llply

0th

Percentile

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

For each element of a list, apply function, keeping results as a list.

Keywords
manip
Usage
llply(.data, .fun = NULL, ..., .progress = "none", .inform = FALSE, .parallel = FALSE, .paropts = NULL)
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 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
.paropts
a list of additional options passed into the foreach function when parallel computation is enabled. This is important if (for example) your code relies on external data or packages: use the .export and .packages arguments to supply them so that all cluster nodes have the correct environment set up for computing.
Details

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

Value

list of results

Input

This function splits lists by elements.

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 list input: l_ply, laply, ldply

Other list output: alply, dlply, mlply

Aliases
  • llply
Examples
library(plyr) 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)
Documentation reproduced from package plyr, version 1.8.4, License: MIT + file LICENSE

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