A Nice, Simple Web Scraping Code Golf Introduction
This is a web scraping Code Golf challenge that attempts to take stock Name and price columns from the 'Most Active' list on this New York Times URL.
Why is this challenge interesting?
Challenge:
Scrape these figures from this NYT page and turn it into a data frame using the smallest number of bytes possible (IE: import pandas as pd (should you choose to use Python) would give you a score of 19 (19 bytes). The data frame must be printed or returned as output.

Shortest Code by bytes wins the challenge. That's it!
Input:

import requests
from bs4 import BeautifulSoup
import pandas as pd

url='https://markets.on.nytimes.com/research/markets/overview/overview.asp'

def pull_active(url):
    # your code
    response = requests.get(url)
    if response.status_code == 200:
      print(&quot;Response Successful&quot;)
    else:
      print(&quot;Response Unsuccessful&quot;)
      return()
    bs_object = BeautifulSoup(response.content,'lxml')
    st_value = bs_object.find_all('td',class_='colPrimary')
    st_name = bs_object.find_all('a',class_=&quot;truncateMeTo1&quot;)
    x = []
    y = []
    for tag in st_name:
      x.append(tag.get_text())
    for tag in st_value:
      y.append(tag.get_text())
    data = {'Name': x[0:8],
            'Price': y[0:8]}
    df = pd.DataFrame(data)
    return(df)
pull_active(url)


Score: 773 bytes
To beat it, any code under 773 bytes.
Output:

  Name    Price
0 General Electric Co 10.11
1 Advanced Micro Devices Inc  33.13
2 PG&amp;E Corp   6.14
3 Fiat Chrysler Automobiles NV    14.98
4 Neuralstem Inc  1.83
5 AT&amp;T Inc    38.20
6 GrubHub Inc 34.00
7 Twitter Inc 29.86


...
Bash + lynx, 73
lynx -dump http://nyti.ms/2BY72Ph|grep -Po '\[(1[6-9]|2[0-3])]\K[^.]*...'

Output is as follows:
General Electric Co          10.11
Advanced Micro Devices Inc   33.13
PG&amp;E Corp                    6.14 
Fiat Chrysler Automobiles NV 14.98
Neuralstem Inc               1.83 
AT&amp;T Inc                     38.20
GrubHub Inc                  34.00
Twitter Inc                  29.86