing together, which might suggest some relation between them.
In this exercise, you will first draw the aggregation plot for the biopics
data and then practice making conclusions based on it. Let's do some plotting!
This exercise is part of the course
Handling Missing Data with Imputations in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Load the VIM package
library(___)
# Draw an aggregation plot of biopics
biopics %>%
___(combined = ___, numbers = ___)