如何通过将字符串转换为环境中可用的同名函数来改变包含函数的列表列？

Question

I'm building a tibble in which I organize names (as chr ) of data objects and the relevant wrangling function for each one.

For example, I have one function for wrangling mtcars and one function for wrangling iris :

library(dplyr)

wrangle_mtcars <- function() {
  mtcars %>%
    group_by(am) %>%
    summarise(mean_mpg = mean(mpg))
}

wrangle_iris <- function() {
  iris %>%
    group_by(Species) %>%
    summarise(across(starts_with("Sepal"), mean))
}

And I want to organize them in a table that looks like that:

library(tibble)

my_trb <-
  tribble(~data_name, ~.fn_wrangling,
          "mtcars", wrangle_mtcars,
          "iris", wrangle_iris)

my_trb
#> # A tibble: 2 x 2
#>   data_name .fn_wrangling
#>   <chr>     <list>       
#> 1 mtcars    <fn>         
#> 2 iris      <fn>

But instead of building my_trb manually as I did above, I want to do it programmatically . That is, if I'm already given a 1-column table with the name of the data object, I want to simply paste a "wrangle_" prefix and have the tibble "understand" that I'm referring to the function with the same name that is in the global environment.

In other words I want to get from:

given_table <- tibble(data_name = c("mtcars", "iris"))

to

## # A tibble: 2 x 2
##   data_name .fn_wrangling
##   <chr>     <list>       
## 1 mtcars    <fn>         
## 2 iris      <fn>  

By doing something like:

given_table %>%
  mutate(.fn_wrangling = list(paste0("wrangle_", data_name) %>% as.name))

## # A tibble: 2 x 2
##   data_name .fn_wrangling
##   <chr>     <list>       
## 1 mtcars    <sym>  # <----| but I want it to be <fn> as in `my_trb`, not <sym>       
## 2 iris      <sym>  # <----|

But if I use as.function() instead of as.name() it throws an error:

given_table %>%
  mutate(.fn_wrangling = list(paste0("wrangle_", data_name) %>% as.function))

Error: Problem with mutate() column .fn_wrangling .
i .fn_wrangling = list(paste0("wrangle_", data_name) %>% as.function) .
x list argument expected

Answer 1

We could use match.fun

library(dplyr)
given_table %>% 
  rowwise %>%
   mutate(.fn_wrangling = list(match.fun(paste0("wrangle_", data_name)))) %>% 
  ungroup
# A tibble: 2 × 2
  data_name .fn_wrangling
  <chr>     <list>       
1 mtcars    <fn>         
2 iris      <fn>