Calculate percentile rank per date

Last updated: April 4, 2026

Quick Overview

Write a query to compute percentile rank grouped by date, handling edge cases like nulls and duplicates.

Dropbox
Data Manipulation (SQL/Python)
Data Scientist
Dropbox
April 4, 2026
Data Scientist
Take-home Project
Data Manipulation (SQL/Python)
Easy

17

6

2,742 solved


Write a query to compute percentile rank grouped by date, handling edge cases like nulls and duplicates.

This question from Dropbox's Take-home Project 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
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
JOIN types and when to use each
Aggregate functions and GROUP BY
Index optimization and query performance
Common Table Expressions (CTEs)
Subqueries and correlated subqueries
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
  • How would you validate the correctness of your query results?
  • How would you optimize this query for a table with 100 million rows?
  • How would you handle slowly changing dimensions in this scenario?
  • Can you rewrite this without using subqueries?
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Practice SQL Problems
Sample Answer
Approach

Break the problem into logical steps before writing SQL. Think about: 1. What tables do I need to join and on which keys? 2. What filtering (WHERE) d...

Solution Pattern

```sql WITH filtered_data AS ( SELECT * FROM main_table WHERE condition = 'value' AND date_col >= '2024-01-01' ), aggregated AS ( SELECT ...


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