2..2.1. Web Scraping with BeautifulSoup:

• Identify a website with tabular data (e.g., a Wikipedia table).

• Use BeautifulSoup to scrape the data and store it in a DataFrame.

• Display the first few rows of the DataFrame.

Program 1:

Step 1: Install Required Libraries 

pip install requests beautifulsoup4 pandas

from bs4 import BeautifulSoup

import requests

# Send a request to fetch the web page content

url = "https://example.com"

response = requests.get(url)

# Parse the HTML content

soup = BeautifulSoup(response.content, "html.parser")

# Find and print all the links in the page

for link in soup.find_all('a'):

    print(link.get('href'))

Expected Output

Explanation:

1. Requests to Fetch Webpage Content:

   • The requests library is used to send a GET request to the URL of the Wikipedia page containing the table.

2. Parsing HTML with BeautifulSoup:

   • The response content is parsed using BeautifulSoup with the 'html.parser' option.