Worked on the RocketPy-Team/RocketPy repository to enhance Monte Carlo analysis capabilities, focusing on improving data visualization and uncertainty quantification. Developed new features using Python and Matplotlib, adding boxplots to existing histogram visualizations and expanding printed statistics to include the median and 95% prediction intervals. This approach provided users with clearer insights into simulation results, supporting more robust risk assessment and data-driven decision making. The work emphasized scientific computing best practices, enabling better interpretation of data distributions and uncertainty. Over the course of the month, delivered one feature that advanced the repository’s simulation analytics without introducing or addressing any bugs.