Get the column names passed to a data-masked expression

This is a helper function that evaluates a tidyselect expression in the context of a data frame and returns the names of the columns that were selected.

Usage

passed_colnames(data, expr)

Arguments

data: A data frame in which to evaluate the expression.
expr: A tidyselect expression (usually a quosure from rlang::enquo()) that specifies which columns to select.

Value

A character vector of column names that were selected by the expression.

The function returns character(0) when NULL is passed, which can signal no columns were selected. (note group_by(all_of(character(0))) conveniently does nothing.

The function will error if the expression selects columns that are not present in the data frame.

Details

This is useful in a dplyr-style function where you want the user to be able to specify no, one, or multiple columns using tidyselect syntax, and you want to get the names of those columns for further processing.

Examples

library(dplyr)

averages <- function(data, values, groups = NULL) {
  group_cols <- passed_colnames(data, rlang::enquo(groups))

  data |>
    group_by(across(all_of(group_cols))) |>
    summarise(avg = mean({{ values }}), .groups = "drop")
}

mtcars |> averages(values = mpg, groups = c(cyl, gear))
#> # A tibble: 8 × 3
#>     cyl  gear   avg
#>   <dbl> <dbl> <dbl>
#> 1     4     3  21.5
#> 2     4     4  26.9
#> 3     4     5  28.2
#> 4     6     3  19.8
#> 5     6     4  19.8
#> 6     6     5  19.7
#> 7     8     3  15.0
#> 8     8     5  15.4
mtcars |> averages(values = mpg, groups = cyl)
#> # A tibble: 3 × 2
#>     cyl   avg
#>   <dbl> <dbl>
#> 1     4  26.7
#> 2     6  19.7
#> 3     8  15.1
mtcars |> averages(mpg, starts_with("c"))
#> # A tibble: 9 × 3
#>     cyl  carb   avg
#>   <dbl> <dbl> <dbl>
#> 1     4     1  27.6
#> 2     4     2  25.9
#> 3     6     1  19.8
#> 4     6     4  19.8
#> 5     6     6  19.7
#> 6     8     2  17.2
#> 7     8     3  16.3
#> 8     8     4  13.2
#> 9     8     8  15  
mtcars |> averages(values = mpg, groups = NULL)
#> # A tibble: 1 × 1
#>     avg
#>   <dbl>
#> 1  20.1