plyr (version 1.5.2)

llply: Split list, apply function, and return results in a list.

Description

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

Usage

llply(.data, .fun, ..., .progress="none", .inform=FALSE,
    .parallel=FALSE)

Arguments

.data

list to be processed

.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

.inform

produce informative error messages? This is turned off by by default because it substantially slows processing speed, but is very useful for debugging

.parallel

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

Value

• list of results

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 lists by elements and combines the result into a list. If there are no results, then this function will return a list of length 0 (list()).

llply is equivalent to lapply except that it will preserve labels and can display a progress bar.

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

llply(llply(mtcars, round), table)
llply(baseball, summary)
# Examples from ?lapply
x <- list(a = 1:10, beta = exp(-3:3), logic = c(TRUE,FALSE,FALSE,TRUE))

llply(x, mean)
llply(x, quantile, probs = 1:3/4)