Generate comprehensive README.md for IPL Data Analysis repository

[Copilot]

This PR adds a comprehensive README.md file that provides complete documentation for the IPL Data Analysis Using Apache PySpark project.

What's included:

📊 Project Overview

• Clear description of the project's purpose and scope
• Key features highlighting big data processing capabilities with 150,000+ records
• Technology stack overview (Apache PySpark, Python, Jupyter, Matplotlib/Seaborn)

📈 Dataset Documentation

• Detailed breakdown of all 5 CSV files with record counts and sizes
• Schema descriptions for ball-by-ball data, match information, player profiles, and team data
• Data relationships and structure explanation

🚀 Setup Instructions

• Complete installation guide with prerequisites
• Step-by-step setup process from cloning to running the analysis
• Quick start code examples for immediate use
• Memory configuration recommendations for optimal performance

🔍 Analysis Highlights

• Comprehensive overview of the analytical capabilities:
  • Player performance analysis (top batsmen, economical bowlers)
  • Team performance metrics (win/loss ratios, toss impact)
  • Match dynamics (powerplay analysis, venue trends)
  • Advanced analytics (window functions, aggregations, SQL queries)

📊 Technical Details

• Project structure documentation
• Configuration notes for different system setups
• Performance tuning recommendations
• File path management guidance

🤝 Community Features

• Contributing guidelines
• Development setup instructions
• Professional badges for technology stack
• Contact information and acknowledgments

The README provides everything needed for users to understand, set up, and contribute to this comprehensive cricket analytics project, making the repository more accessible and professional.

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