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, …)
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.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
  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 ("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
  duplicated) 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. 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!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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