order                  package:base                  R Documentation

_O_r_d_e_r_i_n_g _P_e_r_m_u_t_a_t_i_o_n

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

     'order' returns a permutation which rearranges its first argument
     into ascending or descending order, breaking ties by further
     arguments. 'sort.list' is the same, using only one argument.

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

     order(..., na.last = TRUE, decreasing = FALSE)

     sort.list(x, partial = NULL, na.last = TRUE, decreasing = FALSE,
               method = c("shell", "quick", "radix"))

_A_r_g_u_m_e_n_t_s:

     ...: a sequence of vectors, all of the same length.

       x: a vector.

 partial: vector of indices for partial sorting.

decreasing: logical. Should the sort order be increasing or decreasing?

 na.last: for controlling the treatment of 'NA's. If 'TRUE', missing
          values in the data are put last; if 'FALSE', they are put
          first; if 'NA', they are removed. 

  method: the method to be used: partial matches are allowed.

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

     In the case of ties in the first vector, values in the second are
     used to break the ties.  If the values are still tied, values in
     the later arguments are used to break the tie (see the first
     example). The sort used is _stable_ (except for 'method =
     "quick"'), so any unresolved ties will be left in their original
     ordering.

     The default method for 'sort.list' is a good compromise. Method
     '"quick"' is only supported for numeric 'x' with 'na.last=NA', and
     is not stable, but will be faster for long vectors. Method
     '"radix"' is only implemented for integer 'x' with a range of less
     than 100,000.  For such 'x' it is very fast (and stable), and
     hence is ideal for sorting factors.

     'partial' is supplied for compatibility with other implementations
     of S, but no other values are accepted and ordering is always
     complete.

_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:

     'sort' and 'rank'.

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

     (ii <- order(x <- c(1,1,3:1,1:4,3), y <- c(9,9:1), z <-c(2,1:9)))
     ## 6  5  2  1  7  4 10  8  3  9
     rbind(x,y,z)[,ii] # shows the reordering (ties via 2nd & 3rd arg)

     ## Suppose we wanted descending order on y. A simple solution is
     rbind(x,y,z)[, order(x, -y, z)]
     ## For character vectors we can make use of rank:
     cy <- as.character(y)
     rbind(x,y,z)[, order(x, -rank(y), z)]

     ## rearrange matched vectors so that the first is in ascending order
     x <- c(5:1, 6:8, 12:9)
     y <- (x - 5)^2
     o <- order(x)
     rbind(x[o], y[o])

     ## tests of na.last
     a <- c(4, 3, 2, NA, 1)
     b <- c(4, NA, 2, 7, 1)
     z <- cbind(a, b)
     (o <- order(a, b)); z[o, ]
     (o <- order(a, b, na.last = FALSE)); z[o, ]
     (o <- order(a, b, na.last = NA)); z[o, ]

     ## Not run: 
     ##  speed examples for long vectors: timings are immediately after gc()
     x <- factor(sample(letters, 1e6, replace=TRUE))
     system.time(o <- sort.list(x)) ## 4 secs
     stopifnot(!is.unsorted(x[o]))
     system.time(o <- sort.list(x, method="quick", na.last=NA)) # 0.4 sec
     stopifnot(!is.unsorted(x[o]))
     system.time(o <- sort.list(x, method="radix")) # 0.04 sec
     stopifnot(!is.unsorted(x[o]))
     xx <- sample(1:26, 1e7, replace=TRUE)
     system.time(o <- sort.list(xx, method="radix")) # 0.4 sec
     xx <- sample(1:100000, 1e7, replace=TRUE)
     system.time(o <- sort.list(xx, method="radix")) # 4 sec
     ## End(Not run)

