duplicated
Determine Duplicate Elements
duplicated()
determines which elements of a vector or data frame are duplicates
of elements with smaller subscripts, and returns a logical vector
indicating which elements (rows) are duplicates.
anyDuplicated(.)
is a “generalized” more efficient
shortcut for any(duplicated(.))
.
Usage
duplicated(x, incomparables = FALSE, ...)
"duplicated"(x, incomparables = FALSE, fromLast = FALSE, nmax = NA, ...)
"duplicated"(x, incomparables = FALSE, MARGIN = 1, fromLast = FALSE, ...)
anyDuplicated(x, incomparables = FALSE, ...)
"anyDuplicated"(x, incomparables = FALSE, fromLast = FALSE, ...)
"anyDuplicated"(x, incomparables = FALSE, MARGIN = 1, fromLast = FALSE, ...)
Arguments
 x
 a vector or a data frame or an array or
NULL
.  incomparables
 a vector of values that cannot be compared.
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 asx
.  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
.  nmax
 the maximum number of unique items expected (greater than one).
 ...
 arguments for particular methods.
 MARGIN
 the array margin to be held fixed: see
apply
, and note thatMARGIN = 0
maybe useful.
Details
These are generic functions with methods for vectors (including lists), data frames and arrays (including matrices).
For the default methods, and whenever there are equivalent method
definitions for duplicated
and anyDuplicated
,
anyDuplicated(x, ...)
is a “generalized” shortcut for
any(duplicated(x, ...))
, in the sense that it returns the
index i
of the first duplicated entry x[i]
if
there is one, and 0
otherwise. Their behaviours may be
different when at least one of duplicated
and
anyDuplicated
has a relevant method.
duplicated(x, fromLast = TRUE)
is equivalent to but faster than
rev(duplicated(rev(x)))
.
The data frame method works by pasting together a character
representation of the rows separated by \r
, so may be imperfect
if the data frame has characters with embedded carriage returns or
columns which do not reliably map to characters.
The array method calculates for each element of the subarray
specified by MARGIN
if the remaining dimensions are identical
to those for an earlier (or later, when fromLast = TRUE
) element
(in rowmajor order). This would most commonly be used to find
duplicated rows (the default) or columns (with MARGIN = 2
).
Note that MARGIN = 0
returns an array of the same
dimensionality attributes as x
.
Missing values are regarded as equal, but NaN
is not equal to
NA_real_
.
Values in incomparables
will never be marked as duplicated.
This is intended to be used for a fairly small set of values and will
not be efficient for a very large set.
When used on a data frame with more than one column, or an array or matrix when comparing dimensions of length greater than one, this tests for identity of character representations. This will catch people who unwisely rely on exact equality of floatingpoint numbers!
Character strings will be compared as byte sequences if any input is
marked as "bytes"
(see Encoding
).
Except for factors, logical and raw vectors the default nmax = NA
is
equivalent to nmax = length(x)
. Since a hash table of size
8*nmax
bytes is allocated, setting nmax
suitably can
save large amounts of memory. For factors it is automatically set to
the smaller of length(x)
and the number of levels plus one (for
NA
). If nmax
is set too small there is liable to be an
error: nmax = 1
is silently ignored.
Long vectors are supported for the default method of
duplicated
, but may only be usable if nmax
is supplied.
Value

duplicated():
For a vector input, a logical vector of the same length as
x. For a data frame, a logical vector with one element for
each row. For a matrix or array, and when MARGIN = 0, a
logical array with the same dimensions and dimnames.anyDuplicated(): an integer or real vector of length one with
value the 1based index of the first duplicate if any, otherwise
0.
Warning
Using this for lists is potentially slow, especially if the elements
are not atomic vectors (see vector
) or differ only
in their attributes. In the worst case it is $O(n^2)$.
References
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
See Also
Examples
library(base)
x < c(9:20, 1:5, 3:7, 0:8)
## extract unique elements
(xu < x[!duplicated(x)])
## similar, same elements but different order:
(xu2 < x[!duplicated(x, fromLast = TRUE)])
## xu == unique(x) but unique(x) is more efficient
stopifnot(identical(xu, unique(x)),
identical(xu2, unique(x, fromLast = TRUE)))
duplicated(iris)[140:143]
duplicated(iris3, MARGIN = c(1, 3))
anyDuplicated(iris) ## 143
anyDuplicated(x)
anyDuplicated(x, fromLast = TRUE)
Community examples
#take some data data < mtcars[, c(1:3)] row.names(data) < NULL #add three new rows equal to the first three rows of data new.rows < data.frame(mpg=c(21.0, 21.0, 22.8), cyl=c(6, 6, 4), disp=c(160, 160, 93)) new.data < rbind(data, new.rows) #check for duplicated rows duplicated(new.data) #select the duplicated rows new.data[duplicated(new.data),] #remove the duplicated rows new.data[!duplicated(new.data),]