Hi, guys!
I have been trying to import 4 .csv files at once.
Each .csv will be a data.frame.
My code:
files <- list.files(path = "data-raw/csgo_stat/", pattern = "*.csv") |> stringr::str_remove(".csv")
multiple_csv <- sapply(paste0("data-raw/csgo_stat/",files,".csv"), read.csv)
for(i in 1:length(multiple_csv)){
assign(paste0(files[[i]]), multiple_csv |> purrr::pluck(i))
}
This worked, but I'm pretty sure that there is a easy way to do it.
Thanks a lot!
If you want the data to be in separate data frames, you could try this. I like datatable because its faster on large files.
library(dplyr)
library(data.table)
data_path <- "data-raw/csgo_stat/"
files_df <- paste0(data_path, list.files(path = data_path, pattern = "*.csv")) %>% lapply(FUN=function(f) {
fread(f) })
1 Like
Cool!
Thanks for the sugestion!
system
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