Quick Summary
- Chronologically rank each user's activity by distinct calendar months, ignoring gaps.
- Filter to the first and third active months to compare early versus sustained engagement.
- Aggregate ride ratings at the city level while preserving individual user timelines.
What This Tests
- Correctly partitioning window functions to maintain independent per-user sequences.
- Extracting and comparing date granularities to identify active periods.
- Ordering operations to filter ranked subsets before calculating group-level aggregates.
- Handling edge cases where users lack sufficient active months for comparison.
Common Patterns
Inner Join
Window Function
Ranking
Aggregation
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Test Cases
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