If I have a function defined using rlang, how I can use purrr::map to use it with several variables ?
Suppose I have a function defined as:
mean_by <- function(data, by, var) {
data %>%
group_by({{ by }}) %>%
summarise(avg = mean({{ var }}, na.rm = TRUE))
}
Which computes group means,
Preferably using a purrr::map solution, how could I apply this function for several "by" variables but a single "var" in a data frame?
You need the !!! operator or using group_by_at
library(tidyverse)
mean_by <- function(data, by, var) {
data %>%
group_by_at(by) %>%
summarise(avg = {{var}} %>% mean(na.rm =TRUE))
}
mtcars %>%
mean_by(by = vars(mpg,cyl),hp)
#> # A tibble: 27 x 3
#> # Groups: mpg [25]
#> mpg cyl avg
#> <dbl> <dbl> <dbl>
#> 1 10.4 8 210
#> 2 13.3 8 245
#> 3 14.3 8 245
#> 4 14.7 8 230
#> 5 15 8 335
#> 6 15.2 8 165
#> 7 15.5 8 150
#> 8 15.8 8 264
#> 9 16.4 8 180
#> 10 17.3 8 180
#> # … with 17 more rows
# or
mean_by <- function(data, by, var) {
data %>%
group_by(!!!by) %>%
summarise(avg = {{var}} %>% mean(na.rm =TRUE))
}
mtcars %>%
mean_by(by = vars(cyl,disp),hp)
#> # A tibble: 27 x 3
#> # Groups: cyl [3]
#> cyl disp avg
#> <dbl> <dbl> <dbl>
#> 1 4 71.1 65
#> 2 4 75.7 52
#> 3 4 78.7 66
#> 4 4 79 66
#> 5 4 95.1 113
#> 6 4 108 93
#> 7 4 120. 97
#> 8 4 120. 91
#> 9 4 121 109
#> 10 4 141. 95
#> # … with 17 more rows
Created on 2020-01-07 by the reprex package (v0.3.0)
A good alternative is to "pass the dots".
The first argument will be the single variable you want to summarise, and use ... to pass all (if any) grouping variables you want.
This way you have a cleaner syntax for your function and you avoid including the vars function.
library(tidyverse)
mean_by <- function(data, var, ...) {
data %>%
group_by(...) %>%
summarise(avg = {{var}} %>% mean(na.rm =TRUE))
}
mtcars %>%
mean_by(hp, cyl, disp)
#> # A tibble: 27 x 3
#> # Groups: cyl [3]
#> cyl disp avg
#> <dbl> <dbl> <dbl>
#> 1 4 71.1 65
#> 2 4 75.7 52
#> 3 4 78.7 66
#> 4 4 79 66
#> 5 4 95.1 113
#> 6 4 108 93
#> 7 4 120. 97
#> 8 4 120. 91
#> 9 4 121 109
#> 10 4 141. 95
#> # ... with 17 more rows
mtcars %>%
mean_by(hp)
#> # A tibble: 1 x 1
#> avg
#> <dbl>
#> 1 147.
Created on 2020-01-08 by the reprex package (v0.3.0)
