miss_prop_summary: Proportions of missings in data, variables, and cases.

In njtierney/naniar: Data Structures, Summaries, and Visualisations for Missing Data

Proportions of missings in data, variables, and cases.

Description

Return missing data info about the dataframe, the variables, and the cases. Specifically, returning how many elements in a dataframe contain a missing value, how many elements in a variable contain a missing value, and how many elements in a case contain a missing.

Usage

miss_prop_summary(data)

Arguments

data	a dataframe

Value

a dataframe

See Also

pct_miss_case() prop_miss_case() pct_miss_var() prop_miss_var() pct_complete_case() prop_complete_case() pct_complete_var() prop_complete_var() miss_prop_summary() miss_case_summary() miss_case_table() miss_summary() miss_var_run() miss_var_span() miss_var_summary() miss_var_table()

Examples

miss_prop_summary(airquality)
## Not run: 
library(dplyr)
# respects dplyr::group_by
airquality %>% group_by(Month) %>% miss_prop_summary()

## End(Not run)

njtierney/naniar documentation built on March 19, 2024, 9:48 p.m.