Skip to contents

Counting-Generalization of duplicated()

Duplicated.Rd

Duplicated() generalizes the duplicated method for vectors, by returning indices of “equivalence classes” for duplicated entries and returning nomatch (NA by default) for unique entries.

Note that duplicated() is not TRUE for the first time a duplicate appears, whereas Duplicated() only marks unique entries with nomatch (NA).

Usage

Duplicated(v, incomparables = FALSE, fromLast = FALSE, nomatch = NA_integer_)

Arguments

v

a vector, often character, factor, or numeric.

incomparables

a vector of values that cannot be compared, passed to both duplicated() and match(). FALSE is a special value, meaning that all values can be compared, and may be the only value accepted for methods other than the default. It will be coerced internally to the same type as x.

fromLast

logical indicating if duplication should be considered from the reverse side, i.e., the last (or rightmost) of identical elements would correspond to duplicated=FALSE.

nomatch

passed to match(): the value to be returned in the case when no match is found. Note that it is coerced to integer.

Value

an integer vector of the same length as v. Can be used as a factor, e.g., in split, tapply, etc.

Author

Christoph Buser and Martin Maechler, Seminar fuer Statistik, ETH Zurich, Sep.2007

See also

uniqueL (also in this sfsmisc package); duplicated, match.

Examples

x <- c(9:12, 1:4, 3:6, 0:7)
data.frame(x, dup = duplicated(x),
              dupL= duplicated(x, fromLast=TRUE),
              Dup = Duplicated(x),
              DupL= Duplicated(x, fromLast=TRUE))
#>     x   dup  dupL Dup DupL
#> 1   9 FALSE FALSE  NA   NA
#> 2  10 FALSE FALSE  NA   NA
#> 3  11 FALSE FALSE  NA   NA
#> 4  12 FALSE FALSE  NA   NA
#> 5   1 FALSE  TRUE   3    1
#> 6   2 FALSE  TRUE   4    2
#> 7   3 FALSE  TRUE   1    3
#> 8   4 FALSE  TRUE   2    4
#> 9   3  TRUE  TRUE   1    3
#> 10  4  TRUE  TRUE   2    4
#> 11  5 FALSE  TRUE   7    7
#> 12  6 FALSE  TRUE   8    8
#> 13  0 FALSE FALSE  NA   NA
#> 14  1  TRUE FALSE   3    1
#> 15  2  TRUE FALSE   4    2
#> 16  3  TRUE FALSE   1    3
#> 17  4  TRUE FALSE   2    4
#> 18  5  TRUE FALSE   7    7
#> 19  6  TRUE FALSE   8    8
#> 20  7 FALSE FALSE  NA   NA