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  3. Dealing With Missing Data in R

Exercise

Your first missing data visualizations

It can be difficult to get a handle on where the missing values are in your data, and here is where visualization can really help.

The function vis_miss() creates an overview visualization of the missingness in the data. It also has options to cluster rows based on missingness, using cluster = TRUE; as well as options for sorting the columns, from most missing to least missing (sort_miss = TRUE).

Instructions

100 XP

Using the riskfactors dataset from naniar:

  • Use vis_miss() to visualize the missingness in the data.
  • Use vis_miss() with cluster = TRUE to explore some clusters of missingness.
  • Use vis_miss() and sort the missings with sort_miss to arrange the columns by missingness.