d_ply {plyr} | R Documentation |
Split data frame, apply function, and discard results.
Description
For each subset of a data frame, apply function and discard results.
To apply a function for each row, use a_ply
with
.margins
set to 1
.
Usage
d_ply(
.data,
.variables,
.fun = NULL,
...,
.progress = "none",
.inform = FALSE,
.drop = TRUE,
.print = FALSE,
.parallel = FALSE,
.paropts = NULL
)
Arguments
.data |
data frame to be processed |
.variables |
variables to split data frame by, as |
.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 |
.drop |
should combinations of variables that do not appear in the input data be preserved (FALSE) or dropped (TRUE, default) |
.print |
automatically print each result? (default: |
.parallel |
if |
.paropts |
a list of additional options passed into
the |
Value
Nothing
Input
This function splits data frames by variables.
Output
All output is discarded. This is useful for functions that you are calling purely for their side effects like displaying plots or saving output.
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 data frame input:
daply()
,
ddply()
,
dlply()
Other no output:
a_ply()
,
l_ply()
,
m_ply()