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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

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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(___)
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