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(.))
.
duplicated(x, incomparables = FALSE, …)# S3 method for default
duplicated(x, incomparables = FALSE,
fromLast = FALSE, nmax = NA, …)
# S3 method for array
duplicated(x, incomparables = FALSE, MARGIN = 1,
fromLast = FALSE, …)
anyDuplicated(x, incomparables = FALSE, …)
# S3 method for default
anyDuplicated(x, incomparables = FALSE,
fromLast = FALSE, …)
# S3 method for array
anyDuplicated(x, incomparables = FALSE,
MARGIN = 1, fromLast = FALSE, …)
a vector or a data frame or an array or NULL
.
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
.
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
.
the maximum number of unique items expected (greater than one).
arguments for particular methods.
the array margin to be held fixed: see
apply
, and note that MARGIN = 0
may be useful.
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
.
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 \(O(n^2)\).
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 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 ("NA"
) are regarded as equal, numeric and
complex ones differing from NaN
; character strings will be compared in a
“common encoding”; for details, see match
(and
unique
) which use the same concept.
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.
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.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
# NOT RUN {
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
# }
# NOT RUN {
anyDuplicated(x)
anyDuplicated(x, fromLast = TRUE)
# }
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