在python中将一个csv拆分为多个文件
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splitting one csv into multiple files in python
提问by Mounarajan
I have a csv file of about 5000 rows in python i want to split it into five files.
我在 python 中有一个大约 5000 行的 csv 文件,我想将它分成五个文件。
I wrote a code for it but it is not working
我为它写了一个代码,但它不起作用
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.
上面的代码创建了许多内容为空的文件。
How to split one files into five csv files?
如何将一个文件拆分为五个csv文件?
回答by Aziz Alto
In Python
在 Python 中
Use readlines()
and writelines()
to do that, here is an example:
使用readlines()
和writelines()
来做到这一点,这是一个例子:
>>> 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.
输出文件名将被编号1.csv
, 2.csv
, ... 等。
From terminal
从终端
FYI, you can do this from the command line using split
as follows:
仅供参考,您可以使用split
以下命令从命令行执行此操作:
$ split -l 1000 import_1458922827.csv
回答by Rudzianko?
I suggest you not inventing a wheel. There is existing solution. Source here
我建议你不要发明轮子。有现有的解决方案。来源在这里
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:
像这样使用它:
split(open('/your/pat/input.csv', 'r'));
回答by Shubham Najardhane
I have modified the accepted answer a little bit to make it simpler
我稍微修改了接受的答案以使其更简单
Edited: Added the import statement, modified the print statement for printing the exception. @Alex F code snippet was written for python2, for python3 you also need to use header_row = rows.__next__()
instead header_row = rows.next()
. Thanks for pointing out.
编辑:添加了导入语句,修改了打印异常的打印语句。@Alex F-码片段是为python2写入,以便python3你还需要使用header_row = rows.__next__()
代替header_row = rows.next()
。谢谢指出。
import os
import csv
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(out_dir)
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by Ryan Tuck
A python3-friendly solution:
一个python3友好的解决方案:
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by Ramesh K
@Ryan, Python3 code worked for me. I used newline=''
as below to avoid the blank line issue:
@Ryan,Python3 代码对我有用。我使用newline=''
如下以避免空行问题:
with open(target_filepath, 'w', newline='') as target:
回答by Aetos
I suggest you leverage the possibilities offered by pandas. Here are functions you could use to do that :
我建议您利用熊猫提供的可能性。以下是您可以用来执行此操作的函数:
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 :
然后在您的主要或 jupyter 笔记本中放置:
# 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.
PS1:我把nrows = 4000000
因为当它是个人喜好。如果您愿意,您可以更改该号码。
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
PS2:我使用日志库来显示消息。何时将此类功能应用于远程服务器上存在的大文件,您确实希望避免“简单打印”并合并日志记录功能。您可以替换logging.info
或logging.debug
使用print
P.S.3 : Of course, you need to replace the {# Blablabla}
parts of the code with your own parameters.
PS3:当然,你需要{# Blablabla}
用你自己的参数替换部分代码。
回答by Whitefret
if count <= count:
pass
This condition is always true so you pass everytime
此条件始终为真,因此您每次都通过
Otherwise you can look at this post: Splitting a CSV file into equal parts?
否则,您可以查看这篇文章:将 CSV 文件拆分为相等的部分?