script.py

#import the Beautiful soup functions to parse the data returned from the website
from bs4 import BeautifulSoup
# Import pandas to make data tables and to import it to CSV
import pandas as pd
#import the library used to query a website
import urllib.request
class AppURLopener(urllib.request.FancyURLopener):
    version = "Mozilla/5.0"
x = 1
while x == 1:
    #specify the url
    website = "https://www.google.com/covid19-map/"
    #Query the website and return the html to the variable 'page'
    page = AppURLopener().open(website) 

    #Parse the html in the 'page' variable, and store it in Beautiful Soup format
    soup = BeautifulSoup(page, 'html.parser')

    # print(soup.title)

    all_tables = soup.find_all('table', class_='SAGQRd')

    right_table = all_tables[0]

    rows = right_table.findAll("tr")
    
    datas = rows[1].findAll("td")

    #print('Confirmed Cases : ' + datas[1].string)
    #print('Recovered : ' + datas[3].string)
    #print('Deaths : ' + datas[4].string)

    # make a table from the data
    stat = pd.DataFrame(
        {
            'Confirmed Cases': [datas[1].string],
            'Recovered':  [datas[3].string],
            'Deaths': [datas[4].string],
        }
    )

    print(stat)

    html = (stat.to_html())
    # Export the table to csv
    stat.to_csv('stats.csv')

    # Export the table to HTML
    stat.to_html('stats.html')

    print(html)