3 SQL practice questions in our Lyft collection, part of our 188-question bank across 23 companies. Write SQL against practice datasets and get checked in your browser. Free, no card or trial.
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Identify VIP riders based on their lifetime spending and completed trip count. A VIP rider has accumulated at least $500 in total spend and completed at least 50 rides. Return rider_id, city_id, total_spend, completed_ride_count, and first_ride_date. This helps the business identify high-value customers.
Analyze active driver performance with current month average ratings and rolling 30-day trends. Return driver_id, city_id, current_month_avg_rating (March 2026), rolling_30d_avg_rating, and total_completed_rides_current_month. Include only drivers with at least 5 completed rides in the current month. This helps identify top performers and potential problem drivers.
Analyze ride completion rates across cities and time-of-day buckets. Bucket requests into morning (6-9 AM), midday (9 AM-5 PM), evening (5-9 PM), and night (9 PM-6 AM). Return city_id, time_bucket, total_requests, completed_rides, completion_rate, and rnk (rank within each city by completion rate, descending). Include only buckets with at least 100 requests. This helps identify when and where the service struggles.
3 Lyft problems, each with its own dataset. Click one and you’re in the workspace, free, right in your browser.
Your dataset
rider_id (INTEGER) · signup_date (DATE) · city_id (INTEGER) · is_active (BOOLEAN)
ride_id (INTEGER) · rider_id (INTEGER) · driver_id (INTEGER) · completed_date (DATE) · fare_usd (DECIMAL) · status (VARCHAR)
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Practice Lyft SQL free188 SQL practice questions. 23 companies. Free access to every problem.