Importing multiple .csv files with variable column types into R

Question

How can I properly build an lapply to read (from out of one directory) all the .csv files, load all the columns as strings and then bind them into one data frame.

Per this, I have a way to get all the .csv files loaded and bound into a dataframe. Unfortunately they are getting hung up on the variablity of how the columns are getting type cast. Thus giving me this error:

Error: Can not automatically convert from character to integer in column

I have tried supplementing the code with the arguments for data type and am trying to just keep everything as characters; I am getting stuck now on being able to properly get my lapply 'loop' to effectively reference the subject of each cycle of its 'loop'.

srvy1 <- structure(list(RESPONSE_ID = 584580L, QUESTION_ID = 328L, SURVEY_ID = 2324L, 
           AFF_ID_INV_RESP = 5L), .Names = c("RESPONSE_ID", "QUESTION_ID", 
                                             "SURVEY_ID", "AFF_ID_INV_RESP"), class = "data.frame", row.names = c(NA, 
                                                                                                                  -1L))

srvy2 <- structure(list(RESPONSE_ID = 584580L, QUESTION_ID = 328L, SURVEY_ID = 2324L, 
           AFF_ID_INV_RESP = "bovine"), .Names = c("RESPONSE_ID", "QUESTION_ID", 
                                                   "SURVEY_ID", "AFF_ID_INV_RESP"), class = "data.frame", row.names = c(NA, 
                                                                                                                        -1L))    

files = list.files(pattern="*.csv")
tbl = lapply(files, read_csv(files, col_types = cols(.default = col_character()))) %>% bind_rows

Is there an easy fix for this that I can keep in tidyverse, or must I drop down a level and go into openly building the for loop myself - per this.

Answer 1

The lapply should be the form lapply(x, FUN, ...) where ... is the arguments passed to FUN. You're filling the arguments within FUN. It should be lapply(files, read_csv, col_types = cols(.default = "c"))

If you like a tidyverse solution:

files %>%
  map_df(~read_csv(.x, col_types = cols(.default = "c")))

Which will bind the whole thing into a data frame at the end.