如果我理解正确的话，我们可以将每一行构建成一个列表，因为你在for循环中找到了值，并将其附加到另一个列表中。然后我们可以使用csv模块将列表的列表写入一个csv文件

# -*- coding: utf-8 -*-
"""
Created on Tue Jul 25 13:43:22 2023

@author: eruku
"""

import pandas as pd
import requests
import csv

infile = 'C:/Volume/PythonProjects/WIP_Projects/Marketsmithindia/StocksList.txt'
outfile = 'C:/Volume/PythonProjects/WIP_Projects/Marketsmithindia/MktSmithData.csv'

timeout = 10
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.0.0 Safari/537.36"
}

starturl = 'https://msi-gcloud-prod.appspot.com/gateway/simple-api/ms-india/instr/0/3023210/symboldetails.json?s=20180719&e=20230719&text='
endurl = '&lang=en&isConsolidated=0&ms-auth=3990+MarketSmithINDUID-Web0000000000+MarketSmithINDUID-Web0000000000+0+230325200706+-514613229'
# stock = 'TCS'

csvdata = []
with open(infile, 'r') as IN, open(outfile, 'w') as OUT:
    for stock in IN:
        stock = stock.strip()
        url = starturl + stock + endurl
        r = requests.get(url, headers=headers)        
        try:
            # line = '%s,%s,%s,%s' % (
            #     stock,

            # )
            df1 = pd.json_normalize(r.json()[
                                    'response']['quarterlySalesAndEarningsInternational']['quarterlySalesAndEarningsOrigin'][0])
            # df = pd.json_normalize(r.json()['response']['detailsGeneralInformationHeader'])
            df2 = pd.json_normalize(
                r.json()['response']['detailsGeneralInformationHeader'])
            GR = df2.loc[:, "industryGroupRank"]
            EPR = df2.loc[:, "epsRank"]
            Funds = df1.loc[:, "noOfFunds"]
            df1.to_csv('MktSmithData.csv', index=False)
            row = [GR, EPR, Funds]
            csvdata.append(row)
            # print(line, file=OUT)
        except KeyError as E:
            print(stock, 'KeyError:', E)

with open("out.csv", "w", newline="") as f:
    writer = csv.writer(f)
    writer.writerows(csvdata)

# print(df)
print(GR)
print(EPR)
print(Funds)

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