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Tabulating Missingness

The summaries of missingness we just calculated give us the number and percentage of missing observations for the cases and variables.

Another way to summarize missingness is by tabulating the number of times that there are 0, 1, 2, 3, missings in a variable, or in a case.

In this exercise we are going to tabulate the number of missings in each case and variable using miss_var_table() and miss_case_table(), and also combine these summaries with the the group_by operator from dplyr. to explore the summaries over a grouping variable in the dataset.

Este exercício faz parte do curso

Dealing With Missing Data in R

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Instruções do exercício

For the airquality dataset:

  • Tabulate missingness for each variable using miss_var_table().
  • Tabulate missingness for every case using miss_case_table().
  • Combine previous tabulations with dplyr's group_by() function to create tabulations for each variable and case, by each Month.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# Tabulate missingness in each variable and case of the `airquality` dataset
___(airquality)
___(___)

# Tabulate the missingness in each variable, grouped by Month, in the `airquality` dataset
airquality %>% group_by(___) %>% miss_var_table()

# Tabulate of missingness in each case, grouped by Month, in the `airquality` dataset
airquality %>% ___ %>% miss_case_table()
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