iterate reading/mutating csv files in R purr

Question

I have a folder of csv files in R that will need to loop through, clean, and create in columns based on information in the file name. I am trying to use purr and this is what I have done so far.

# get file names
files_names <- list.files("data/", recursive = TRUE, full.names = TRUE) 

# inspect
files_names 

[1] "data/BOC_All_ATMImage_(Aug 2020).txt" "data/BOC_All_ATMImage_(Aug 2021).txt" "data/BOC_All_ATMImage_(Feb 2021).txt"
[4] "data/BOC_All_ATMImage_(May 2021).txt" "data/BOC_All_ATMImage_(Nov 2020).txt" "data/BOC_All_ATMImage_(Nov 2021).txt"

# extract month/year inside brackets and convert to snakecase
# this will be used later to create column names

names_data <- files_names %>% 
  str_extract(., "(?<=\\().*?(?=\\))") %>% 
  str_to_lower() %>%
  str_replace(., " ", "_")

column_names

[1] "aug_2020" "aug_2021" "feb_2021" "may_2021" "nov_2020" "nov_2021"

now loop through the csvs, read each csv, do some data cleaning and create columns

mc_data <-
  map(files_names,
         ~ read_csv(.x, guess_max = 50000) %>%
        janitor::clean_names() %>% 
           mutate(month_year = str_extract(.x, "(?<=\\().*?(?=\\))"),
                  date_dmy = paste0(day, "-", month_year),
                  date = dmy(date_dmy),
                  fsa = str_sub(postal_code, start = 1, end=3),
                  ?? = 1) %>% 
         select(-date_dmy),
         .id = "group"
  )

I need to mutate one more column and that column has to named based on this names_data extracted. I currently have this as ?? in the fake code above. names_data follows the same order as the file path so the idea is to do it in one loop and save each data after it has been cleaned.

Answer 1

We can use glue syntax and map2 . Perhaps:

mc_data <-
    map2(files_names, column_names,
        ~ read_csv(.x, guess_max = 50000) %>%
            janitor::clean_names() %>% 
            mutate(month_year = str_extract(.x, "(?<=\\().*?(?=\\))"),
                   date_dmy = paste0(day, "-", month_year),
                   date = dmy(date_dmy),
                   fsa = str_sub(postal_code, start = 1, end=3),
                   '{.y}' := 1) %>% 
            select(-date_dmy),
        .id = "group"
    )