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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/arrange.R
\name{step_arrange}
\alias{step_arrange}
\title{Sort rows using dplyr}
\usage{
step_arrange(
recipe,
...,
role = NA,
trained = FALSE,
inputs = NULL,
skip = FALSE,
id = rand_id("arrange")
)
}
\arguments{
\item{recipe}{A recipe object. The step will be added to the
sequence of operations for this recipe.}
\item{...}{Comma separated list of unquoted variable names.
Use `desc()`` to sort a variable in descending order. See
\code{\link[dplyr:arrange]{dplyr::arrange()}} for more details.}
\item{role}{Not used by this step since no new variables are
created.}
\item{trained}{A logical to indicate if the quantities for
preprocessing have been estimated.}
\item{inputs}{Quosure of values given by \code{...}.}
\item{skip}{A logical. Should the step be skipped when the
recipe is baked by \code{\link[=bake]{bake()}}? While all operations are baked
when \code{\link[=prep]{prep()}} is run, some operations may not be able to be
conducted on new data (e.g. processing the outcome variable(s)).
Care should be taken when using \code{skip = TRUE} as it may affect
the computations for subsequent operations.}
\item{id}{A character string that is unique to this step to identify it.}
}
\value{
An updated version of \code{recipe} with the new step added to the
sequence of any existing operations.
}
\description{
\code{step_arrange} creates a \emph{specification} of a recipe step
that will sort rows using \code{\link[dplyr:arrange]{dplyr::arrange()}}.
}
\details{
When an object in the user's global environment is
referenced in the expression defining the new variable(s),
it is a good idea to use quasiquotation (e.g. \verb{!!!})
to embed the value of the object in the expression (to
be portable between sessions). See the examples.
}
\section{Tidying}{
When you \code{\link[=tidy.recipe]{tidy()}} this step, a tibble with column
\code{terms} which contains the sorting variable(s) or expression(s) is
returned. The expressions are text representations and are not
parsable.
}
\section{Case weights}{
The underlying operation does not allow for case weights.
}
\examples{
rec <- recipe(~., data = iris) \%>\%
step_arrange(desc(Sepal.Length), 1 / Petal.Length)
prepped <- prep(rec, training = iris \%>\% slice(1:75))
tidy(prepped, number = 1)
library(dplyr)
dplyr_train <-
iris \%>\%
as_tibble() \%>\%
slice(1:75) \%>\%
dplyr::arrange(desc(Sepal.Length), 1 / Petal.Length)
rec_train <- bake(prepped, new_data = NULL)
all.equal(dplyr_train, rec_train)
dplyr_test <-
iris \%>\%
as_tibble() \%>\%
slice(76:150) \%>\%
dplyr::arrange(desc(Sepal.Length), 1 / Petal.Length)
rec_test <- bake(prepped, iris \%>\% slice(76:150))
all.equal(dplyr_test, rec_test)
# When you have variables/expressions, you can create a
# list of symbols with `rlang::syms()`` and splice them in
# the call with `!!!`. See https://tidyeval.tidyverse.org
sort_vars <- c("Sepal.Length", "Petal.Length")
qq_rec <-
recipe(~., data = iris) \%>\%
# Embed the `values` object in the call using !!!
step_arrange(!!!syms(sort_vars)) \%>\%
prep(training = iris)
tidy(qq_rec, number = 1)
}
\seealso{
Other row operation steps:
\code{\link{step_filter}()},
\code{\link{step_impute_roll}()},
\code{\link{step_lag}()},
\code{\link{step_naomit}()},
\code{\link{step_sample}()},
\code{\link{step_shuffle}()},
\code{\link{step_slice}()}
Other dplyr steps:
\code{\link{step_filter}()},
\code{\link{step_mutate_at}()},
\code{\link{step_mutate}()},
\code{\link{step_rename_at}()},
\code{\link{step_rename}()},
\code{\link{step_sample}()},
\code{\link{step_select}()},
\code{\link{step_slice}()}
}
\concept{dplyr steps}
\concept{row operation steps}
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