Summarizing missingness
Now that you understand the behavior of missing values in R, and how to count them, let's scale up our summaries for cases (rows) and variables, using miss_var_summary()
and miss_case_summary()
, and also explore how they can be applied for groups in a dataframe, using the group_by
function from dplyr
.
This exercise is part of the course
Dealing With Missing Data in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Summarize missingness in each variable of the `airquality` dataset
miss_var_summary(___)