Web Scraping with Python project showcasing how to extract, parse, and analyze data from websites using BeautifulSoup, Requests, and Selenium. A practical hands-on project for data collection, automation, and real-world analytics.
This project demonstrates web scraping techniques in Python to extract and analyze structured/unstructured data from websites. It is ideal for learning data collection, automation, and preprocessing for analytics or machine learning.
Features
Scraping static & dynamic websites Using Requests & BeautifulSoup for parsing Handling Selenium for dynamic content Export scraped data to CSV/Excel Automating scraping workflows
Dataset
Scraped datasets from various websites (blogs, e-commerce, and news portals).
Tech Stack
Python BeautifulSoup Requests Selenium Pandas
Usage
Clone the repo Install requirements using pip install -r requirements.txt Run Jupyter Notebooks or .py scripts to start scraping Export scraped data to CSV/Excel for further analysis
Learning Outcome
Learn how to scrape structured/unstructured web data Build custom data pipelines for projects Apply scraping in automation, ML training, and business insights