📊 Exploratory Data Analysis (EDA) of Python Programming Books Project Overview This project focuses on analyzing the global market for Python programming literature. By using the Open Library API, we collected and analyzed data on over 2,000+ books to understand the factors that drive a book's success, longevity, and global reach.

✨ Key Conclusions

The Python Boom: Our analysis shows a massive spike in Python resources over the last decade, mirroring Python’s dominance in Data Science and AI.

The Power of "Classics": We found that foundational books maintain authority through multiple editions and high digital availability.

Global Language Driver: There is a 0.83 correlation between English availability and a book’s total edition count, proving English is the gateway to global scalability.

Quality is Evergreen: User ratings show that high-quality technical content remains relevant regardless of the publication year.

🛠️ Tech Stack Language: Python

Libraries: Pandas, NumPy, Matplotlib, Seaborn

Data Source: Open Library API (Web Scraping & API Extraction)

👥 The Team This project was a collaborative effort by:

Saraswathi K * Pragna Nerela