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

dlply {plyr}

R Documentation

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/.

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)

[Package plyr version 1.7.1 Index]