使用Pool：
import os
import pandas as pd
from multiprocessing import Pool
# wrap your csv importer in a function that can be mapped
def read_csv(filename):
'converts a filename to a pandas dataframe'
return pd.read_csv(filename)
def main():
# get a list of file names
files = os.listdir('.')
file_list = [filename for filename in files if filename.split('.')[1]=='csv']
# set up your pool
with Pool(processes=8) as pool: # or whatever your hardware can support
# have your pool map the file names to dataframes
df_list = pool.map(read_csv, file_list)
# reduce the list of dataframes to a single dataframe
combined_df = pd.concat(df_list, ignore_index=True)
if __name__ == '__main__':
main()
602392714
清零编程群