dplyr_tidy_select: Argument type: tidy-select
In dplyr: A Grammar of Data Manipulation

dplyr_tidy_select

R Documentation

Argument type: tidy-select

Description

This page describes the ⁠<tidy-select>⁠ argument modifier which indicates the argument supports tidy selections. Tidy selection provides a concise dialect of R for selecting variables based on their names or properties.

Tidy selection is a variant of tidy evaluation. This means that inside functions, tidy-select arguments require special attention, as described in the Indirection section below. If you've never heard of tidy evaluation before, start with vignette("programming").

Overview of selection features

Tidyverse selections implement a dialect of R where operators make it easy to select variables:

: for selecting a range of consecutive variables.
! for taking the complement of a set of variables.
& and | for selecting the intersection or the union of two sets of variables.
c() for combining selections.

In addition, you can use selection helpers. Some helpers select specific columns:

everything(): Matches all variables.
last_col(): Select last variable, possibly with an offset.
group_cols(): Select all grouping columns.

Other helpers select variables by matching patterns in their names:

starts_with(): Starts with a prefix.
ends_with(): Ends with a suffix.
contains(): Contains a literal string.
matches(): Matches a regular expression.
num_range(): Matches a numerical range like x01, x02, x03.

Or from variables stored in a character vector:

all_of(): Matches variable names in a character vector. All names must be present, otherwise an out-of-bounds error is thrown.
any_of(): Same as all_of(), except that no error is thrown for names that don't exist.

Or using a predicate function:

where(): Applies a function to all variables and selects those for which the function returns TRUE.

Indirection

There are two main cases:

If you have a character vector of column names, use all_of() or any_of(), depending on whether or not you want unknown variable names to cause an error, e.g. select(df, all_of(vars)), select(df, !any_of(vars)).
If you want the user to be able to supply a tidyselect specification in a function argument, embrace the function argument, e.g. select(df, {{ vars }}).