**Pandas:** total = df['amount'].sum(); top_users = df.groupby('user_id')['amount'].sum().nlargest(5); most_purchased = df['product_id'].value_counts().index[0].
**SQL:** SUM, GROUP BY + ORDER BY + LIMIT. For top-5: ROW_NUMBER() or RANK() OVER (PARTITION BY 1 ORDER BY total DESC).
**Scalability:** For Myntra-scale: run in warehouse (Snowflake/BigQuery)—push compute....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Myntra. The answer also includes follow-up discussion points that interviewers commonly explore.
Continue Reading the Full Answer
Unlock the complete expert answer with code examples, trade-offs, and pro tips - plus 1,863+ more.
Or upgrade to Platform Pro - $39
Engineers who used these answers got offers at
AmazonDatabricksSnowflakeGoogleMeta
According to DataEngPrep.tech, this is one of the most frequently asked Python/Coding interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.