Quick Overview

This question evaluates SQL competencies in aggregation, filtering, joins, numeric formatting, and precise date-based age calculation, including handling NULL fares, canceled trips, leap-year birthdays, and boundary-age cases.

Write SQL for fares and age-band counts

Company: Uber

Role: Data Scientist

Category: Data Manipulation (SQL/Python)

Difficulty: medium

Interview Round: Technical Screen

You have two tables. Schema: - drivers(driver_id VARCHAR PRIMARY KEY, name VARCHAR, date_of_birth DATE) - trips(trip_id VARCHAR PRIMARY KEY, driver_id VARCHAR, trip_date DATE, trip_fare_dollars DECIMAL(10,2), trip_status VARCHAR) Sample data: drivers | driver_id | name | date_of_birth | |-----------|----------|---------------| | D1 | Jane Doe | 1996-03-14 | | D2 | Mark S | 1963-09-16 | | D3 | Adam L | 1965-05-19 | | D4 | Jaime L | 1976-05-19 | trips | trip_id | driver_id | trip_date | trip_fare_dollars | trip_status | |---------|-----------|------------|-------------------|-------------| | T1 | D1 | 2019-01-01 | 17.52 | completed | | T2 | D1 | 2019-01-02 | 4.40 | completed | | T3 | D1 | 2019-01-03 | NULL | canceled | | T4 | D2 | 2019-01-01 | 25.00 | completed | | T5 | D3 | 2019-01-01 | 8.00 | completed | | T7 | D2 | 2019-01-02 | NULL | canceled | Write SQL (one query or two CTEs is fine) to: (a) Return driver names whose average fare over completed trips is strictly greater than 10.00. Exclude non-completed trips and rows where trip_fare_dollars IS NULL. Output columns: driver_name, avg_fare_2dp (rounded to 2 decimals). Order by avg_fare_2dp DESC, then driver_name ASC. Drivers with zero completed trips must not appear. (b) Count completed trips by driver age bands as of 2025-09-01. Use inclusive boundaries for bands: 20–35 and 36–45 (i.e., ages in [20,35] and [36,45]). Compute age from date_of_birth accurately (no 365-day approximation). Output two rows with columns: age_band ('20-35' or '36-45'), total_completed_trips. Ignore drivers outside 20–45. Edge cases to handle: null fares, canceled trips, drivers without completed trips, leap-year birthdays, and band boundary birthdays on 2025-09-01.

Overview: This question evaluates SQL competencies in aggregation, filtering, joins, numeric formatting, and precise date-based age calculation, including handling NULL fares, canceled trips, leap-year birthdays, and boundary-age cases.

Drivers with average completed-trip fare > $10

You are given two tables: drivers and trips. Write a SQL query to return driver names whose average fare over completed trips is strictly greater than 10.00. Rules: - Only include trips where trip_status = 'completed'. - Exclude rows where trip_fare_dollars IS NULL. - Drivers with zero qualifying completed trips must not appear. Output columns: - driver_name - avg_fare_2dp (average fare rounded to 2 decimals) Sort by avg_fare_2dp DESC, then driver_name ASC.

Tables

drivers(driver_id VARCHAR(10), name VARCHAR(100), date_of_birth DATE)

trips(trip_id VARCHAR(10), driver_id VARCHAR(10), trip_date DATE, trip_fare_dollars DECIMAL(10,2), trip_status VARCHAR(20))

Hints

  1. Filter to completed trips and non-NULL fares before aggregating.
  2. Use HAVING for the average-fare threshold after GROUP BY.

Completed trip counts by age band as of 2025-09-01

Using the same drivers and trips tables, count completed trips by driver age bands as of 2025-09-01. Requirements: - Compute age from date_of_birth accurately (do not approximate using 365 days). - Use inclusive age bands: 20–35 and 36–45. - Ignore drivers outside ages 20–45. - Count trips where trip_status = 'completed' (fares may be NULL; still count the trip). - Output exactly two rows for the age bands, even if a band has 0 trips. Output columns: - age_band (either '20-35' or '36-45') - total_completed_trips

Tables

drivers(driver_id VARCHAR(10), name VARCHAR(100), date_of_birth DATE)

trips(trip_id VARCHAR(10), driver_id VARCHAR(10), trip_date DATE, trip_fare_dollars DECIMAL(10,2), trip_status VARCHAR(20))

Hints

  1. To compute accurate age in years, subtract 1 when the birthday in the reference year has not occurred yet.
  2. To guarantee both bands appear, build a two-row "bands" CTE and LEFT JOIN the computed counts.

Community answers

Answer by SS

Part(a) WITH filtered AS ( SELECT driver_id, ROUND(AVG(trip_fare_dollars), 2) AS avg_fare_2dp FROM trips WHERE trip_fare_dollars IS NOT NULL AND trip_status = 'completed' GROUP BY driver_id HAVING AVG(trip_fare_dollars) > 10 ) SELECT d.name AS driver_name, f.avg_fare_2dp FROM filtered f INNER JOIN drivers d ON f.driver_id = d.driver_id ORDER BY f.avg_fare_2dp DESC, d.name ASC; Part(b) WITH driver_ages AS ( SELECT driver_id, EXTRACT(YEAR FROM DATE '2025-09-01') - EXTRACT(YEAR FROM date_of_birth) - CASE WHEN EXTRACT(MONTH FROM date_of_birth) > EXTRACT(MONTH FROM DATE '2025-09-01') THEN 1 WHEN EXTRACT(MONTH FROM date_of_birth) = EXTRACT(MONTH FROM DATE '2025-09-01') AND EXTRACT(DAY FROM date_of_birth) > EXTRACT(DAY FROM DATE '2025-09-01') THEN 1 ELSE 0 END AS age FROM drivers ), age_bands AS ( SELECT driver_id, CASE WHEN age BETWEEN 20 AND 35 THEN '20-35' WHEN age BETWEEN 36 AND 45 THEN '36-45' END AS age_band FROM driver_ages WHERE age BETWEEN 20 AND 45 ) SELECT ab.age_band, COUNT(t.trip_id) AS total_completed_trips FROM age_bands ab INNER JOIN trips t ON ab.driver_id = t.driver_id WHERE t.trip_status = 'completed' GROUP BY ab.age_band ORDER BY ab.age_band;

Loading coding console...