% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gg_partial.R
\name{gg_partial}
\alias{gg_partial}
\title{Split partial dependence data into continuous or categorical datasets}
\usage{
gg_partial(part_dta, nvars = NULL, cat_limit = 10, model = NULL)
}
\arguments{
\item{part_dta}{partial plot data from \code{rfsrc::plot.variable}}

\item{nvars}{how many of the partial plot variables to calculate}

\item{cat_limit}{Categorical features are built when there are fewer than
\code{cat_limit} unique feature values.}

\item{model}{a label name applied to all features. Useful when combining
multiple partial plot objects in figures.}
}
\value{
A named list with two elements:
  \describe{
    \item{continuous}{data.frame with columns \code{x}, \code{yhat},
      \code{name} (and optionally \code{model}) for continuous variables}
    \item{categorical}{data.frame with the same columns but with \code{x}
      as a factor, for low-cardinality / categorical variables}
  }
}
\description{
Takes the list returned by \code{rfsrc::plot.variable(partial = TRUE)} and
separates the variables into two data frames: one for continuous predictors
and one for categorical (factor-like) predictors.  The split is controlled
by \code{cat_limit}: variables with more unique x-values than this threshold
are treated as continuous; all others are categorical.
}
\examples{
## Build a small regression forest on the airquality dataset
set.seed(42)
airq <- na.omit(airquality)
rf <- rfsrc(Ozone ~ ., data = airq, ntree = 50)

## Compute partial dependence via plot.variable (show.plots = FALSE to
## suppress the base-graphics output — we only want the data)
pv <- randomForestSRC::plot.variable(rf, partial = TRUE,
                                      show.plots = FALSE)

## Split into continuous and categorical data frames
result <- gg_partial(pv)
head(result$continuous)

## Label this model for later comparison with a second forest
result_labelled <- gg_partial(pv, model = "airq_model")
unique(result_labelled$continuous$model)

}
\seealso{
\code{\link{gg_partial_rfsrc}} \code{\link{gg_partialpro}}
}
