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laply.Rd
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laply.Rd
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\name{laply}
\alias{laply}
\title{Split list, apply function, and return results in an array.}
\usage{
laply(.data, .fun = NULL, ..., .progress = "none",
.drop = TRUE, .parallel = FALSE)
}
\arguments{
\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
\code{\link{create_progress_bar}}}
\item{.parallel}{if \code{TRUE}, apply function in
parallel, using parallel backend provided by foreach}
\item{.data}{list to be processed}
\item{.drop}{should extra dimensions of length 1 in the
output be dropped, simplifying the output. Defaults to
\code{TRUE}}
}
\value{
if results are atomic with same type and dimensionality,
a vector, matrix or array; otherwise, a list-array (a
list with dimensions)
}
\description{
For each element of a list, apply function then combine
results into an array.
}
\details{
\code{laply} is similar in spirit to \code{\link{sapply}}
except that it will always return an array, and the
output is transposed with respect \code{sapply} - each
element of the list corresponds to a column, not a row.
}
\section{Input}{
This function splits lists by elements.
}
\section{Output}{
If there are no results, then this function will return a
vector of length 0 (\code{vector()}).
}
\examples{
laply(baseball, is.factor)
# cf
ldply(baseball, is.factor)
colwise(is.factor)(baseball)
laply(seq_len(10), identity)
laply(seq_len(10), rep, times = 4)
laply(seq_len(10), matrix, nrow = 2, ncol = 2)
}
\references{
Hadley Wickham (2011). The Split-Apply-Combine Strategy
for Data Analysis. Journal of Statistical Software,
40(1), 1-29. \url{http://www.jstatsoft.org/v40/i01/}.
}
\seealso{
Other array output: \code{\link{aaply}},
\code{\link{daply}}, \code{\link{maply}}
Other list input: \code{\link{l_ply}},
\code{\link{ldply}}, \code{\link{llply}}
}
\keyword{manip}