R: Test for missing values

are_na {rlang} | R Documentation

## 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.

### 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)

[Package rlang version 0.1.6 Index]