plyr: m_ply – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

m_ply

Call function with arguments in array or data frame, discarding results.

Description

Call a multi-argument function with values taken from columns of an data frame or array, and discard results into a list.

Usage

m_ply(
  .data,
  .fun = NULL,
  ...,
  .expand = TRUE,
  .progress = "none",
  .inform = FALSE,
  .print = FALSE,
  .parallel = FALSE,
  .paropts = NULL
)

Arguments

`.data`	matrix or data frame to use as source of arguments
`.fun`	function to apply to each piece
`...`	other arguments passed on to `.fun`
`.expand`	should output be 1d (expand = FALSE), with an element for each row; or nd (expand = TRUE), with a dimension for each variable.
`.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
`.print`	automatically print each result? (default: `FALSE`)
`.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

The m*ply functions are the plyr version of mapply, specialised according to the type of output they produce. These functions are just a convenient wrapper around a*ply with margins = 1 and .fun wrapped in splat.

Value

Nothing

Input

Call a multi-argument function with values taken from columns of an data frame or array

Output

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

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/.