將來自不同目錄路徑的多個.csv文件與python合並

Question

我正在嘗試使用pandas中的數據框將多個.csv文件合並為一個.csv文件。 棘手的是，我需要從多天內抓取多個文件。 如果這沒有意義，請告訴我。 就目前而言，我無法弄清楚如何遍歷目錄。 您能提供一些幫助嗎？

import csv
import pandas as pd
import datetime as dt
import glob, os


startDate = 20160613
endDate = 20160614

dateRange = endDate - startDate
dateRange = dateRange + 1
todaysDateFilePath = startDate


for x in xrange(dateRange):
    print startDate
    startDate = startDate + 1
    filePath = os.path.join(r"\\export\path", startDate, "preprocessed")
    os.chdir(filePath)
    interesting_files = glob.glob("trade" + "*.csv")

print interesting_files

df_list = []
for filename in sorted(interesting_files):
    df_list.append(pd.read_csv(filename))
    full_df = pd.concat(df_list)




saveFilepath = r"U:\Chris\Test_Daily_Fails"
fileList = []


full_df.to_csv(saveFilepath + '\\Files_For_IN' + "_0613_" + ".csv", index = False)

Answer 1

IIUC您可以創建list all_files並循環將glob輸出追加到all_files ：

all_files = []
for x in xrange(dateRange):
    print startDate
    startDate = startDate + 1
    filePath = os.path.join(r"\\export\path", startDate, "preprocessed")
    os.chdir(filePath)
    all_files = all_files + glob.glob("trade" + "*.csv")

print interesting_files

另外，您需要首先將所有值附加到df_list ，然后只需一次concat （我縮進了concat代碼）：

df_list = []
for filename in sorted(interesting_files):
    df_list.append(pd.read_csv(filename))

full_df = pd.concat(df_list)