are_na

0th

Percentile

Test for missing values

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.

Aliases
  • are_na
  • is_na
  • is_lgl_na
  • is_int_na
  • is_dbl_na
  • is_chr_na
  • is_cpl_na
Examples
# NOT RUN {
# 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)
# }
Documentation reproduced from package rlang, version 0.1.6, License: GPL-3

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