nanull: NA / NULL Check

In oliver-wyman-actuarial/easyr: Helpful Functions from Oliver Wyman Actuarial Consulting

NA / NULL Check

Description

Facilitates checking for missing values which may cause errors later in code. NULL values can cause errors on is.na checks, and is.na can cause warnings if it is inside if() and is passed multiple values. This function makes it easier to check for missing values before trying to operate on a variable. It will NOT check for strings like "" or "NA". Only NULL and NA values will return TRUE. Author: Bryce Chamberlain. Tech Review: Maria Gonzalez.

Usage

nanull(x, na_strings = easyr::nastrings, do.test.each = FALSE)

Arguments

x	Vector to check. In the case of a data frame or vector, it will check the first (non-NULL) value.
na_strings	(Optional) Set the strings you want to consider NA. These will be applied after stringr::str_trim on x.
do.test.each	Return a vector of results to check each element instead of checking the entire object.

Value

True/false indicating if the argument is NA, NULL, or an empty/NA string/vector. For speect, only the first value is checked.

Examples

nanull( NULL )
nanull( NA )
nanull( c( NA , NULL ) )
nanull( c( 1, 2, 3 ) )
nanull( c( NA, 2, 3 ) )
nanull( c( 1, 2, NA ) ) # only the first values is checked, so this will come back FALSE.
nanull( c( NULL, 2, 3 ) ) # NULL values get skipped in a vector.
nanull( data.frame() )
nanull( dplyr::group_by( dplyr::select( cars, speed, dist ), speed ) ) # test a tibble.

oliver-wyman-actuarial/easyr documentation built on Jan. 27, 2024, 4:37 a.m.