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  3. Handling Missing Data with Imputations in R

Exercise

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!

Instructions 1/2

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  • Load the VIM package.
  • Pass the biopics data to the correct plotting function to draw an aggregation plot.
  • Set combined and numbers to TRUE.