import requests
import numpy as np
import pandas as pd
import bs4
url='https://uk.finance.yahoo.com/quote/AAPL/history?p=AAPL'
r=requests.get(url)
bsobj=bs4.BeautifulSoup(r.text,'html.parser')
historical_table=bsobj.find('table',{'class':'W(100%) M(0)'})
rows=historical_table.tbody.find_all("tr")
data=[]
for row in rows:
    cells = row.find_all("td")
    data.append([cell.text for cell in cells])
pd.DataFrame(data)