l_ply: Split list, apply function, and discard results.

Description Usage Arguments Value Input Output References See Also Examples

View source: R/l_ply.r


For each element of a list, apply function and discard results


l_ply(.data, .fun = NULL, ..., .progress = "none", .inform = FALSE,
  .print = 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


automatically print each result? (default: FALSE)


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.




This function splits lists by elements.


All output is discarded. This is useful for functions that you are calling purely for their side effects like displaying plots or saving output.


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: laply, ldply, llply

Other no output: a_ply, d_ply, m_ply



plyr documentation built on May 19, 2017, 10:09 a.m.

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