Poker End-to-End Project on IRC Dataset

This project utilizes the IRC Poker dataset to analyze Poker hands from Holdem3 game files. It includes steps for data extraction, preparation, analysis, and building a predictive model.

Table of Contents

1. Setup
2. Project Workflow
   • Data Extraction
   • Data Preparation
   • Data Analysis
   • Model Building
3. Dependencies

Setup

1. Create a Virtual Environment
   Create a Python virtual environment to isolate project dependencies:

   python -m venv venv

2. Activate the Virtual Environment Activate the virtual environment and install all the dependencies

   source venv/bin/activate
   pip install -r requirements.txt

3. Run the Data Extractor Execute the extractor.py script to extract Poker hands data. After execution, a hands.json file will be created in the main directory:

   python extractor.py

Project Workflow

Data Extraction

The extractor.py script processes the Holdem3 game files and extracts Poker hands data, saving it in a hands.json file in the root directory.

Data Preparation

The data_preparation.ipynb notebook contains all necessary steps to convert the hands.json file into a .csv format. The key output is the data/holdem3.csv file, which will be used in subsequent steps.

Data Analysis

The data_analysis.ipynb notebook provides a detailed analysis of the participating players in Holdem3 game hands. Insights and patterns observed during the analysis are highlighted.

Model Building

The model_building.ipynb notebook covers feature engineering and the development of a LightGBM model. This model predicts whether a player will win during the turn stage of the game.

Dependencies

Ensure all the following dependencies are installed by using the requirements.txt file:

source venv/bin/activate
pip install -r requirements.txt