plyr (version 1.8.4)

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


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


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



list to be processed


function to apply to each piece


other arguments passed on to .fun


name of the progress bar to use, see create_progress_bar


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


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


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.


list of results


This function splits lists by elements.


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.


Hadley Wickham (2011). The Split-Apply-Combine Strategy for Data Analysis. Journal of Statistical Software, 40(1), 1-29.

See Also

Other list input: l_ply, laply, ldply

Other list output: alply, dlply, mlply


Run this code
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)
# }

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