🕸️ Web Scraping Project

Author: Sylvester Wanina Cybershujaa ID: CS-DA01-25087 Date: 2 February 2026

---

Overview

This script scrapes hockey team statistics from ScrapeThisSite, parses the HTML table using BeautifulSoup, loads the data into a Pandas DataFrame, and exports it to a CSV file.

---

Requirements

Make sure you have Python 3 installed, then install the required libraries:

pip install requests beautifulsoup4 pandas

---

How It Works

1. Fetch the page – Sends an HTTP GET request to the target URL.
2. Parse HTML – Uses BeautifulSoup to parse the page's HTML content.
3. Extract table data – Locates the HTML table, reads the column headers, and iterates over each row to collect the data.
4. Load into DataFrame – Stores the extracted data in a Pandas DataFrame for easy manipulation and viewing.
5. Export to CSV – Saves the final DataFrame to hockey_teams_data.csv in the working directory.

---

Usage

Run the script directly with Python:

python web_scraping.py

On success, you will see the column names and the first few rows printed to the console, and a file named hockey_teams_data.csv will be created in the same directory.

---

Output

File	Description
hockey_teams_data.csv	All scraped hockey team records in CSV format

---

Project Structure

.
├── web_scraping.py       # Main scraping script
├── hockey_teams_data.csv # Output file (generated on run)
└── README.md             # Project documentation

---

Notes

• The target site is a sandbox site designed for practicing web scraping, so no special permissions are required.
• The script skips the header row when extracting table rows to avoid including column names as data.
• Empty rows are filtered out automatically.