ldply {plyr} | R Documentation |
For each element of a list, apply function then combine results into a data frame.
ldply(.data, .fun = NULL, ..., .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 |
list to be processed |
A data frame, as described in the output section.
This function splits lists by elements.
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 data frame output: adply
,
ddply
, mdply
Other list input: l_ply
,
laply
, llply