adply {plyr} | R Documentation |
For each slice of an array, apply function then combine results into a data frame.
adply(.data, .margins, .fun = NULL, ..., .expand = TRUE, .progress = "none", .inform = FALSE, .parallel = FALSE, .paropts = NULL)
.fun |
function to apply to each piece |
... |
other arguments passed on to |
.progress |
name of the progress bar to use, see
|
.parallel |
if |
.paropts |
a list of additional options passed into
the |
.inform |
produce informative error messages? This is turned off by by default because it substantially slows processing speed, but is very useful for debugging |
.data |
matrix, array or data frame to be processed |
.margins |
a vector giving the subscripts to split
up |
.expand |
if |
A data frame, as described in the output section.
This function splits matrices, arrays and data frames by dimensions
The most unambiguous behaviour is achieved when
.fun
returns a data frame - in that case pieces
will be combined with rbind.fill
. If
.fun
returns an atomic vector of fixed length, it
will be rbind
ed together and converted to a data
frame. Any other values will result in an error.
If there are no results, then this function will return a
data frame with zero rows and columns
(data.frame()
).
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/.
Other array input: a_ply
,
aaply
, alply
Other data frame output: ddply
,
ldply
, mdply