plyr (version 1.8.3)

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 .e

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()).

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.

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 array output: aaply; daply; laply

Other multiple arguments input: m_ply; mdply; mlply

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)