Player Analysis Project

Overview

This project provides a comprehensive analysis tool for player performance in team-based ranked matches. It processes match data, calculates various statistics, and generates insightful visualizations to help understand a player's performance over time.

Features

• Data processing from parquet files
• Calculation of weekly and monthly statistics
• Generation of multiple performance graphs:
  • Weekly Matches Played
  • Skill and Match Rating Over Time
  • Weekly Skill Change
  • Weekly Wins and Losses
  • Match Rating Distribution
• HTML report generation with interactive Plotly graphs

Requirements

• Python 3.7+
• pandas
• plotly
• parquet

Usage

Run the main script to generate the analysis:

python main.py

This will create an HTML file named player_134300_analysis.html (or similar, depending on the player ID) in the project directory. Open this file in a web browser to view the complete analysis.

Project Structure

• main.py: The entry point of the application
• data.py: Contains functions for data loading and processing
• graphs.py: Handles the creation of Plotly graphs
• template.html: HTML template for the final report

Customization

To analyze a different player, modify the player_id variable in the generate_report() function in main.py.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is open source and available under the MIT License.