duplicated               package:base               R Documentation

_D_e_t_e_r_m_i_n_e _D_u_p_l_i_c_a_t_e _E_l_e_m_e_n_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     Determines which elements of a vector of data frame are duplicates
     of elements with smaller subscripts, and returns a logical vector
     indicating which elements (rows) are duplicates.

_U_s_a_g_e:

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

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

_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. Currently,
          'FALSE' is the only possible value, meaning that all values
          can be compared.

     ...: arguments for particular methods.

  MARGIN: the array margin to be held fixed: see 'apply'.

_D_e_t_a_i_l_s:

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

     The data frame method works by pasting together a character
     representation of the rows separated by '\r', so may be imperfect
     if the data frame has characters with embedded carriage returns or
     columns which do not reliably map to characters.

     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 element (in row-major order).  This would
     most commonly be used to find duplicated rows (the default) or
     columns (with 'MARGIN = 2').

_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:

     'unique'.

_E_x_a_m_p_l_e_s:

     x <- c(9:20, 1:5, 3:7, 0:8)
     ## extract unique elements
     (xu <- x[!duplicated(x)])
     ## xu == unique(x) but unique(x) is more efficient

     duplicated(iris)[140:143]

     duplicated(iris3, MARGIN = c(1, 3))

