What you’ll learn to build
- Read sales records and explain gross, fees and refunds
- Reconcile exact arithmetic by product and month
- Produce a self-contained dashboard with defensible metrics and tests
Who it’s for
Beginner-to-intermediate Python learners interested in analytics and evidence-based decisions. Start after running and modifying a small Python script.
Two focused lessons
- 01
Run and understand the working tool
- 02
Test, extend and document the workflow
Explore the curriculum topics
- Start with a decision, not a chart
- Inspect the transaction schema
- Gross revenue is not take-home income
- Refunds can make net negative
- Use Decimal for financial inputs
- Dates determine period grouping
- Product aggregation
- Monthly net receipts
- Orders are not unique customers
- Generate an offline dashboard
- Inspect product-level results
- Export machine-readable totals
- Milestone: reconcile by hand
- Data validity before aggregation
- Reject nonfinite or negative source values
- Refund conventions need documentation
- Filter reporting windows
- No mixed currencies
- Escaping user-provided product names
- Negative monthly bars
- Zero data is still a result
- Overwriting outputs deliberately
- Data privacy and access boundaries
- Test data pipeline math
- Explain limitations to a stakeholder
- Roadmap to business analytics
Project boundaries
Uses fictional, single-currency CSV input. Net receipts subtract fees and refunds before taxes and other expenses; they are not accounting profit. No Payhip or bank connection is included.