# duplicated

0th

Percentile

##### 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(.)).

Keywords
manip, logic
##### 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 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.
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 that MARGIN = 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 sub-array specified by MARGIN if the remaining dimensions are identical to those for an earlier (or later, when fromLast = TRUE) element (in row-major 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 floating-point 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 1-based 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.

unique.

##### Aliases
• duplicated
• duplicated.default
• duplicated.data.frame
• duplicated.matrix
• duplicated.array
• anyDuplicated
• anyDuplicated.default
• anyDuplicated.array
• anyDuplicated.matrix
• anyDuplicated.data.frame
##### 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) 
Documentation reproduced from package base, version 3.3, License: Part of R @VERSION@

### Community examples

fabionatalini@gmail.com at Jan 12, 2018 base v3.4.3

#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),]