Add "filename" column to table as multiple files are read and bound

You could use purrr::map2 here, which works similarly to mapply

filenames <- list.files(path, full.names = TRUE, pattern = fileptrn, recursive = TRUE)
sites <- str_extract(filenames, "[A-Z]{2}-[A-Za-z0-9]{3}")  # same length as filenames

library(purrr)
library(dplyr)
library(readr)
stopifnot(length(filenames)==length(sites))  # returns error if not the same length
ans <- map2(filenames, sites, ~read_csv(.x) %>% mutate(id = .y))  # .x is element in filenames, and .y is element in sites

The output of map2 is a list, similar to lapply

If you have a development version of purrr, you can use imap, which is a wrapper for map2 with an index

tidyverse approach:

Update:

readr 2.0 (and beyond) now has built-in support for reading a list of files with the same columns into one output table in a single command. Just pass the filenames to be read in the same vector to the reading function. For example reading in csv files:

(files <- fs::dir_ls("D:/data", glob="*.csv"))
dat <- read_csv(files, id="path")

Alternatively using map_dfr with purrr: Add the filename using the .id = "source" argument in purrr::map_dfr() An example loading .csv files:

 # specify the directory, then read a list of files
  data_dir <- here("file/path")
  data_list <- fs::dir_ls(data_dir, regexp = ".csv$")

 # return a single data frame w/ purrr:map_dfr 
 my_data = data_list %>% 
    purrr::map_dfr(read_csv, .id = "source")
  
 # Alternatively, rename source from the file path to the file name
  my_data = data_list %>% 
    purrr::map_dfr(read_csv, .id = "source") %>% 
    dplyr::mutate(source = stringr::str_replace(source, "file/path", ""))
  

I generally use the following approach, based on dplyr/tidyr:

data = tibble(File = files) %>%
    extract(File, "Site", "([A-Z]{2}-[A-Za-z0-9]{3})", remove = FALSE) %>%
    mutate(Data = lapply(File, read_csv)) %>%
    unnest(Data) %>%
    select(-File)