| tapply {base} | R Documentation |
Apply a function to each cell of a ragged array, that is to each (non-empty) group of values given by a unique combination of the levels of certain factors.
tapply(X, INDEX, FUN = NULL, ..., default = NA, simplify = TRUE)
X |
an atomic object, typically a vector. |
INDEX |
a |
FUN |
the function to be applied, or |
... |
optional arguments to |
default |
(only in the case of simplification to an array) the
value with which the array is initialized as
|
simplify |
logical; if |
If FUN is not NULL, it is passed to
match.fun, and hence it can be a function or a symbol or
character string naming a function.
When FUN is present, tapply calls FUN for each
cell that has any data in it. If FUN returns a single atomic
value for each such cell (e.g., functions mean or var)
and when simplify is TRUE, tapply returns a
multi-way array containing the values, and NA for the
empty cells. The array has the same number of dimensions as
INDEX has components; the number of levels in a dimension is
the number of levels (nlevels()) in the corresponding component
of INDEX. Note that if the return value has a class (e.g., an
object of class "Date") the class is discarded.
Note that contrary to S, simplify = TRUE always returns an
array, possibly 1-dimensional.
If FUN does not return a single atomic value, tapply
returns an array of mode list whose components are the
values of the individual calls to FUN, i.e., the result is a
list with a dim attribute.
When there is an array answer, its dimnames are named by
the names of INDEX and are based on the levels of the grouping
factors (possibly after coercion).
For a list result, the elements corresponding to empty cells are
NULL.
Optional arguments to FUN supplied by the ... argument
are not divided into cells. It is therefore inappropriate for
FUN to expect additional arguments with the same length as
X.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
the convenience functions by and
aggregate (using tapply);
apply,
lapply with its versions
sapply and mapply.
require(stats)
groups <- as.factor(rbinom(32, n = 5, prob = 0.4))
tapply(groups, groups, length) #- is almost the same as
table(groups)
## contingency table from data.frame : array with named dimnames
tapply(warpbreaks$breaks, warpbreaks[,-1], sum)
tapply(warpbreaks$breaks, warpbreaks[, 3, drop = FALSE], sum)
n <- 17; fac <- factor(rep_len(1:3, n), levels = 1:5)
table(fac)
tapply(1:n, fac, sum)
tapply(1:n, fac, sum, default = 0) # maybe more desirable
tapply(1:n, fac, sum, simplify = FALSE)
tapply(1:n, fac, range)
tapply(1:n, fac, quantile)
tapply(1:n, fac, length) ## NA's
tapply(1:n, fac, length, default = 0) # == table(fac)
## example of ... argument: find quarterly means
tapply(presidents, cycle(presidents), mean, na.rm = TRUE)
ind <- list(c(1, 2, 2), c("A", "A", "B"))
table(ind)
tapply(1:3, ind) #-> the split vector
tapply(1:3, ind, sum)
## Some assertions (not held by all patch propsals):
nq <- names(quantile(1:5))
stopifnot(
identical(tapply(1:3, ind), c(1L, 2L, 4L)),
identical(tapply(1:3, ind, sum),
matrix(c(1L, 2L, NA, 3L), 2, dimnames = list(c("1", "2"), c("A", "B")))),
identical(tapply(1:n, fac, quantile)[-1],
array(list(`2` = structure(c(2, 5.75, 9.5, 13.25, 17), .Names = nq),
`3` = structure(c(3, 6, 9, 12, 15), .Names = nq),
`4` = NULL, `5` = NULL), dim=4, dimnames=list(as.character(2:5)))))