• vec_duplicate_any(): detects the presence of duplicated values, similar to anyDuplicated().

• vec_duplicate_detect(): returns a logical vector describing if each element of the vector is duplicated elsewhere. Unlike duplicated(), it reports all duplicated values, not just the second and subsequent repetitions.

• vec_duplicate_id(): returns an integer vector giving the location of the first occurence of the value.

vec_duplicate_any(x)

vec_duplicate_detect(x)

vec_duplicate_id(x)

## Arguments

x A vector (including a data frame).

## Value

• vec_duplicate_any(): a logical vector of length 1.

• vec_duplicate_detect(): a logical vector the same length as x.

• vec_duplicate_id(): an integer vector the same length as x.

## 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.)

vec_unique() for functions that work with the dual of duplicated values: unique values.

## Examples

vec_duplicate_any(1:10)
#> [1] FALSE
vec_duplicate_any(c(1, 1:10))
#> [1] TRUE
x <- c(10, 10, 20, 30, 30, 40) vec_duplicate_detect(x)
#> [1] TRUE TRUE FALSE TRUE TRUE FALSE
# Note that duplicated() doesn't consider the first instance to # be a duplicate duplicated(x)
#> [1] FALSE TRUE FALSE FALSE TRUE FALSE
# Identify elements of a vector by the location of the first element that # they're equal to: vec_duplicate_id(x)
#> [1] 1 1 3 4 4 6
# Location of the unique values: vec_unique_loc(x)
#> [1] 1 3 4 6
# Equivalent to duplicated(): vec_duplicate_id(x) == seq_along(x)
#> [1] TRUE FALSE TRUE TRUE FALSE TRUE