unique
returns a vector, data frame or array like x
but with duplicate elements/rows removed.
unique(x, incomparables = FALSE, ...)
"unique"(x, incomparables = FALSE, fromLast = FALSE, nmax = NA, ...)
"unique"(x, incomparables = FALSE, MARGIN = 1, fromLast = FALSE, ...)
"unique"(x, incomparables = FALSE, MARGIN = 1, fromLast = FALSE, ...)
NULL
.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
.duplicated
.vector
) or differ only
in their attributes. In the worst case it is $O(n^2)$. The array method calculates for each element of the dimension
specified by MARGIN
if the remaining dimensions are identical
to those for an earlier element (in row-major order). This would most
commonly be used for matrices to find unique rows (the default) or columns
(with MARGIN = 2
).
Note that unlike the Unix command uniq
this omits
duplicated and not just repeated elements/rows. That
is, an element is omitted if it is equal to any previous element and
not just if it is equal the immediately previous one. (For the
latter, see rle
).
Missing values are regarded as equal, but NaN
is not equal to
NA_real_
. Character strings are regarded as equal if they are
in different encodings but would agree when translated to UTF-8.
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
).
duplicated
which gives the indices of duplicated
elements. rle
which is the equivalent of the Unix uniq -c
command.
x <- c(3:5, 11:8, 8 + 0:5)
(ux <- unique(x))
(u2 <- unique(x, fromLast = TRUE)) # different order
stopifnot(identical(sort(ux), sort(u2)))
length(unique(sample(100, 100, replace = TRUE)))
## approximately 100(1 - 1/e) = 63.21
unique(iris)
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