splitting one csv into multiple files in python

问题:

I have a csv file of about 5000 rows in python i want to split it into five files.

I wrote a code for it but it is not working

import codecs
import csv
NO_OF_LINES_PER_FILE = 1000
def again(count_file_header,count):
    f3 = open('write_'+count_file_header+'.csv', 'at')
    with open('import_1458922827.csv', 'rb') as csvfile:
        candidate_info_reader = csv.reader(csvfile, delimiter=',', quoting=csv.QUOTE_ALL)
        co = 0      
        for row in candidate_info_reader:
            co = co + 1
            count  = count + 1
            if count <= count:
                pass
            elif count >= NO_OF_LINES_PER_FILE:
                count_file_header = count + NO_OF_LINES_PER_FILE
                again(count_file_header,count)
            else:
                writer = csv.writer(f3,delimiter = ',', lineterminator='\n',quoting=csv.QUOTE_ALL)
                writer.writerow(row)

def read_write():
    f3 = open('write_'+NO_OF_LINES_PER_FILE+'.csv', 'at')
    with open('import_1458922827.csv', 'rb') as csvfile:


        candidate_info_reader = csv.reader(csvfile, delimiter=',', quoting=csv.QUOTE_ALL)

        count = 0       
        for row in candidate_info_reader:
            count  = count + 1
            if count >= NO_OF_LINES_PER_FILE:
                count_file_header = count + NO_OF_LINES_PER_FILE
                again(count_file_header,count)
            else:
                writer = csv.writer(f3,delimiter = ',', lineterminator='\n',quoting=csv.QUOTE_ALL)
                writer.writerow(row)

read_write()

The above code creates many fileswith empty content.

How to split one files into five csv files?

回答1:

I suggest you not inventing a wheel. There is existing solution. Source here

import os


def split(filehandler, delimiter=',', row_limit=1000,
          output_name_template='output_%s.csv', output_path='.', keep_headers=True):
    import csv
    reader = csv.reader(filehandler, delimiter=delimiter)
    current_piece = 1
    current_out_path = os.path.join(
        output_path,
        output_name_template % current_piece
    )
    current_out_writer = csv.writer(open(current_out_path, 'w'), delimiter=delimiter)
    current_limit = row_limit
    if keep_headers:
        headers = reader.next()
        current_out_writer.writerow(headers)
    for i, row in enumerate(reader):
        if i + 1 > current_limit:
            current_piece += 1
            current_limit = row_limit * current_piece
            current_out_path = os.path.join(
                output_path,
                output_name_template % current_piece
            )
            current_out_writer = csv.writer(open(current_out_path, 'w'), delimiter=delimiter)
            if keep_headers:
                current_out_writer.writerow(headers)
        current_out_writer.writerow(row)

Use it like:

split(open('/your/pat/input.csv', 'r'));

回答2:

In Python

Use readlines() and writelines() to do that, here is an example:

>>> csvfile = open('import_1458922827.csv', 'r').readlines()
>>> filename = 1
>>> for i in range(len(csvfile)):
...     if i % 1000 == 0:
...         open(str(filename) + '.csv', 'w+').writelines(csvfile[i:i+1000])
...         filename += 1

the output file names will be numbered 1.csv, 2.csv, ... etc.

From terminal

FYI, you can do this from the command line using split as follows:

$ split -l 1000 import_1458922827.csv

回答3:

A python3-friendly solution:

def split_csv(source_filepath, dest_folder, split_file_prefix,
                records_per_file):
    """
    Split a source csv into multiple csvs of equal numbers of records,
    except the last file.

    Includes the initial header row in each split file.

    Split files follow a zero-index sequential naming convention like so:

        `{split_file_prefix}_0.csv`
    """
    if records_per_file <= 0:
        raise Exception('records_per_file must be > 0')

    with open(source_filepath, 'r') as source:
        reader = csv.reader(source)
        headers = next(reader)

        file_idx = 0
        records_exist = True

        while records_exist:

            i = 0
            target_filename = f'{split_file_prefix}_{file_idx}.csv'
            target_filepath = os.path.join(dest_folder, target_filename)

            with open(target_filepath, 'w') as target:
                writer = csv.writer(target)

                while i < records_per_file:
                    if i == 0:
                        writer.writerow(headers)

                    try:
                        writer.writerow(next(reader))
                        i += 1
                    except:
                        records_exist = False
                        break

            if i == 0:
                # we only wrote the header, so delete that file
                os.remove(target_filepath)

            file_idx += 1

回答4:

@Ryan, Python3 code worked for me. I used newline='' as below to avoid the blank line issue:

with open(target_filepath, 'w', newline='') as target:

