plyr (version 1.0.1)

dlply: Split data frame, apply function, and return results in a list.

Description

Split data frame, apply function, and return results in a list. For each subset of a data frame, apply function then combine results into a list

Usage

dlply(.data, .variables, .fun, ..., .progress="none", .drop=TRUE)

Arguments

.data

data frame to be processed

.variables

variables to split data frame by, as quoted variables, a formula or character vector

.fun

function to apply to each piece

...

other arguments passed on to .fun

.progress

name of the progress bar to use, see create_progress_bar

.drop

should combinations of variables that do not appear in the data be preserved (FALSE) or dropped (TRUE, default)

Value

• if results are atomic with same type and dimensionality, a vector, matrix or array; otherwise, a list-array (a list with dimensions)

Details

All plyr functions use the same split-apply-combine strategy: they split the input into simpler pieces, apply .fun to each piece, and then combine the pieces into a single data structure. This function splits data frames by variables and combines the result into a list. If there are no results, then this function will return a list of length 0 (list()).

dlply is similar to by except that the results are returned in a different format.

Examples

linmod <- function(df) lm(rbi ~ year, data = transform(df, year = year - min(year)))
models <- dlply(baseball, .(id), linmod)
models[[1]]

coef <- ldply(models, coef)
with(coef, plot(`(Intercept)`, year))
qual <- laply(models, function(mod) summary(mod)$r.squared)
hist(qual)