Apply an `as.character()` function to a list of dataframes

So essentially I have a list of dataframes that I want to apply as.character() to.
To obtain the list of dataframes I have a list of files that I read in using a map() function and a read funtion that I created. I can’t use map_df() because there are columns that are being read in as different data types. All of the files are the same and I know that I could hard code the data types in the read function if I wanted, but I want to avoid that if I can.

At this point I throw the list of dataframes in a for loop and apply another map() function to apply the as.character() function. This final list of dataframes is then compressed using bind_rows().

All in all, this seems like an extremely convoluted process, see code below.

audits <- list.files()


my_reader <- function(x) {
  
 my_file <- read_xlsx(x)
  
  
}


audits <- map(audits, my_reader)

for (i in 1:length(audits)) {
  
  audits[[i]] <- map_df(audits[[i]], as.character)
  
  
}

audits <- bind_rows(audits)

Does anybody have any ideas on how I can improve this? Ideally to the point where I can do everything in a single vectorised map() function?

For reproducibility you can use two iris datasets with one of the columns datatypes changed.

iris2 <- iris

iris2[1] <- as.character(iris2[1])

my_list <- list(iris, iris2)

>Solution :

as.character works on vector whereas data.frame is a list of vectors. An option is to use across if we want only a single use of map

library(dplyr)
library(purrr)
map_dfr(my_list, ~ .x %>%
        mutate(across(everything(), as.character)))