Calculate rolling 7-day average per region

Last updated: December 29, 2025

Quick Overview

Write a query to compute rolling 7-day average grouped by user, handling edge cases like nulls and duplicates.

Coinbase
Data Manipulation (SQL/Python)
Data Scientist
Coinbase
December 29, 2025
Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Easy

84

7

2,932 solved


Write a query to compute rolling 7-day average grouped by user, handling edge cases like nulls and duplicates.

This question from Coinbase's Technical Screen tests practical data skills. The interviewer wants to see clean, efficient queries that handle edge cases like NULLs, duplicates, and large datasets.

What the Interviewer Expects
  • Write syntactically correct SQL with proper JOIN and WHERE clauses
  • Use GROUP BY and aggregate functions appropriately
  • Handle NULL values correctly in your queries
  • Explain the query execution plan at a high level
Key Topics to Cover
Pandas vectorized operations and groupby
JOIN types and when to use each
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Subqueries and correlated subqueries
Date/time manipulation
Index optimization and query performance
How to Approach This
  1. Clarify the schema and expected output format before writing queries.
  2. Use CTEs (WITH clauses) to break complex queries into readable steps.
  3. Consider window functions (ROW_NUMBER, RANK, LAG, LEAD) for ranking and sequential analysis.
  4. Watch for NULLs, duplicates, and edge cases in JOINs and GROUP BY.
  5. For pandas, prefer vectorized operations over row-by-row iteration.
Possible Follow-up Questions
  • What indexes would you create to support this query?
  • How would you validate the correctness of your query results?
  • How would you handle this if the data was spread across multiple databases?
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Sample Answer
Problem Understanding

The task requires calculating a rolling 7-day average of some metric (e.g., daily transactions or user activity) grouped by user and region. The dataset likely contains user activity records with colu...

Approach
  1. Select Relevant Data: Start by selecting the necessary columns from the activity records, ensuring to filter out any NULL values in activity_value.
  2. Create Date Range: Generate a date r...

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