healthcareai (version 2.3.0)

summary.missingness: 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 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

# NOT RUN {
missingness(pima_diabetes) %>%
  summary()

# }

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