summary.missingness: Summarizes data given by 'missingness'

In healthcareai: Tools for Healthcare Machine Learning

Summarizes data given by missingness

Description

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.

Usage

## S3 method for class 'missingness'
summary(object, ...)

Arguments

object	Data frame from missingness
...	Unused

Value

a tibble of the top 5 missingness percentage levels with the count of the number of variables associated with each level. If no missingness is found, NULL is returned instead.

Examples

missingness(pima_diabetes) %>%
  summary()

healthcareai documentation built on Sept. 5, 2022, 5:12 p.m.