| dplyr_tidy_select {dplyr} | R Documentation |
This page the 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. If you've never heard of tidy evaluation before,
start with vignette("programming").
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.
These 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.
These helpers select variables from 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.
This helper selects variables with a function:
where(): Applies a function to all variables and selects those
for which the function returns TRUE.
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 you want the user to supply a tidyselect specification in a
function argument, embrace the function argument, e.g
select(df, {{ vars }}).