% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/count.R
\name{step_count}
\alias{step_count}
\title{Create Counts of Patterns using Regular Expressions}
\usage{
step_count(
  recipe,
  ...,
  role = "predictor",
  trained = FALSE,
  pattern = ".",
  normalize = FALSE,
  options = list(),
  result = make.names(pattern),
  input = NULL,
  skip = FALSE,
  id = rand_id("count")
)
}
\arguments{
\item{recipe}{A recipe object. The step will be added to the
sequence of operations for this recipe.}

\item{...}{A single selector function to choose which variable
will be searched for the regex pattern. The selector should
resolve to a single variable. See \code{\link[=selections]{selections()}} for more details.}

\item{role}{For model terms created by this step, what analysis role should
they be assigned? By default, the new columns created by this step from
the original variables will be used as \emph{predictors} in a model.}

\item{trained}{A logical to indicate if the quantities for
preprocessing have been estimated.}

\item{pattern}{A character string containing a regular
expression (or character string for \code{fixed = TRUE}) to be
matched in the given character vector. Coerced by
\code{as.character} to a character string if possible.}

\item{normalize}{A logical; should the integer counts be
divided by the total number of characters in the string?.}

\item{options}{A list of options to \code{\link[=gregexpr]{gregexpr()}} that
should not include \code{x} or \code{pattern}.}

\item{result}{A single character value for the name of the new
variable. It should be a valid column name.}

\item{input}{A single character value for the name of the
variable being searched. This is \code{NULL} until computed by
\code{\link[=prep]{prep()}}.}

\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_count} creates a \emph{specification} of a recipe
step that will create a variable that counts instances of a
regular expression pattern in text.
}
\section{Tidying}{
When you \code{\link[=tidy.recipe]{tidy()}} this step, a tibble with columns
\code{terms} (the selectors or variables selected) and \code{result} (the
new column name) is returned.
}

\section{Case weights}{


The underlying operation does not allow for case weights.
}

\examples{
\dontshow{if (rlang::is_installed("modeldata")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
data(covers, package = "modeldata")

rec <- recipe(~description, covers) \%>\%
  step_count(description, pattern = "(rock|stony)", result = "rocks") \%>\%
  step_count(description, pattern = "famil", normalize = TRUE)

rec2 <- prep(rec, training = covers)
rec2

count_values <- bake(rec2, new_data = covers)
count_values

tidy(rec, number = 1)
tidy(rec2, number = 1)
\dontshow{\}) # examplesIf}
}
\seealso{
Other dummy variable and encoding steps: 
\code{\link{step_bin2factor}()},
\code{\link{step_date}()},
\code{\link{step_dummy_extract}()},
\code{\link{step_dummy_multi_choice}()},
\code{\link{step_dummy}()},
\code{\link{step_factor2string}()},
\code{\link{step_holiday}()},
\code{\link{step_indicate_na}()},
\code{\link{step_integer}()},
\code{\link{step_novel}()},
\code{\link{step_num2factor}()},
\code{\link{step_ordinalscore}()},
\code{\link{step_other}()},
\code{\link{step_regex}()},
\code{\link{step_relevel}()},
\code{\link{step_string2factor}()},
\code{\link{step_time}()},
\code{\link{step_unknown}()},
\code{\link{step_unorder}()}
}
\concept{dummy variable and encoding steps}
