tapply {base}  R Documentation 
Apply a function to each cell of a ragged array, that is to each (nonempty) 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
multiway 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 1dimensional.
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)))))