% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/select.R
\name{select}
\alias{select}
\alias{select.SummarizedExperiment}
\title{Keep or drop columns using their names and types}
\usage{
\method{select}{SummarizedExperiment}(.data, ...)
}
\arguments{
\item{.data}{A data frame, data frame extension (e.g. a tibble), or a
lazy data frame (e.g. from dbplyr or dtplyr). See \emph{Methods}, below, for
more details.}

\item{...}{<\code{\link[dplyr:dplyr_tidy_select]{tidy-select}}> One or more unquoted
expressions separated by commas. Variable names can be used as if they
were positions in the data frame, so expressions like \code{x:y} can
be used to select a range of variables.}
}
\value{
An object of the same type as \code{.data}. The output has the following
properties:
\itemize{
\item Rows are not affected.
\item Output columns are a subset of input columns, potentially with a different
order. Columns will be renamed if \code{new_name = old_name} form is used.
\item Data frame attributes are preserved.
\item Groups are maintained; you can't select off grouping variables.
}
}
\description{
Select (and optionally rename) variables in a data frame, using a concise
mini-language that makes it easy to refer to variables based on their name
(e.g. \code{a:f} selects all columns from \code{a} on the left to \code{f} on the
right) or type (e.g. \code{where(is.numeric)} selects all numeric columns).
\subsection{Overview of selection features}{

Tidyverse selections implement a dialect of R where operators make
it easy to select variables:
\itemize{
\item \code{:} for selecting a range of consecutive variables.
\item \code{!} for taking the complement of a set of variables.
\item \code{&} and \code{|} for selecting the intersection or the union of two
sets of variables.
\item \code{c()} for combining selections.
}

In addition, you can use \strong{selection helpers}. Some helpers select specific
columns:
\itemize{
\item \code{\link[tidyselect:everything]{everything()}}: Matches all variables.
\item \code{\link[tidyselect:everything]{last_col()}}: Select last variable, possibly with an offset.
\item \code{\link[dplyr:group_cols]{group_cols()}}: Select all grouping columns.
}

Other helpers select variables by matching patterns in their names:
\itemize{
\item \code{\link[tidyselect:starts_with]{starts_with()}}: Starts with a prefix.
\item \code{\link[tidyselect:starts_with]{ends_with()}}: Ends with a suffix.
\item \code{\link[tidyselect:starts_with]{contains()}}: Contains a literal string.
\item \code{\link[tidyselect:starts_with]{matches()}}: Matches a regular expression.
\item \code{\link[tidyselect:starts_with]{num_range()}}: Matches a numerical range like x01, x02, x03.
}

Or from variables stored in a character vector:
\itemize{
\item \code{\link[tidyselect:all_of]{all_of()}}: Matches variable names in a character vector. All
names must be present, otherwise an out-of-bounds error is
thrown.
\item \code{\link[tidyselect:all_of]{any_of()}}: Same as \code{all_of()}, except that no error is thrown
for names that don't exist.
}

Or using a predicate function:
\itemize{
\item \code{\link[tidyselect:where]{where()}}: Applies a function to all variables and selects those
for which the function returns \code{TRUE}.
}
}
}
\section{Methods}{


This function is a \strong{generic}, which means that packages can provide
implementations (methods) for other classes. See the documentation of
individual methods for extra arguments and differences in behaviour.

The following methods are currently available in loaded packages:
\Sexpr[stage=render,results=rd]{dplyr:::methods_rd("select")}.

}

\section{Examples}{



Here we show the usage for the basic selection operators. See the
specific help pages to learn about helpers like \code{\link[dplyr:starts_with]{starts_with()}}.

The selection language can be used in functions like
\code{dplyr::select()} or \code{tidyr::pivot_longer()}. Let's first attach
the tidyverse:

\if{html}{\out{<div class="sourceCode r">}}\preformatted{library(tidyverse)

# For better printing
iris <- as_tibble(iris)
}\if{html}{\out{</div>}}

Select variables by name:

\if{html}{\out{<div class="sourceCode r">}}\preformatted{starwars \%>\% select(height)
#> # A tibble: 87 x 1
#>   height
#>    <int>
#> 1    172
#> 2    167
#> 3     96
#> 4    202
#> # i 83 more rows

iris \%>\% pivot_longer(Sepal.Length)
#> # A tibble: 150 x 6
#>   Sepal.Width Petal.Length Petal.Width Species name         value
#>         <dbl>        <dbl>       <dbl> <fct>   <chr>        <dbl>
#> 1         3.5          1.4         0.2 setosa  Sepal.Length   5.1
#> 2         3            1.4         0.2 setosa  Sepal.Length   4.9
#> 3         3.2          1.3         0.2 setosa  Sepal.Length   4.7
#> 4         3.1          1.5         0.2 setosa  Sepal.Length   4.6
#> # i 146 more rows
}\if{html}{\out{</div>}}

Select multiple variables by separating them with commas. Note how
the order of columns is determined by the order of inputs:

\if{html}{\out{<div class="sourceCode r">}}\preformatted{starwars \%>\% select(homeworld, height, mass)
#> # A tibble: 87 x 3
#>   homeworld height  mass
#>   <chr>      <int> <dbl>
#> 1 Tatooine     172    77
#> 2 Tatooine     167    75
#> 3 Naboo         96    32
#> 4 Tatooine     202   136
#> # i 83 more rows
}\if{html}{\out{</div>}}

