In dplyr: A Grammar of Data Manipulation

# So the second library() call doesn't show messages
library(tidyverse)

Here we show the usage for the basic selection operators. See the specific help pages to learn about helpers like [starts_with()].

The selection language can be used in functions like dplyr::select(). Let's first attach the tidyverse:

library(tidyverse)

# For better printing
iris <- as_tibble(iris)

Select variables by name:

starwars |> select(height)

iris |> select(Sepal.Length)

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

starwars |> select(homeworld, height, mass)

iris |> select(Sepal.Length, Petal.Length)

If you use a named vector to select columns, the output will have its columns renamed:

selection <- c(
  new_homeworld = "homeworld",
  new_height = "height",
  new_mass = "mass"
)
starwars |> select(all_of(selection))

Operators:

The : operator selects a range of consecutive variables:

starwars |> select(name:mass)

The ! operator negates a selection:

starwars |> select(!(name:mass))

iris |> select(!c(Sepal.Length, Petal.Length))

iris |> select(!ends_with("Width"))

& and | take the intersection or the union of two selections:

iris |> select(starts_with("Petal") & ends_with("Width"))

iris |> select(starts_with("Petal") | ends_with("Width"))

To take the difference between two selections, combine the & and ! operators:

iris |> select(starts_with("Petal") & !ends_with("Width"))

dplyr documentation built on Feb. 3, 2026, 9:08 a.m.