回答5:

I have modified the accepted answer a little bit to make it simpler

def split_csv_into_chunks(file_location, out_dir, file_size=2):
    count = 0
    current_piece = 1

    # file_to_split_name.csv
    file_name = file_location.split("/")[-1].split(".")[0]
    split_file_name_template = file_name + "__%s.csv"
    splited_files_path = []

    if not os.path.exists(out_dir):
        os.makedirs(download_location)
    try:
        with open(file_location, "rb") as csv_file:
            rows = csv.reader(csv_file, delimiter=",")
            headers_row = rows.next()
            for row in rows:
                if count % file_size == 0:
                    current_out_path = os.path.join(out_dir,
                                                    split_file_name_template%str(current_piece))
                    current_out_writer = None

                    current_out_writer = csv.writer(open(current_out_path, 'w'), delimiter=",")
                    current_out_writer.writerow(headers_row)
                    splited_files_path.append(current_out_path)
                    current_piece += 1

                current_out_writer.writerow(row)
                count += 1
        return True, splited_files_path
    except Exception as e:
        print "Exception occurred as {}".format(e)
        return False, splited_files_path

回答6:

if count <= count:
   pass

This condition is always true so you pass everytime

Otherwise you can look at this post: Splitting a CSV file into equal parts?

回答7:

I suggest you leverage the possibilities offered by pandas. Here are functions you could use to do that :

def csv_count_rows(file):
    """
    Counts the number of rows in a file.
    :param file: path to the file.
    :return: number of lines in the designated file.
    """
    with open(file) as f:
        nb_lines = sum(1 for line in f)
    return nb_lines


def split_csv(file, sep=",", output_path=".", nrows=None, chunksize=None, low_memory=True, usecols=None):
    """
    Split a csv into several files.
    :param file: path to the original csv.
    :param sep: View pandas.read_csv doc.
    :param output_path: path in which to output the resulting parts of the splitting.
    :param nrows: Number of rows to split the original csv by, also view pandas.read_csv doc.
    :param chunksize: View pandas.read_csv doc.
    :param low_memory: View pandas.read_csv doc.
    :param usecols: View pandas.read_csv doc.
    """
    nb_of_rows = csv_count_rows(file)

    # Parsing file elements : Path, name, extension, etc...
    # file_path = "/".join(file.split("/")[0:-1])
    file_name = file.split("/")[-1]
    # file_ext = file_name.split(".")[-1]
    file_name_trunk = file_name.split(".")[0]
    split_files_name_trunk = file_name_trunk + "_part_"

    # Number of chunks to partition the original file into
    nb_of_chunks = math.ceil(nb_of_rows / nrows)
    if nrows:
        log_debug_process_start = f"The file '{file_name}' contains {nb_of_rows} ROWS. " \
            f"\nIt will be split into {nb_of_chunks} chunks of a max number of rows : {nrows}." \
            f"\nThe resulting files will be output in '{output_path}' as '{split_files_name_trunk}0 to {nb_of_chunks - 1}'"
        logging.debug(log_debug_process_start)

    for i in range(nb_of_chunks):
        # Number of rows to skip is determined by (the number of the chunk being processed) multiplied by (the nrows parameter).
        rows_to_skip = range(1, i * nrows) if i else None
        output_file = f"{output_path}/{split_files_name_trunk}{i}.csv"

        log_debug_chunk_processing = f"Processing chunk {i} of the file '{file_name}'"
        logging.debug(log_debug_chunk_processing)

        # Fetching the original csv file and handling it with skiprows and nrows to process its data
        df_chunk = pd.read_csv(filepath_or_buffer=file, sep=sep, nrows=nrows, skiprows=rows_to_skip,
                               chunksize=chunksize, low_memory=low_memory, usecols=usecols)
        df_chunk.to_csv(path_or_buf=output_file, sep=sep)

        log_info_file_output = f"Chunk {i} of file '{file_name}' created in '{output_file}'"
        logging.info(log_info_file_output)

And then in your main or jupyter notebook you put :

# This is how you initiate logging in the most basic way.
logging.basicConfig(level=logging.DEBUG)
file = {#Path to your file}
split_csv(file,sep=";" ,output_path={#Path where you'd like to output it},nrows = 4000000, low_memory = False)

P.S.1 : I put nrows = 4000000 because when it's a personal preference. You can change that number if you wish.

P.S.2 : I used the logging library to display messages. When would apply such a function on big files that exist on a remote server, you really want to avoid 'simple printing' and incorporate logging capabilities. You can replace logging.info or logging.debug with print

P.S.3 : Of course, you need to replace the {# Blablabla} parts of the code with your own parameters.