Analyze Hourly Distance and Airport Trips

# Analyze Hourly Distance and Airport Trips Use green-taxi trip records to answer two analytical questions. The source does not define one output table, an airport boundary, a fare field, or ordering rules. State those choices explicitly and treat the result as a documented analysis rather than a fixed SQL-console relation. ### Clarifying Questions to Ask - Which timestamp determines hour of day, and in which timezone? - What spatial rule identifies an airport origin or destination? - Which fare measure is intended, and how should invalid or incomplete trips be handled? ### Part 1 — Distance by Hour Report mean and median trip distance grouped by hour of day, with data-quality and sample-size context. #### What This Part Should Cover - A defined timestamp, 24-hour grouping, null policy, and trip eligibility rule. - Counts alongside mean and median so sparse or skewed groups are visible. ### Part 2 — Airport-Related Trips Define a reproducible airport-trip criterion, then report the exact count, average chosen fare measure, and other characteristics that help explain how these trips differ. #### What This Part Should Cover - A defensible spatial classification and treatment of boundary uncertainty. - Counts, fare summary, useful comparisons, and stated limitations. ```hint Audit the classification before aggregating Inspect trips just inside and outside each airport boundary and quantify missing coordinates. ``` ### What a Strong Answer Covers - Explicit definitions instead of hidden assumptions. - Robust treatment of skew, invalid records, and incomplete observation. - Reproducible calculations with interpretation separated from fact. ### Follow-up Questions - How would median distance change the story relative to mean distance? - How would you validate airport classification without a trusted zone label?