Scrape data from website into dataframe(s) using Split function
Don't parse HTML manually, you should use the BeautifulSoup module!
import should be at the top of the file
Use a if __name__ == '__main__' guard
Functions and variable should be snake_case




First you can rewrite the getTable() alot using the BeautifulSoup module

import requests
from bs4 import BeautifulSoup

url = "http://webscraper.io/test-sites/tables"
soup = BeautifulSoup(requests.get(url).text, 'html.parser')
for table in soup.select('.table'):
    new_table = [[c.text for c in row.find_all('td')] for row in table.find_all('tr')]


The only problem is that it will also give back None values in the table, so we'd need to catch the None values and only yield when the list is not filled with None

Revised Code

import requests
import pandas as pd
from bs4 import BeautifulSoup

def parse_table(table):
    for row in table.find_all('tr'):
        col = [c.text for c in row.find_all('td')]
        if not all(c is None for c in col):
            yield col

def scrape_tables():
    url = "http://webscraper.io/test-sites/tables"
    soup = BeautifulSoup(requests.get(url).text, 'html.parser')
    for table in soup.select('.table'):
        parsed_table = [col for col in parse_table(table)]
        df = pd.DataFrame(parsed_table, columns=["#", "First Name", "Last Name", "User Name"])
        print()
        print(df)

if __name__ == '__main__':
    scrape_tables()