For my school project, I collected and organized data from various sources. Using Python and libraries like Pandas and NumPy, I cleaned and analyzed the data, identifying patterns and relationships. I applied statistical techniques, such as hypothesis testing and regression analysis, to extract meaningful insights and make predictions. Visualizations created with Matplotlib and Seaborn helped communicate the findings. In the end, I presented a comprehensive report summarizing the analysis process, key findings, and actionable recommendations. This project improved my Python skills, provided valuable experience in data analysis, and enhanced my ability to present findings effectively.