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\title{Split data frame, apply function, and discard results.}
d_ply(.data, .variables, .fun = NULL, ...,
.progress = "none", .print = FALSE)
\item{.data}{data frame to be processed}
\item{.variables}{variables to split data frame by, as
quoted variables, a formula or character vector}
\item{.fun}{function to apply to each piece}
\item{...}{other arguments passed on to \code{.fun}}
\item{.progress}{name of the progress bar to use, see
\item{.print}{automatically print each result? (default:
For each subset of a data frame, apply function and
discard results
All plyr functions use the same split-apply-combine
strategy: they split the input into simpler pieces, apply
\code{.fun} to each piece, and then combine the pieces
into a single data structure. This function splits data
frames by variable and discards the output. This is
useful for functions that you are calling purely for
their side effects like display plots and saving output.
Hadley Wickham (2011). The Split-Apply-Combine Strategy
for Data Analysis. Journal of Statistical Software,
40(1), 1-29. \url{}.
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