split divides the data in the vector
x into the groups
f. The replacement forms replace values
corresponding to such a division.
unsplit reverses the effect of
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vector or data frame containing values to be divided into groups.
a ‘factor’ in the sense that
logical indicating if levels that do not occur should be dropped
a list of vectors or data frames compatible with a
further potential arguments passed to methods.
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
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
The default method calls
interaction. If the levels of
the factors contain . they may not be split as expected, so
the method has argument
sep which is use to join the levels.
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
drop = TRUE, dropping unused levels).
The replacement forms return their right hand side.
returns a vector or data frame for which
split(x, f) equals
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.
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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)