How to create a function that truncates a subset of data frame columns based on a list of field length values in R?

I have a data frame in which some of the fields need to be truncated to different lengths. Here is a sample data:

library(dplyr)

id <- c(1111, 2222, 3333, 4444, 5555)
first_name <- c("Jonathan", "Sally", "Courtney", "Stephen", "Matthew")
last_name <- c("Johnson", "Montgomery", "Cunningham", "Stephenson", "Matthews")
Height <- c(200, 160, 170, 180, 190)
 
df <- data.frame(id, first_name, last_name, Height, stringsAsFactors = FALSE)

I want to truncate first_name and last_name columns to the corresponding lengths of 3 and 5. I created a simple function that accepts a data frame, field name and field length.

truncate_fields <- function(df, field, n) {
  df_tr <-
    mutate(df, {{field}} := str_trunc({{field}}, n, ellipsis = ""))
  return(df_tr)
}

The function works great. I now want to apply it to a subset of columns using a list of lengths.

fields <- c("first_name", "last_name")
lengths <- c(3, 5)

for(i in 1:length(fields)) {
  df <-
    truncate_fields(df, noquote(fields)[i], lengths[i])
}

However I get the following error:

Error in `splice()`:
! The LHS of `:=` must be a string or a symbol

I also tried lapply and mapply without much success. Any help is greatly appreciated. Thank you.

>Solution :

The noquote function only affects how string values are printed the the console. noquote("variable") is very different from just variable. If you want to turn a string into a symbol, you can use rlang::sym and inject that into the calling expression with !!. So the following will work

for(i in 1:length(fields)) {
  df <-
    truncate_fields(df, !!rlang::sym((fields)[i]), lengths[i])
}

and that will be logically equivalent to

df <- truncate_fields(df, first_name, 3)
df <- truncate_fields(df, last_name, 5)