plyr (version 1.6)

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

Description

For each subset of a data frame, apply function then combine results into a list. dlply is similar to by except that the results are returned in a different format.

Usage

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

Arguments

.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

.data

data frame to be processed

.variables

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

.drop

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

.parallel

if TRUE, apply function in parallel, using parallel backend provided by foreach

Value

• list of results

Input

This function splits data frames by variables.

Output

If there are no results, then this function will return a list of length 0 (list()).

References

Hadley Wickham (2011). The Split-Apply-Combine Strategy for Data Analysis. Journal of Statistical Software, 40(1), 1-29. http://www.jstatsoft.org/v40/i01/.

See Also

Other data frame input: daply, ddply

Other list output: alply, llply

Examples

linmod <- function(df) {
lm(rbi ~ year, data = mutate(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)