import requests
from bs4 import BeautifulSoup
import pandas as pd
url = "https://www.google.com/finance/historical?cid=207437&startdate=Jan%201%2C%201971&enddate=Jul%201%2C%202017&start={0}&num=30"
#change this to 138
how_many_pages=3
start=0
for i in range(how_many_pages):
new_url = url.format(start)
page = requests.get(new_url)
soup = BeautifulSoup(page.content, "html5lib")
table = soup.find_all('table', class_='gf-table historical_price')[0]
columns_header = [th.getText() for th in table.findAll('tr')[0].findAll('th')]
data_rows=table.findAll('tr')[1:]
data=[[td.getText() for td in data_rows[i].findAll(['td'])] for i in range(len(data_rows))]
if (start == 0):
final_df = pd.DataFrame(data, columns=columns_header)
else:
df=pd.DataFrame(data, columns=columns_header)
final_df = pd.concat([final_df, df],axis=0)
start += 30
#write your code to save final_df to csv
你应该能够下载股票数据使用下面的代码。在
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