# R: Ordering Permutation

order {base} | R Documentation

## Ordering Permutation

### Description

`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.
See the examples for how to use these functions to sort data frames, etc.

### Usage

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

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

### Arguments

`...` | a sequence of numeric, complex, character or logical vectors, all of the same length.
`x` | a vector.
`partial` | vector of indices for partial sorting. (Non-`NULL` values are not implemented.)
`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.

### Details

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.

Complex values are sorted first by the real part, then the imaginary part.

The sort order for character vectors will depend on the collating sequence of the locale in use: see `Comparison`.

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.

Note that these functions are only defined for vectors, so any class of the object supplied is ignored: this means factors are sorted on their internal codes and not their printed representation.

### Note

`sort.list` can get called by mistake as a method for `sort` with a list argument, and gives a suitable error message for list `x`.

### References

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

### See Also

`sort` and `rank`.

### Examples

    require(stats)

    (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(cy), z)]

    ## Sorting data frames:
    dd <- transform(data.frame(x,y,z),
                    z = factor(z, labels=LETTERS[9:1]))
    ## Either as above {for factor 'z' : using internal coding}:
    dd[ order(x, -y, z) ,]
    ## or along 1st column, ties along 2nd, ... *arbitrary* no.{columns}:
    dd[ do.call(order, dd) ,]

    set.seed(1)# reproducible example:
    d4 <- data.frame(x = round(   rnorm(100)), y = round(10*runif(100)),
                     z = round( 8*rnorm(100)), u = round(50*runif(100)))
    (d4s <- d4[ do.call(order, d4) ,])
    (i <- which(diff(d4s[,3]) == 0))# in 2 places, needed 3 cols to break ties:
    d4s[ rbind(i,i+1), ]

    ## 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:
    x <- factor(sample(letters, 1e6, replace=TRUE))
    system.time(o <- sort.list(x)) ## 1.2 secs
    stopifnot(!is.unsorted(x[o]))
    system.time(o <- sort.list(x, method="quick", na.last=NA)) # 0.15 sec
    stopifnot(!is.unsorted(x[o]))
    system.time(o <- sort.list(x, method="radix")) # 0.02 sec
    stopifnot(!is.unsorted(x[o]))
    xx <- sample(1:26, 1e7, replace=TRUE)
    system.time(o <- sort.list(xx, method="radix")) # 0.2 sec
    xx <- sample(1:100000, 1e7, replace=TRUE)
    system.time(o <- sort.list(xx, method="radix")) # 0.8 sec
    system.time(o <- sort.list(xx, method="quick", na.last=NA)) # 1.4 sec
    ## End(Not run)

[Package base version 2.6.0 Index]