tapply {base} | R Documentation |
Apply a function to each cell of a ragged array, i.e., for to each (non-empty) group of values given by a unique combination of the levels of certain factors.
tapply(X, INDEX, FUN = NULL, simplify = TRUE, ...)
X |
an atomic object, typically a vector. |
INDEX |
list of factors, each of same length as X . |
FUN |
the function to be applied. In the case of functions like
+ , %*% , etc., the function name must be quoted. If
FUN is NULL , tapply returns a vector which can be used
to subscript the multi-way array tapply normally produces. |
simplify |
If FALSE , tapply always returns an array
of mode "list" . If TRUE (the default), then if
FUN always returns a scalar, tapply returns an array
with the mode of the scalar. |
... |
optional arguments to FUN . |
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 cell (e.g., functions mean
or var
) and
when simplify
is TRUE
, tapply
returns a multi-way
array containing the values. 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 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.
the convenience function aggregate
(using tapply
);
apply
,
lapply
with its version
sapply
.
groups <- as.factor(rbinom(32, n = 5, p = .4)) tapply(groups, groups, length) #- is almost the same as table(groups) data(warpbreaks) ## contingency table from data.frame : array with named dimnames tapply(warpbreaks$breaks, warpbreaks[,-1], sum) tapply(warpbreaks$breaks, warpbreaks[,3,drop=F], sum) n <- 17; fac <- factor(rep(1:3, len = n), levels = 1:5) table(fac) tapply(1:n, fac, sum) tapply(1:n, fac, sum, simplify = FALSE) tapply(1:n, fac, range) tapply(1:n, fac, quantile) ind <- list(c(1, 2, 2), c("A", "A", "B")) table(ind) tapply(1:3, ind) #-> the split vector tapply(1:3, ind, sum)