R: Apply a Function Over a Ragged Array

tapply {base}

R Documentation

Apply a Function Over a Ragged Array

Description

Apply a function to each cell of a ragged array, that is to each (non-empty) group of values or data rows given by a unique combination of the levels of certain factors.

Usage

tapply(X, INDEX, FUN = NULL, ..., default = NA, simplify = TRUE)

Arguments

`X`	an R object for which a `split` method exists. Typically vector-like, allowing subsetting with `[`, or a data frame.
`INDEX`	a `list` of one or more `factor`s, each of same length as `X`. The elements are coerced to factors by `as.factor`. Can also be a formula, which is useful if `X` is a data frame; see the `f` argument in `split` for interpretation.
`FUN`	a function (or name of a function) to be applied, or `NULL`. In the case of functions like `+`, `%*%`, etc., the function name must be backquoted or quoted. If `FUN` is `NULL`, `tapply` returns a vector which can be used to subscript the multi-way array `tapply` normally produces.
`...`	optional arguments to `FUN`: the Note section.
`default`	(only in the case of simplification to an array) the value with which the array is initialized as `array(default, dim = ..)`. Before R 3.4.0, this was hard coded to `array()`'s default `NA`. If it is `NA` (the default), the missing value of the answer type, e.g. `NA_real_`, is chosen (`as.raw(0)` for `"raw"`). In a numerical case, it may be set, e.g., to `FUN(integer(0))`, e.g., in the case of `FUN = sum` to `0` or `0L`.
`simplify`	logical; if `FALSE`, `tapply` always returns an array of mode `"list"`; in other words, a `list` with a `dim` attribute. If `TRUE` (the default), then if `FUN` always returns a scalar, `tapply` returns an array with the mode of the scalar.

Details

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.

Value

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.

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.

The array2DF function can be used to convert the array returned by tapply into a data frame, which may be more convenient for further analysis.

Note

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.

References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

Examples

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)))))

[Package base version 4.4.1 Index]