import pandas as pd

from bs4 import BeautifulSoup
import requests
import re

wkn = 'DBX0G9'
url = 'http://www.boerse-frankfurt.de/en/etfs/db+x+trackers+msci+world+information+technology+trn+index+ucits+etf+LU0540980496/price+turnover+history/historical+data'

page = 1
dates = []
prices = []
while True:
    soup = BeautifulSoup(requests.get(url+"#page="+str(page)).text)

    tmp_dates  = soup.findAll('td', class_='column-date')
    tmp_dates  = [re.sub('[\\nt\s]','',d.string) for d in tmp_dates]
    tmp_prices = soup.findAll('td', class_='column-price')
    tmp_prices = [float(re.sub('[\\nt\s]','',p.string)) for p in tmp_prices]
    if not tmp_prices or page > 2:
        break
    else:
        dates = dates + tmp_dates
        prices = prices + tmp_prices
        page = page + 1

df = pd.DataFrame(index = dates)
df[wkn] = prices