I have many ".csv" files in one folder with names "file1", "file2", "file3", ... "file50". They all have totally the same structure. Expression for reading one file is:
read.csv(file = "file1.csv", delim = ";", dec = ".")
I need to union (append) all these files in one dataset. How to do it in the most short way?
The idea here is to make a table of all your files, then apply the read_csv() function to each of those files (rows of your table) to create a new column with the data from each csv file.
Finally, use bind_rows() on the data column to get your appended dataset. You could call distinct() on the result before doing the bind_rows() call to get the union of all these files (i.e. no duplicates).
For example, this could work:
library(tidyverse)
result <- tibble(fns = dir(path = "C:/Users/ncama/Downloads", pattern = "csv", full.names = T)) %>%
mutate(data = map(fns, read_csv, show_col_types = F)); result
#> # A tibble: 5 x 2
#> fns data
#> <chr> <list>
#> 1 C:/Users/ncama/Downloads/csv1 - Copy (2).csv <spec_tbl_df [1 x 2]>
#> 2 C:/Users/ncama/Downloads/csv1 - Copy (3).csv <spec_tbl_df [1 x 2]>
#> 3 C:/Users/ncama/Downloads/csv1 - Copy (4).csv <spec_tbl_df [1 x 2]>
#> 4 C:/Users/ncama/Downloads/csv1 - Copy.csv <spec_tbl_df [1 x 2]>
#> 5 C:/Users/ncama/Downloads/csv1.csv <spec_tbl_df [1 x 2]>
bind_rows(result$data)
#> # A tibble: 5 x 2
#> A B
#> <chr> <chr>
#> 1 hello world
#> 2 hello world
#> 3 hello world
#> 4 hello world
#> 5 hello world
Created on 2022-04-20 by the reprex package (v2.0.1)
Where obviously you should change the path to the path of your folder. If you all these files have the csv extension, this should work.
