Living alone and ordering groceries online every week, I kept wondering where is my money actually going? Are my subscriptions worth it? Do I overspend in certain seasons?
I used a real consumer transactions dataset and asked it the exact questions I ask myself every month about my own wallet.
| # | Question | SQL Concept Used |
|---|---|---|
| Q1 | Which categories consume the most money? | GROUP BY + Window SUM |
| Q2 | Which expenses are recurring? | CASE + COUNT thresholds |
| Q3 | Which categories are growing? | CTE + PARTITION BY |
| Q4 | What is my seasonal spending premium? | Window AVG vs overall AVG |
| Q5 | Which subscriptions have low satisfaction? | WHERE + HAVING + CASE |
| Q6 | What % is discretionary vs essential? | CASE bucket + Window SUM |
- SQL — DuckDB (analytical SQL, window functions, CTEs)
- Python — Pandas for data loading
- Visualization — Matplotlib
- Notebook — Kaggle
[Fill in your Q1 top category] was the biggest budget drain [Fill in top recurring item] was the most autopilot purchase [Fill in growing category] showed consistent seasonal growth [Fill in high season] had the highest spending premium [Fill in cancel candidate item] scored lowest on satisfaction Discretionary spending = [fill in]% of total budget
Customer Shopping Trends Dataset by iamsouravbanerjee on Kaggle