How to Import Multiple .Csv Files At Once

How to import multiple .csv files at once?

Something like the following should result in each data frame as a separate element in a single list:

temp = list.files(pattern="*.csv")
myfiles = lapply(temp, read.delim)

This assumes that you have those CSVs in a single directory--your current working directory--and that all of them have the lower-case extension .csv.

If you then want to combine those data frames into a single data frame, see the solutions in other answers using things like do.call(rbind,...), dplyr::bind_rows() or data.table::rbindlist().

If you really want each data frame in a separate object, even though that's often inadvisable, you could do the following with assign:

temp = list.files(pattern="*.csv")
for (i in 1:length(temp)) assign(temp[i], read.csv(temp[i]))

Or, without assign, and to demonstrate (1) how the file name can be cleaned up and (2) show how to use list2env, you can try the following:

temp = list.files(pattern="*.csv")
list2env(
  lapply(setNames(temp, make.names(gsub("*.csv$", "", temp))), 
         read.csv), envir = .GlobalEnv)

But again, it's often better to leave them in a single list.

How to import multiple .csv files from folder into R and select columns?

You may try this approach -

#column names
cols <- c('col1', 'col5', 'col6', ...)
#Or column numbers
#cols <- c(1, 5, 6, ...)

library(dplyr)
library(purrr)

all_files <- list.files('/csv/folder', pattern = '\\.csv$', full.names = TRUE)
result <- map_df(all_files, 
            ~.x %>% readr::read_csv() %>% select(cols), .id = 'filenum')

result

In result, I have also created an additional column called filenum which will indicate the file number from where the row is originating.

How to import multiple .csv files that contain the same information at once?

maybe you should try:

filenames = list.files(pattern=".csv", full.names=TRUE)
myfiles = lapply(filenames, read_csv)

# i added this line and it is working
myfiles = setNames(myfiles, basename(filenames))

names(myfiles)<-str_remove(names(myfiles), '.csv')

How to import multiple csv files at once

use a loop

https://intellipaat.com/community/17913/import-multiple-csv-files-into-pandas-and-concatenate-into-one-dataframe

import glob

import pandas as pd

# get data file names

local_path = r'/my_files'

filenames = glob.glob(local_path + "/*.csv")

dfs = [pd.read_csv(filename)) for filename in filenames]


# if needed concatenate all data into one DataFrame

big_frame = pd.concat(dfs, ignore_index=True)

Also you can try put data online: github or google drive and read from there
https://towardsdatascience.com/3-ways-to-load-csv-files-into-colab-7c14fcbdcb92

How to load multiple csv files into seperate objects(dataframes) in R based on filename?

Solution for anyone curious...

files <- list.files(pattern = ".*csv")

for(file in 1:length(files)) { 
  file_name <- paste(c("file00",file), collapse = " ")
  file_name <- gsub(" ", "", file_name, fixed = TRUE)
  ex_file_name <- paste(c("exfile00",file), collapse = " ")
  ex_file_name <- gsub(" ", "", ex_file_name, fixed = TRUE)
  
  file_object <- read.csv(file = paste(file_name, ".csv", sep=""),fileEncoding="UTF-8-BOM")
  exfile_object <- read.csv(file = paste(ex_file_name, ".csv", sep=""),fileEncoding="UTF-8-BOM")
  }

Essentially build the filename within the loop, then passs it to the readcsv function on each iteration.

How can I read multiple csv files into R at once and know which file the data is from?

In case you want to use base R you can use

file.names <- list.files(pattern = "*.csv")

df.list <- lapply(file.names, function(file.name)
                              {
                                    df           <- read.csv(file.name)
                                    df$file.name <- file.name
                                    return(df)
                               })

df <- list.rbind(df.list)

Import multiple .csv files with different name pattern as a different dataframe

EDIT: you can try map.

library(tidyverse)

patterns <- c('pattern1', 'pattern2', 'pattern3')


lst <- patterns %>%
  map(
    ~list.files(path = my_path, pattern = .x, full.names=TRUE) %>%
      map(read_csv) %>% 
      bind_rows()
  )

names(lst) <- patterns

Export multiple .csv files into .txt files in one go

Here's code that does exactly what I suggested in my earlier comment.

It makes use of the built-in pathlib module to simplify processing.

import pandas as pd
from pathlib import Path


def export_csv(input_filepath, output_filepath):
    """Reformat input file and save result to the given output file path."""
    data = pd.read_csv(input_filepath)
    data.drop('symbol', inplace=True, axis=1)
    data['datetime'] = pd.to_datetime(data['datetime']).dt.strftime('%Y%m%d')
    data.to_csv(output_filepath, sep=';', header=None, index=False)


folderpath = Path('path/to/csv/files/folder').resolve()
new_suffix = '.txt'

# Convert all .csv files in given folder.
for input_filepath in folderpath.glob('*.csv'):

    # Output file path is the same as the input file except it has a different
    # extension.
    output_filepath = input_filepath.with_suffix(new_suffix)

    export_csv(input_filepath, output_filepath)  # Convert the file.

For loop to read multiple csv files in R from different directories

You are trying to use string interpolation, which does not exist in R.

Look at the output of this:

files <- c(21,22,29,30,34,65,66,69,70,74)

for(i in files) {                                             # Loop over character vector
  print("F:/Fish[i]/Fish[i].csv")
}

Output:

[1] "F:/Fish[i]/Fish[i].csv"
[1] "F:/Fish[i]/Fish[i].csv"
[1] "F:/Fish[i]/Fish[i].csv"
[1] "F:/Fish[i]/Fish[i].csv"
[1] "F:/Fish[i]/Fish[i].csv"
[1] "F:/Fish[i]/Fish[i].csv"
[1] "F:/Fish[i]/Fish[i].csv"
[1] "F:/Fish[i]/Fish[i].csv"
[1] "F:/Fish[i]/Fish[i].csv"
[1] "F:/Fish[i]/Fish[i].csv"

Additionally, what is F? If it is a list, you will need to use double square brackets:

for(i in files) {                                             # Loop over character vector
 F[[i]] <- read.csv(paste0("F:/Fish",i,"/Fish", i, ".csv"))
}