unique                 package:base                 R Documentation

_E_x_t_r_a_c_t _U_n_i_q_u_e _E_l_e_m_e_n_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     'unique' returns a vector, data frame or array like 'x' but with
     duplicate elements/rows removed.

_U_s_a_g_e:

     unique(x, incomparables = FALSE, ...)

     ## Default S3 method:
     unique(x, incomparables = FALSE, fromLast = FALSE, ...)

     ## S3 method for class 'matrix':
     unique(x, incomparables = FALSE, MARGIN = 1,
            fromLast = FALSE, ...)

     ## S3 method for class 'array':
     unique(x, incomparables = FALSE, MARGIN = 1,
            fromLast = FALSE, ...)

_A_r_g_u_m_e_n_t_s:

       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 last, i.e., the last (or rightmost) of identical elements
          will be kept.  This only matters for 'names' or 'dimnames'.

     ...: arguments for particular methods.

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

_D_e_t_a_i_l_s:

     This is a generic function with methods for vectors, data frames
     and arrays (including matrices).

     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 identical to any previous element and not just if
     it is the same as the immediately previous one. (For the latter,
     see 'rle').

     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.

_V_a_l_u_e:

     For a vector, an object of the same type of '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'.

_W_a_r_n_i_n_g:

     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).

_R_e_f_e_r_e_n_c_e_s:

     Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) _The New S
     Language_. Wadsworth & Brooks/Cole.

_S_e_e _A_l_s_o:

     'duplicated' which gives the indices of duplicated elements.

     'rle' which is the equivalent of the Unix 'uniq -c' command.

_E_x_a_m_p_l_e_s:

     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)

