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.
an atomic object, typically a vector.
the function to be applied, or
optional arguments to
(only in the case of simplification to an array) the
value with which the array is initialized as
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.
FUN is present,
FUN for each
cell that has any data in it. If
FUN returns a single atomic
value for each such cell (e.g., functions
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
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.
FUN does not return a single atomic value,
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
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
Optional arguments to
FUN supplied by the
are not divided into cells. It is therefore inappropriate for
FUN to expect additional arguments with the same length as
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
the convenience functions
lapply with its versions
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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)))))
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