Interpreting missingness
results from wide
datasets is difficult. This function helps interpret missingness output by
summarizing this output by listing: the percent of variables that
contain missingness, the variable name of the variable with the maximum
amount of missingness along with its percent of observations containing
missing values, and a tibble that lists the top 5 missingness levels with
the count of the number of variables associated with each level (0
missingness level is ignored). If there are no variables with missingness,
a message that reports no missingness is printed and NULL is returned
instead.