Functions like \code{tidyr::pivot_longer()} don't take variables with
dots. In this case use \code{c()} to select multiple variables:

\if{html}{\out{<div class="sourceCode r">}}\preformatted{iris \%>\% pivot_longer(c(Sepal.Length, Petal.Length))
#> # A tibble: 300 x 5
#>   Sepal.Width Petal.Width Species name         value
#>         <dbl>       <dbl> <fct>   <chr>        <dbl>
#> 1         3.5         0.2 setosa  Sepal.Length   5.1
#> 2         3.5         0.2 setosa  Petal.Length   1.4
#> 3         3           0.2 setosa  Sepal.Length   4.9
#> 4         3           0.2 setosa  Petal.Length   1.4
#> # i 296 more rows
}\if{html}{\out{</div>}}
\subsection{Operators:}{

The \code{:} operator selects a range of consecutive variables:

\if{html}{\out{<div class="sourceCode r">}}\preformatted{starwars \%>\% select(name:mass)
#> # A tibble: 87 x 3
#>   name           height  mass
#>   <chr>           <int> <dbl>
#> 1 Luke Skywalker    172    77
#> 2 C-3PO             167    75
#> 3 R2-D2              96    32
#> 4 Darth Vader       202   136
#> # i 83 more rows
}\if{html}{\out{</div>}}

The \code{!} operator negates a selection:

\if{html}{\out{<div class="sourceCode r">}}\preformatted{starwars \%>\% select(!(name:mass))
#> # A tibble: 87 x 11
#>   hair_color skin_color  eye_color birth_year sex   gender    homeworld species
#>   <chr>      <chr>       <chr>          <dbl> <chr> <chr>     <chr>     <chr>  
#> 1 blond      fair        blue            19   male  masculine Tatooine  Human  
#> 2 <NA>       gold        yellow         112   none  masculine Tatooine  Droid  
#> 3 <NA>       white, blue red             33   none  masculine Naboo     Droid  
#> 4 none       white       yellow          41.9 male  masculine Tatooine  Human  
#> # i 83 more rows
#> # i 3 more variables: films <list>, vehicles <list>, starships <list>

iris \%>\% select(!c(Sepal.Length, Petal.Length))
#> # A tibble: 150 x 3
#>   Sepal.Width Petal.Width Species
#>         <dbl>       <dbl> <fct>  
#> 1         3.5         0.2 setosa 
#> 2         3           0.2 setosa 
#> 3         3.2         0.2 setosa 
#> 4         3.1         0.2 setosa 
#> # i 146 more rows

iris \%>\% select(!ends_with("Width"))
#> # A tibble: 150 x 3
#>   Sepal.Length Petal.Length Species
#>          <dbl>        <dbl> <fct>  
#> 1          5.1          1.4 setosa 
#> 2          4.9          1.4 setosa 
#> 3          4.7          1.3 setosa 
#> 4          4.6          1.5 setosa 
#> # i 146 more rows
}\if{html}{\out{</div>}}

\code{&} and \code{|} take the intersection or the union of two selections:

\if{html}{\out{<div class="sourceCode r">}}\preformatted{iris \%>\% select(starts_with("Petal") & ends_with("Width"))
#> # A tibble: 150 x 1
#>   Petal.Width
#>         <dbl>
#> 1         0.2
#> 2         0.2
#> 3         0.2
#> 4         0.2
#> # i 146 more rows

iris \%>\% select(starts_with("Petal") | ends_with("Width"))
#> # A tibble: 150 x 3
#>   Petal.Length Petal.Width Sepal.Width
#>          <dbl>       <dbl>       <dbl>
#> 1          1.4         0.2         3.5
#> 2          1.4         0.2         3  
#> 3          1.3         0.2         3.2
#> 4          1.5         0.2         3.1
#> # i 146 more rows
}\if{html}{\out{</div>}}

To take the difference between two selections, combine the \code{&} and
\code{!} operators:

\if{html}{\out{<div class="sourceCode r">}}\preformatted{iris \%>\% select(starts_with("Petal") & !ends_with("Width"))
#> # A tibble: 150 x 1
#>   Petal.Length
#>          <dbl>
#> 1          1.4
#> 2          1.4
#> 3          1.3
#> 4          1.5
#> # i 146 more rows
}\if{html}{\out{</div>}}
}

}

\examples{
data(pasilla)
pasilla |> select(.sample, .feature, counts)

}
\references{
Hutchison, W.J., Keyes, T.J., The tidyomics Consortium. et al. The tidyomics ecosystem: enhancing omic data analyses. Nat Methods 21, 1166–1170 (2024). https://doi.org/10.1038/s41592-024-02299-2

Wickham, H., François, R., Henry, L., Müller, K., Vaughan, D. (2023). dplyr: A Grammar of Data Manipulation. R package version 2.1.4, https://CRAN.R-project.org/package=dplyr
}
\seealso{
Other single table verbs: 
\code{\link[dplyr]{arrange}()},
\code{\link[dplyr]{filter}()},
\code{\link[dplyr]{mutate}()},
\code{\link[dplyr]{reframe}()},
\code{\link[dplyr]{rename}()},
\code{\link[dplyr]{slice}()},
\code{\link[dplyr]{summarise}()}
}
