Why These 25?
Hand-curated for maximum interview ROI.
Multi-FK Industry Schemas
Every problem composes 2–4 merges across the same kind of 8–15 table relational structures you’d see at a Stripe, Airbnb, or Uber. Not toy 2-DataFrame examples — actual multi-table joins.
The Real Merge Failure Modes
Row explosion from many-to-many joins. Silent column overrides. Indexes-don’t-match. The traps that crash production pipelines but get ignored in tutorials — you see them, feel them, and learn to spot them in your own code.
Anti-Merge → Feature-Matrix Capstones
Stage 4 drills the canonical anti-merge (indicator=True + filter _merge=='left_only') — the pandas equivalent of LEFT JOIN + IS NULL. Stage 5 then chains 4–5 merges with classification and feature engineering into production-grade feature matrices.
Skill Coverage
How the 25 problems distribute across pandas topics.
FAQ
Helpful but not required.
If you can write basic boolean filtering (df[df[col]==X]), start here.
Stage 1 begins with the simplest 2-table inner merge.
Ready to Master Pandas?
Start with Stage 1 — graded instantly in your browser.
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