`unique`

returns a vector, data frame or array like `x`

but with duplicate elements/rows removed.`unique(x, incomparables = FALSE, …)`# S3 method for default
unique(x, incomparables = FALSE, fromLast = FALSE,
nmax = NA, …)

# S3 method for matrix
unique(x, incomparables = FALSE, MARGIN = 1,
fromLast = FALSE, …)

# S3 method for array
unique(x, incomparables = FALSE, MARGIN = 1,
fromLast = FALSE, …)

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

nmax

the maximum number of unique items expected (greater than one).
See

`duplicated`

.…

arguments for particular methods.

MARGIN

the array margin to be held fixed: a single integer.

`x`

, but with only
one copy of each duplicated element. No attributes are copied (so
the result has no names). For a data frame, a data frame is returned with the same columns but
possibly fewer rows (and with row names from the first occurrences of
the unique rows). A matrix or array is subsetted by `[, drop = FALSE]`

, so
dimensions and dimnames are copied appropriately, and the result
always has the same number of dimensions as `x`

.`vector`

) or differ only
in their attributes. In the worst case it is \(O(n^2)\).`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
`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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