natural language processing algorithms to identify sentiments in market.

NASDAQNews.py

import requests
from bs4 import BeautifulSoup
import csv
import pandas as pd


mostActiveStocksUrl = "https://www.nasdaq.com/markets/most-active.aspx"  
r = requests.get(mostActiveStocksUrl)
data = r.text
soup = BeautifulSoup(data)

table = soup.find_all('div', attrs = {'class': 'genTable'})
all_rows = table[1].find_all('tr')

symbols = []
names = []
last_sales = []
change_nets = []
share_volumes = []


for row in all_rows:
    cols = row.find_all('td')
    if len(cols):
        names.append(cols[1].text)
        last_sales.append(cols[2].text)
        change_nets.append(cols[3].text)
        share_volumes.append(cols[4].text)

data = pd.DataFrame(
    {'Names': names, 'Last Sale': last_sales, 'Chnange Net': change_nets,
     'Share Volume': share_volumes})
# print(data)

typo error fixed in line 2
syntax error line 7 fixed