Applying function to specific columns of dataframes in list

Question

I have a list of dataframes with common columns that I need to merge, but I need to coerce certain columns to character type first prior to merging. To fix this, I wrote the following:

master_list <- lapply(master_list, function(x) x %>%
                     mutate_at(.vars = vars(master_list$x$'send date',
                                            master_list$x$'send time',
                                            master_list$x$'Monthly',
                                            master_list$x$'InteractionEventDate'),
                               .funs = as.character))

However, when I look at these columns in any one dataframe in my list, the change was not made (e.g. InteractionEventDate is still a double), despite no error being thrown by the above line of code. I based it partially on the answer to this post, which used the now deprecated mutate_each.

score 0 · Answer 1 · answered Apr 17 '20 at 14:14

0

Your approach is a bit roundabout here. So maybe first define a function using dplyr logic and then lapply it over the list?

premerge <- function(df){
            df %>%
               mutate_at(.vars = c("send date","send time", "Monthly","InteractionEventDate"), .funs = as.character)                        
              }

lappyl(master_list,premerge)

answered Apr 17 '20 at 14:14

Fnguyen

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I tried your suggestion, but get this following: "Error: Can't subset columns that don't exist. x The column `send date` doesn't exist." – The_Dude Apr 17 '20 at 14:18
@The_Dude do ALL data frames have this column? – Fnguyen Apr 17 '20 at 14:19
ah that was the issue. I had some empty dataframes in my list, and your suggestion works now after removing them. – The_Dude Apr 17 '20 at 14:27
@The_Dude glad to help. – Fnguyen Apr 17 '20 at 14:38

Applying function to specific columns of dataframes in list

1 Answers1