# vec_unique

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##### Find and count unique values

• 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 containining 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.

##### 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.)

##### Performance

These functions are currently slightly slower than their base equivalents. This is primarily because they do a little more checking and coercion in R, which makes them both a litter safer and more generic. Additionally, the C code underlying vctrs has not yet been implemented: we expect some performance improvements when that happens.

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

##### Aliases
• vec_unique
• vec_unique_loc
• vec_unique_count
##### Examples
# NOT RUN {
x <- rpois(100, 8)
vec_unique(x)
vec_unique_loc(x)
vec_unique_count(x)

# vec_unique() returns values in the order that encounters them
# use sort = "location" to match to the result of vec_count()
head(vec_count(x, sort = "location"))

# Normally missing values are not considered to be equal
NA == NA

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

Documentation reproduced from package vctrs, version 0.1.0, License: GPL-3

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