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Find and count unique values

Source: R/dictionary.R
vec_unique.Rd

  • vec_unique(): the unique values. Equivalent to unique().

  • vec_unique_loc(): the locations of the unique values.

  • vec_unique_count(): the number of unique values.

Usage

vec_unique(x)

vec_unique_loc(x)

vec_unique_count(x)

Arguments

x

A vector (including a data frame).

Value

  • vec_unique(): a vector the same type as x containing only unique values.

  • vec_unique_loc(): an integer vector, giving locations of unique values.

  • vec_unique_count(): an integer vector of length 1, giving the number of unique values.

Dependencies

Missing values

In most cases, missing values are not considered to be equal, i.e. NA == NA is not TRUE. This behaviour would be unappealing here, so these functions consider all NAs to be equal. (Similarly, all NaN are also considered to be equal.)

See also

vec_duplicate for functions that work with the dual of unique values: duplicated values.

Examples

x <- rpois(100, 8)
vec_unique(x)
#>  [1]  4 13 10  5  8  7  9  6 15 12 11 14  2
vec_unique_loc(x)
#>  [1]  1  2  3  4  5  8  9 11 14 20 25 27 31
vec_unique_count(x)
#> [1] 13

# `vec_unique()` returns values in the order that encounters them
# use sort = "location" to match to the result of `vec_count()`
head(vec_unique(x))
#> [1]  4 13 10  5  8  7
head(vec_count(x, sort = "location"))
#>   key count
#> 1   4     3
#> 2  13     4
#> 3  10     6
#> 4   5     9
#> 5   8    15
#> 6   7    17

# Normally missing values are not considered to be equal
NA == NA
#> [1] NA

# But they are for the purposes of considering uniqueness
vec_unique(c(NA, NA, NA, NA, 1, 2, 1))
#> [1] NA  1  2