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Provide a tidy table of the number of cases with 0, 1, 2, up to n, missing values and the proportion of the number of cases those cases make up.

Usage

miss_case_table(data)

Arguments

data

a dataframe

Value

a dataframe

Examples


miss_case_table(airquality)
#> # A tibble: 3 × 3
#>   n_miss_in_case n_cases pct_cases
#>            <int>   <int>     <dbl>
#> 1              0     111     72.5 
#> 2              1      40     26.1 
#> 3              2       2      1.31
if (FALSE) {
library(dplyr)
airquality %>%
  group_by(Month) %>%
  miss_case_table()
}