📚 BookMiner

BookMiner is a data pipeline project that scrapes book data from web pages, stores the raw HTML, processes and combines the data, and performs exploratory data analysis (EDA) to derive insights.

🚀 Project Workflow

1. Web Scraping
   Scrapes book listings from online pages and stores the HTML files.

2. Data Extraction & Storage
   Parses and combines data from multiple HTML pages into a single structured CSV file.

3. Exploratory Data Analysis (EDA)
   Performs visual and statistical analysis to uncover patterns in book pricing, ratings, value scores, and more.

📁 Project Structure

├── 1_scraping.ipynb        # Scrapes book data and stores HTML files
├── 2_EDA.ipynb             # Performs EDA on the combined CSV data
├── DATA.csv                # Cleaned and structured dataset
├── README.md               # Project overview and instructions
├── HTMLs                   # All scraped pages from website

📊 Sample Insights

• Price distribution of books
• Correlation between rating and value score
• Most common price ranges for high-rated books

🛠️ Tools & Libraries

• Python (BeautifulSoup, Requests, Pandas)
• Jupyter Notebook
• Matplotlib, Seaborn for visualization

📌 Getting Started

1. Clone the repo:

git clone https://github.com/your-username/BookMiner.git
cd BookMiner

2. Run the notebooks in order:
   • 1_scraping.ipynb
   • 2_EDA.ipynb

📃 License

This project is for educational and non-commercial use.

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Made with ❤️ for data and books.