split {base} | R Documentation |

`split`

divides the data in the vector `x`

into the groups
defined by `f`

. The replacement forms replace values
corresponding to such a division. `unsplit`

reverses the effect of
`split`

.

split(x, f, drop = FALSE, ...) split(x, f, drop = FALSE, ...) <- value unsplit(value, f, drop = FALSE)

`x` |
vector or data frame containing values to be divided into groups. |

`f` |
a ‘factor’ in the sense that |

`drop` |
logical indicating if levels that do not occur should be dropped
(if |

`value` |
a list of vectors or data frames compatible with a
splitting of |

`...` |
further potential arguments passed to methods. |

`split`

and `split<-`

are generic functions with default and
`data.frame`

methods.
The data frame
method can also be used to split a matrix into a list of matrices,
and the replacement form likewise, provided they are invoked
explicitly.

`unsplit`

works with lists of vectors or data frames (assumed to
have compatible structure, as if created by `split`

). It puts
elements or rows back in the positions given by `f`

. In the data
frame case, row names are obtained by unsplitting the row name
vectors from the elements of `value`

.

`f`

is recycled as necessary and if the length of `x`

is not
a multiple of the length of `f`

a warning is printed.

Any missing values in `f`

are dropped together with the
corresponding values of `x`

.

The value returned from `split`

is a list of vectors containing
the values for the groups. The components of the list are named by
the levels of `f`

(after converting to a factor, or if already a
factor and `drop = TRUE`

, dropping unused levels).

The replacement forms return their right hand side. `unsplit`

returns a vector or data frame for which `split(x, f)`

equals
`value`

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

`cut`

to categorize numeric values.

`strsplit`

to split strings.

require(stats); require(graphics) n <- 10; nn <- 100 g <- factor(round(n * runif(n * nn))) x <- rnorm(n * nn) + sqrt(as.numeric(g)) xg <- split(x, g) boxplot(xg, col = "lavender", notch = TRUE, varwidth = TRUE) sapply(xg, length) sapply(xg, mean) ### Calculate 'z-scores' by group (standardize to mean zero, variance one) z <- unsplit(lapply(split(x, g), scale), g) # or zz <- x split(zz, g) <- lapply(split(x, g), scale) # and check that the within-group std dev is indeed one tapply(z, g, sd) tapply(zz, g, sd) ### data frame variation ## Notice that assignment form is not used since a variable is being added g <- airquality$Month l <- split(airquality, g) l <- lapply(l, transform, Oz.Z = scale(Ozone)) aq2 <- unsplit(l, g) head(aq2) with(aq2, tapply(Oz.Z, Month, sd, na.rm = TRUE)) ### Split a matrix into a list by columns ma <- cbind(x = 1:10, y = (-4:5)^2) split(ma, col(ma)) split(1:10, 1:2)

[Package *base* version 2.15.3 Index]