Visualizing missing cases and variables

To get a clear picture of the missingness across variables and cases, use gg_miss_var() and gg_miss_case(). These are the visual counterpart to miss_var_summary() and miss_case_summary().

These can be split up into multiple plots with one for each category by choosing a variable to facet by.

Using the riskfactors dataset:

Visualize the number of missings in cases using gg_miss_case().
Explore the number of missings in cases using gg_miss_case() and facet by the variable education.
Visualize the number of missings in variables using gg_miss_var().
Explore the number of missings in variables using gg_miss_var() and facet by the variable education.

What do you notice in the visualizations of the whole data compared to the faceting?

Take Hint (-30 XP)

Exercise

Visualizing missing cases and variables

Instructions