| tidyr_tidy_select {tidyr} | R Documentation |
This page the describes the <tidy-select> argument modifier which indicates
the argument uses tidy selection (a special type of tidy evaluation).
Tidy selection provides a concise DSL for selecting variables based on their
names.
If you have a data frame with variables apple, banana, cantaloupe,
date, eggplant, fig, grape you can:
Select individual variables with their name: e.g. c(apple, fig, grape).
Select data-variables stored in an env-variable with all_of() (which
will error if a variable is not found) or any_of() (which is
relaxed and will silently drop missing variables), e.g.
if vars <- c("apple", "fig", "peach"), then all_of(vars) will
error; any_of(vars) will select apple and fig.
Select contiguous variables with :, e.g. apple:date.
Select variables with name-based helpers: e.g. ends_with("a"),
contains("g"). See full list in tidyselect::select_helpers.
Select variables of a given type with an is function: is.numeric,
is.factor, is.character, etc.
Invert a selection with !: !is.numeric, or !contains("x").
Create logical combination with | and &:
starts_with("a") | starts_with("b"), contains("x") & is.numeric
Remove variables from a collection with & and !:
is.numeric & !starts_with("a")
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 unnest(df, all_of(vars)),
unnest(df, -any_of(vars)).
If you want the user to supply a tidyselect specification in a
function argument, you need to tunnel the selection through the function
argument. This is done by embracing the function argument {{ }},
e.g unnest(df, {{ vars }}).
Learn more in vignette("programming.Rmd").