A Python-based simulation tool that models dice roll probability distributions and visualizes outcome frequencies.
This project was built to analyze and balance tabletop game mechanics by generating and aggregating large roll datasets.
It demonstrates data simulation, aggregation, and visualization workflows.
- Configurable dice roll simulation
- Large-scale roll dataset generation
- Frequency aggregation
- Statistical distribution analysis
- Graphical visualization of results
- Python
- Data aggregation logic
- Statistical analysis
- Matplotlib and Pandas
- Simulate a large number of dice rolls
- Store results in structured format
- Aggregate outcome frequencies
- Generate distribution visualizations
- Support for non-standard dice
- CSV file export
- Statistical comparison between roll strategies