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

miss_var_table(data)

Arguments

data

a dataframe

Value

a dataframe

See also

Examples

miss_var_table(airquality)
#> # A tibble: 3 x 3 #> n_miss_in_var n_vars pct_vars #> <int> <int> <dbl> #> 1 0 4 66.7 #> 2 7 1 16.7 #> 3 37 1 16.7
if (FALSE) { library(dplyr) airquality %>% group_by(Month) %>% miss_var_table() }