Is it possible to pass multible variables to the same curly curly? - r

Question

I am building a function that uses {{ }} (curly curly or double mustache)
I would like the user to be able to pass multiple variables into the same {{ }}, but I am not sure if this is possible using {{ }}. I can't find any examples showing how to do this.
Can you tell me if it possible, and if yes help me make the below minimal reprex work?
library(tidyverse)
group_mean <- function(.data, group){
.data %>%
group_by({{group}}) %>%
summarise_all(mean)
}
# Works
mtcars %>%
group_mean(group = cyl)
# Fails
mtcars %>%
group_mean(group = c(cyl, am))
Error: Column `c(cyl, am)` must be length 32 (the number of rows) or one, not 64

Answer 1

Edit 2022: Nowadays we'd tend to use the c() syntax of tidyselect for taking in multiple groups of variables.
library(dplyr)
my_mean <- function(data, group_vars, summary_vars) {
data |>
group_by(across({{ group_vars }})) |>
summarise(across({{ summary_vars }}, \(x) mean(x, na.rm = TRUE)))
}
mtcars |> my_mean(c(cyl, am), c(mpg, disp))
#> `summarise()` has grouped output by 'cyl'. You can override using the
#> `.groups` argument.
#> # A tibble: 6 × 4
#> # Groups: cyl [3]
#> cyl am mpg disp
#> <dbl> <dbl> <dbl> <dbl>
#> 1 4 0 22.9 136.
#> 2 4 1 28.1 93.6
#> 3 6 0 19.1 205.
#> 4 6 1 20.6 155
#> 5 8 0 15.0 358.
#> 6 8 1 15.4 326
See also the Bidge patterns section in https://rlang.r-lib.org/reference/topic-data-mask-programming.html
If your function takes several groups of multiple variables, you need external quoting with vars(). This function simply capture its inputs as a list of expressions:
vars(foo, bar)
#> [[1]]
#> <quosure>
#> expr: ^foo
#> env: global
#>
#> [[2]]
#> <quosure>
#> expr: ^bar
#> env: global
Take an argument that you splice with !!!:
group_mean <- function(.data, .vars, ...) {
.data <- doingsomethingelse(.data, ...)
.data %>%
group_by(!!!.vars) %>%
summarise_all(mean)
}
Use it like this:
data %>% group_mean(vars(foo, bar), baz, quux)

Answer 2

For multiple grouping variables, you don't need curly-curly, pass three dots instead.
group_mean <- function(.data, ...){
.data %>%
group_by(...) %>%
summarise_all(mean)
}
mtcars %>% group_mean(cyl)
# A tibble: 3 x 11
# cyl mpg disp hp drat wt qsec vs am gear carb
# <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#1 4 26.7 105. 82.6 4.07 2.29 19.1 0.909 0.727 4.09 1.55
#2 6 19.7 183. 122. 3.59 3.12 18.0 0.571 0.429 3.86 3.43
#3 8 15.1 353. 209. 3.23 4.00 16.8 0 0.143 3.29 3.5
mtcars %>% group_mean(cyl, am)
# cyl am mpg disp hp drat wt qsec vs gear carb
# <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#1 4 0 22.9 136. 84.7 3.77 2.94 21.0 1 3.67 1.67
#2 4 1 28.1 93.6 81.9 4.18 2.04 18.4 0.875 4.25 1.5
#3 6 0 19.1 205. 115. 3.42 3.39 19.2 1 3.5 2.5
#4 6 1 20.6 155 132. 3.81 2.76 16.3 0 4.33 4.67
#5 8 0 15.0 358. 194. 3.12 4.10 17.1 0 3 3.08
#6 8 1 15.4 326 300. 3.88 3.37 14.6 0 5 6