web scraping of webpage on chartink.com

Data indeed comes from a POST request. You don't need to allow JavaScript to run. You simply need to pick up one cookie (ci_session - which can be done using Session object to hold cookies from initial landing page request to pass on with subsequent POST), and one token (X-CSRF-TOKEN - which can be pulled from a meta tag in the initial request response):

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

data = {
  'scan_clause': '( {cash} ( monthly rsi( 14 ) > 60 and weekly rsi( 14 ) > 60 and latest rsi( 14 ) > 60 and 1 day ago  rsi( 14 ) <= 60 and latest volume > 100000 ) ) '
}

with requests.Session() as s:
    r = s.get('https://chartink.com/screener/time-pass-48')
    soup = bs(r.content, 'lxml')
    s.headers['X-CSRF-TOKEN'] = soup.select_one('[name=csrf-token]')['content']
    r = s.post('https://chartink.com/screener/process', data=data).json()
    #print(r.json())
    df = pd.DataFrame(r['data'])
    print(df)

You can access the table data by making a post request. You can have a look in the Chrome Dev Tools Network tab and see which elements are loading from elsewhere.

The data from the table is loading from https://chartink.com/screener/process post request (look at the 'process' name in the network tab). You can make a post request using the requests library as QHarr suggested.

Alternatively, you can achieve this without making things complicated by using requests-html library even though it will be much faster by getting data directly from the source, e.g. making a post request.

from requests_html import HTMLSession

session = HTMLSession()
response = session.get('https://chartink.com/screener/time-pass-48')
# renders javascript
response.html.render()

for result in response.html.xpath('//*[@id="DataTables_Table_0"]/tbody/tr'):
    print(f'{result.text}\n')

# part of the output:
'''
1
Kothari Products Limited
KOTHARIPRO
P&F | F.A
19.96%
106.7
262,997
'''

And from there all needs to be done is to split() elements and get the desired element (index), e.g:

for result in response.html.xpath('//*[@id="DataTables_Table_0"]/tbody/tr'):
    # getting text data, splitting by a new line and grabbing first index [1]
    # the process is the same for every other column
    stock_name = result.text.split('\n')[1]
    print(stock_name)

# part of the output:
'''
Kothari Products Limited
STEELXIND
Oswal Chemicals & Fertilizers Limited
Hbl Power Systems Limited
'''

import requests
import bs4
page = requests.get("https://chartink.com/screener/time-pass-48")
bs4.BeautifulSoup(page.text,'lxml')

I think this should do it.