add_n_miss: Add column containing number of missing data values

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

Add column containing number of missing data values

Description

It can be useful when doing data analysis to add the number of missing data points into your dataframe. add_n_miss adds a column named "n_miss", which contains the number of missing values in that row.

Usage

add_n_miss(data, ..., label = "n_miss")

Arguments

data	a dataframe
...	Variable names to use instead of the whole dataset. By default this looks at the whole dataset. Otherwise, this is one or more unquoted expressions separated by commas. These also respect the dplyr verbs starts_with, contains, ends_with, etc. By default will add "_all" to the label if left blank, otherwise will add "_vars" to distinguish that it has not been used on all of the variables.
label	character default is "n_miss".

Value

a dataframe

See Also

bind_shadow() add_any_miss() add_label_missings() add_label_shadow() add_miss_cluster() add_prop_miss() add_shadow_shift() cast_shadow()

Examples

airquality %>% add_n_miss()
airquality %>% add_n_miss(Ozone, Solar.R)
airquality %>% add_n_miss(dplyr::contains("o"))

naniar documentation built on May 29, 2024, 1:43 a.m.