ldply {plyr} | R Documentation |
Split list, apply function, and return results in a data frame.
Description
For each element of a list, apply function then combine results into a data frame.
Usage
ldply(
.data,
.fun = NULL,
...,
.progress = "none",
.inform = FALSE,
.parallel = FALSE,
.paropts = NULL,
.id = NA
)
Arguments
.data |
list to be processed |
.fun |
function to apply to each piece |
... |
other arguments passed on to |
.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 of the index column (used if |
Value
A data frame, as described in the output section.
Input
This function splits lists by elements.
Output
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()
).
References
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/.
See Also
Other list input:
l_ply()
,
laply()
,
llply()
Other data frame output:
adply()
,
ddply()
,
mdply()