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: Find and print all the links in the page

Program 2: Identify a website with tabular data (e.g., a Wikipedia table).

Program 3: Find and print all article titles 

Program 4: 1. Parsing a Simple HTML Document 

Program 5:  Finding Elements by Tag 

Program 6:  Finding an Element by Class Name 

Program 7:  Extracting Attributes from a Tag 

Program 8:  Navigating HTML with Parent and Sibling Relationships 

Step 1: Install Required Libraries 

pip install requests beautifulsoup4 pandas

Step 2: Write the Python Code import requests

from bs4 import BeautifulSoup

import pandas as pd

import requests

# Step 1: Identify the URL of the website with tabular data

url = "https://en.wikipedia.org/wiki/List_of_countries_and_dependencies_by_population"

# Step 2: Send a request to fetch the webpage content

response = requests.get(url)

# Step 3: Parse the webpage content using BeautifulSoup

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

# Step 4: Locate the table you want to scrape (use inspect tool to find the right table)

table = soup.find('table', {'class': 'wikitable'})