are_na: Test for missing values

In tidyverse/rlang: Functions for Base Types and Core R and 'Tidyverse' Features

Test for missing values

Description

are_na() checks for missing values in a vector and is equivalent to base::is.na(). It is a vectorised predicate, meaning that its output is always the same length as its input. On the other hand, is_na() is a scalar predicate and always returns a scalar boolean, TRUE or FALSE. If its input is not scalar, it returns FALSE. Finally, there are typed versions that check for particular missing types.

Usage

are_na(x)

is_na(x)

is_lgl_na(x)

is_int_na(x)

is_dbl_na(x)

is_chr_na(x)

is_cpl_na(x)

Arguments

x	An object to test

Details

The scalar predicates accept non-vector inputs. They are equivalent to is_null() in that respect. In contrast the vectorised predicate are_na() requires a vector input since it is defined over vector values.

Life cycle

These functions might be moved to the vctrs package at some point. This is why they are marked as questioning.

Examples

# are_na() is vectorised and works regardless of the type
are_na(c(1, 2, NA))
are_na(c(1L, NA, 3L))

# is_na() checks for scalar input and works for all types
is_na(NA)
is_na(na_dbl)
is_na(character(0))

# There are typed versions as well:
is_lgl_na(NA)
is_lgl_na(na_dbl)

tidyverse/rlang documentation built on Oct. 31, 2024, 5:35 p.m.