d_ply: 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 as.quoted
variables, a formula or character vector .fun
function to apply to each piece
...
other arguments passed on to .fun
.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: FALSE
)
.parallel
if TRUE
, apply function in parallel, using parallel
backend provided by foreach
.paropts
a list of additional options passed into
the foreach
function when parallel computation
is enabled. This is important if (for example) your code relies on
external data or packages: use the .e
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.
http://www.jstatsoft.org/v40/i01/.