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.

miss_case_table(data)

Arguments

data

a dataframe

Value

a dataframe

See also

Examples

miss_case_table(airquality)
#> # A tibble: 3 x 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() }