adply | 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,
.id = NA
)
.data |
matrix, array or data frame to be processed |
.margins |
a vector giving the subscripts to split up |
.fun |
function to apply to each piece |
... |
other arguments passed on to |
.expand |
if |
.progress |
name of the progress bar to use, see
|
.inform |
produce informative error messages? This is turned off by default because it substantially slows processing speed, but is very useful for debugging |
.parallel |
if |
.paropts |
a list of additional options passed into
the |
.id |
name(s) of the index column(s).
Pass |
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. https://www.jstatsoft.org/v40/i01/.
Other array input:
a_ply()
,
aaply()
,
alply()
Other data frame output:
ddply()
,
ldply()
,
mdply()
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