Peform operations on column names within a user defined function

Question

I recently understood how to access a column names inside a user defined function: How to access a column name in a user defined function with dplyr?

However, now I also need to access the column names within the operations that are being carried out. For example I would like to do this:

samp_df <- tibble(var1 = c('a', 'b', 'c'),
              var_in_df = c(3,7,9))
calculateSummaries <- function(df, variable){
  df <- df %>% 
    mutate("mean_of_{{variable}}" := mean({{variable}}),
           "sd_of_{{variable}}" := sd({{variable}}),
           "sd_plus_mean_of_{{variable}}" := ("mean_of_{{variable}}" + "sd_of_{{variable}}")
           )
}
df_result <- calculateSummaries(samp_df, var_in_df)

Of course I could do:

"sd_plus_mean_of_{{variable}}" := mean({{variable}}) + sd({{variable}})

But in practice, with the real data this won't be practical.

Does anyone know how to so this?

Answer 1

This case ineed a little bit tricky, I think we have to constuct the names first and then use !! sym() to evaluate the strings as objects.

library(dplyr)

samp_df <- tibble(var1 = c('a', 'b', 'c'),
                  var_in_df = c(3,7,9))

calculateSummaries <- function(df, variable){
  
  var_nm <- deparse(substitute(variable))
  
  mean_var_nm <- paste0("mean_of_", var_nm)
  sd_var_nm <- paste0("sd_of_", var_nm)
  
  df %>%
    mutate("mean_of_{{variable}}" := mean({{variable}}),
           "sd_of_{{variable}}" := sd({{variable}}),
           "sd_plus_mean_of_{{variable}}" := !! sym(mean_var_nm) + !! sym(sd_var_nm)
    )
}

calculateSummaries(samp_df, var_in_df)

#> # A tibble: 3 x 5
#>   var1  var_in_df mean_of_var_in_df sd_of_var_in_df sd_plus_mean_of_var_in_df
#>   <chr>     <dbl>             <dbl>           <dbl>                     <dbl>
#> 1 a             3              6.33            3.06                      9.39
#> 2 b             7              6.33            3.06                      9.39
#> 3 c             9              6.33            3.06                      9.39

An alternative way is using across(), but we still have to construct the variable names.

calculateSummaries <- function(df, variable){
  
  df %>%
    mutate("mean_of_{{variable}}" := mean({{variable}}),
           "sd_of_{{variable}}" := sd({{variable}}),
           across(c({{ variable }}),
                  list(sd_plus_mean_of = ~ get(paste0("mean_of_", cur_column())) + get(paste0("sd_of_", cur_column())))
                  )
    )
}

calculateSummaries(samp_df, var_in_df)

#> # A tibble: 3 x 5
#>   var1  var_in_df mean_of_var_in_df sd_of_var_in_df var_in_df_sd_plus_mean_of
#>   <chr>     <dbl>             <dbl>           <dbl>                     <dbl>
#> 1 a             3              6.33            3.06                      9.39
#> 2 b             7              6.33            3.06                      9.39
#> 3 c             9              6.33            3.06                      9.39

Here is a final way inspired by Lionel Henry's answer to this question. We can use rlang::englue() to construct names and use those names with the .data[[...]] pronoun.

calculateSummaries <- function(df, variable){
  
  mean_var_nm <- rlang::englue("mean_of_{{ variable }}")
  sd_var_nm   <- rlang::englue("sd_of_{{ variable }}")
  
  df %>%
    mutate("mean_of_{{ variable }}" := mean({{ variable }}),
           "sd_of_{{ variable }}" := sd({{ variable }}),
           "sd_plus_mean_of_{{ variable }}" := .data[[mean_var_nm]] + .data[[sd_var_nm]]
    )
}

calculateSummaries(samp_df, var_in_df)

#> # A tibble: 3 x 5
#>   var1  var_in_df mean_of_var_in_df sd_of_var_in_df sd_plus_mean_of_var_in_df
#>   <chr>     <dbl>             <dbl>           <dbl>                     <dbl>
#> 1 a             3              6.33            3.06                      9.39
#> 2 b             7              6.33            3.06                      9.39
#> 3 c             9              6.33            3.06                      9.39

^{Created on 2022-10-13 by the reprex package (v2.0.1)}