Learn R Programming

rlang (version 1.1.2)

are_na: Test for missing values

Description

[Questioning]

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

Life cycle

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

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.

Examples

Run this code
# 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)

Run the code above in your browser using DataLab