# AllDuplicated: Index Vector of All Values Involved in Ties In AndriSignorell/DescTools: Tools for Descriptive Statistics

## Description

The function `duplicated` returns a logical vector indicating which elements x are duplicates, but will not include the very first appearance of subsequently duplicated elements. `AllDuplicated` returns an index vector of ALL the values in `x` which are involved in ties.
So `!AllDuplicated` can be used to determine all elements of x, which appear exactly once (thus with frequency 1).

## Usage

 `1` ```AllDuplicated(x) ```

## Arguments

 `x` vector of any type.

## Value

logical vector of the same dimension as x.

## Author(s)

Andri Signorell <andri@signorell.net>

## See Also

`unique` returns a unique list of all values in x
`duplicated` returns an index vector flagging all elements, which appeared more than once (leaving out the first appearance!)
`union`(A, B) returns a list with the unique values from A and B
`intersect` returns all elements which appear in A and in B
`setdiff`(A, B) returns all elements appearing in A but not in B
`setequal`(A, B) returns `TRUE` if A contains exactly the same elements as B
`split`(A, A) returns a list with all the tied values in A (see examples)

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43``` ```x <- c(1:10, 4:6) AllDuplicated(x) # compare to: duplicated(x) x[!AllDuplicated(x)] # union, intersect and friends... A <- c(sort(sample(1:20, 9)),NA) B <- c(sort(sample(3:23, 7)),NA) # all elements from A and B (no duplicates) union(A, B) # all elements appearing in A and in B intersect(A, B) # elements in A, but not in B setdiff(A, B) # elements in B, but not in A setdiff(B, A) # Does A contain the same elements as B? setequal(A, B) # Find ties in a vector x x <- sample(letters[1:10], 20, replace=TRUE) ties <- split(x, x) # count tied groups sum(sapply(ties, length) > 1) # length of tied groups (x <- sapply(ties, length))[x>1] # by means of table tab <- table(x) tab[tab>1] # count elements involved in ties sum(tab>1) # count tied groups sum(tab[tab>1]) ```

AndriSignorell/DescTools documentation built on April 8, 2021, 5:51 a.m.