python finance 7 merge csv

merge all csv files into one that has date and each company's daily closing price

about 500 companies record, skip a few unfounded csv file

save merged csv in joined_closes

import datetime as dt

import pandas as pd

import pandas_datareader.data as web

import bs4 as bs

import pickle

import requests

import os

def compile_data():

    with open('sp500tickers.pickle', 'rb') as f:

        tickers = pickle.load(f)

    main_df = pd.DataFrame()

    for count, ticker in enumerate(tickers):

        try:

            ticker = ticker.strip('\n').split('.')[0]

            df = pd.read_csv('stock_dfs/{}.csv'.format(ticker))

            df.set_index('Date', inplace=True)

            #only interested in closing price, drop the rest, change column header to company name

            df.rename(columns = {'Adj Close': ticker}, inplace=True)

            df.drop(['Open', 'High', 'Low', 'Close', 'Volume'], 1, inplace=True)

            if main_df.empty:

                main_df = df

            else:

                #concat columns from different csv

                main_df = main_df.join(df, how='outer')

            if count % 10 == 0:

                print(count)

        except:

            print(ticker, ' not found')

    print(main_df.tail())

    main_df.to_csv('sp500_joined_closes.csv')

compile_data()

reference:
https://www.youtube.com/watch?v=j0zW_KXyQJ4&list=PLQVvvaa0QuDcOdF96TBtRtuQksErCEBYZ&index=7