I’m working on a small college software assignment that centres on data analysis with structured datasets pulled from spreadsheets and a simple SQLite database. The goal is to explore the numbers, surface meaningful trends, compare two related data sources, and wrap everything up in a concise set of insights that my classmates and I can easily understand. Here’s what I need from you: • Clean and prepare the structured data so it is ready for exploration. • Run exploratory analysis that highlights any notable trends or patterns. • Generate clear comparisons between the two datasets I’ll provide. • Summarise the key insights in both narrative form and a few easy-to-read charts. A short Jupyter Notebook (Python + pandas/NumPy/matplotlib or seaborn) or an R-Markdown file is perfect—whatever you feel most comfortable with as long as I can reproduce the steps. Include all code, comments, and the final visualisations in the notebook along with a brief written summary section. If anything is unclear, let me know up front; otherwise, I’m ready to hand over the files and get this mini-project rolling right away.