% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_group.R
\name{data_group}
\alias{data_group}
\alias{data_ungroup}
\title{Create a grouped data frame}
\usage{
data_group(
  data,
  select = NULL,
  exclude = NULL,
  ignore_case = FALSE,
  regex = FALSE,
  verbose = TRUE,
  ...
)

data_ungroup(data, verbose = TRUE, ...)
}
\arguments{
\item{data}{A data frame}

\item{select}{Variables that will be included when performing the required
tasks. Can be either
\itemize{
\item a variable specified as a literal variable name (e.g., \code{column_name}),
\item a string with the variable name (e.g., \code{"column_name"}), or a character
vector of variable names (e.g., \code{c("col1", "col2", "col3")}),
\item a formula with variable names (e.g., \code{~column_1 + column_2}),
\item a vector of positive integers, giving the positions counting from the left
(e.g. \code{1} or \code{c(1, 3, 5)}),
\item a vector of negative integers, giving the positions counting from the
right (e.g., \code{-1} or \code{-1:-3}),
\item one of the following select-helpers: \code{starts_with()}, \code{ends_with()},
\code{contains()}, a range using \code{:} or \code{regex("")}. \code{starts_with()},
\code{ends_with()}, and  \code{contains()} accept several patterns, e.g
\code{starts_with("Sep", "Petal")}.
\item or a function testing for logical conditions, e.g. \code{is.numeric()} (or
\code{is.numeric}), or any user-defined function that selects the variables
for which the function returns \code{TRUE} (like: \code{foo <- function(x) mean(x) > 3}),
\item ranges specified via literal variable names, select-helpers (except
\code{regex()}) and (user-defined) functions can be negated, i.e. return
non-matching elements, when prefixed with a \code{-}, e.g. \code{-ends_with("")},
\code{-is.numeric} or \code{-Sepal.Width:Petal.Length}. \strong{Note:} Negation means
that matches are \emph{excluded}, and thus, the \code{exclude} argument can be
used alternatively. For instance, \code{select=-ends_with("Length")} (with
\code{-}) is equivalent to \code{exclude=ends_with("Length")} (no \code{-}). In case
negation should not work as expected, use the \code{exclude} argument instead.
}

If \code{NULL}, selects all columns. Patterns that found no matches are silently
ignored, e.g. \code{find_columns(iris, select = c("Species", "Test"))} will just
return \code{"Species"}.}

\item{exclude}{See \code{select}, however, column names matched by the pattern
from \code{exclude} will be excluded instead of selected. If \code{NULL} (the default),
excludes no columns.}

\item{ignore_case}{Logical, if \code{TRUE} and when one of the select-helpers or
a regular expression is used in \code{select}, ignores lower/upper case in the
search pattern when matching against variable names.}

\item{regex}{Logical, if \code{TRUE}, the search pattern from \code{select} will be
treated as regular expression. When \code{regex = TRUE}, select \emph{must} be a
character string (or a variable containing a character string) and is not
allowed to be one of the supported select-helpers or a character vector
of length > 1. \code{regex = TRUE} is comparable to using one of the two
select-helpers, \code{select = contains("")} or \code{select = regex("")}, however,
since the select-helpers may not work when called from inside other
functions (see 'Details'), this argument may be used as workaround.}

\item{verbose}{Toggle warnings.}

\item{...}{Arguments passed down to other functions. Mostly not used yet.}
}
\value{
A grouped data frame, i.e. a data frame with additional information
about the grouping structure saved as attributes.
}
\description{
This function is comparable to \code{dplyr::group_by()}, but just
following the \strong{datawizard} function design. \code{data_ungroup()} removes the
grouping information from a grouped data frame.
}
\examples{
\dontshow{if (requireNamespace("poorman")) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
data(efc)
suppressPackageStartupMessages(library(poorman, quietly = TRUE))

# total mean
efc \%>\%
  summarize(mean_hours = mean(c12hour, na.rm = TRUE))

# mean by educational level
efc \%>\%
  data_group(c172code) \%>\%
  summarize(mean_hours = mean(c12hour, na.rm = TRUE))
\dontshow{\}) # examplesIf}
}
