plyr: maply – R documentation

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maply

Call function with arguments in array or data frame, returning an array.

Description

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

Usage

maply(
  .data,
  .fun = NULL,
  ...,
  .expand = TRUE,
  .progress = "none",
  .inform = FALSE,
  .drop = TRUE,
  .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
`.drop`	should extra dimensions of length 1 in the output be dropped, simplifying the output. Defaults to `TRUE`
`.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

if results are atomic with same type and dimensionality, a vector, matrix or array; otherwise, a list-array (a list with dimensions)

Input

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

Output

If there are no results, then this function will return a vector of length 0 (vector()).

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

maply(cbind(mean = 1:5, sd = 1:5), rnorm, n = 5)
maply(expand.grid(mean = 1:5, sd = 1:5), rnorm, n = 5)
maply(cbind(1:5, 1:5), rnorm, n = 5)

plyr

Tools for Splitting, Applying and Combining Data

v1.8.6

MIT + file LICENSE

Authors

Hadley Wickham [aut, cre]

Initial release