The full problem statement is available to Pro members.
preloaded fixtures
import pandas as pd
import numpy as np
watch_events = pd.DataFrame({
"event_id": range(1, 13),
"user": ["alice", "bob", "alice", "carol", "bob", "alice", "carol", "dave", "bob", "carol", "dave", "alice"],
"genre": ["drama", "comedy", "drama", "docs", "comedy", "thriller", "docs", "drama", "comedy", "thriller", "drama", "drama"],
"watch_date": pd.to_datetime(["2024-01-05", "2024-01-06", "2024-01-10", "2024-01-12", "2024-01-15", "2024-01-20", "2024-02-01", "2024-02-03", "2024-02-10", "2024-02-15", "2024-02-20", "2024-02-28"]),
"minutes": [45, 30, 60, 20, 25, 50, 15, 55, 40, 35, 60, 50],
})
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“Average session length per user”
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Pro problem
“Average session length per user”
This is one of the real interview questions in Pro. Try Pro free for 7 days to unlock it and everything below:
- 293 interview-grade problems across SQL, Python & pandas
- 104+ real-world SQL problems: SaaS retention, fintech ledgers, supply chain, recursive CTEs
- 18 company interview packs (Amazon, Meta, Google, Uber and more)
- AI "explain my mistake" tutor and mock interviews
- Use QueryLab inside Claude, Cursor & other AI assistants
// built for real interview rounds
Practice the patterns 18 top companies test
329 problems · 36 free forever · 293 unlocked with Pro
Card required. Then $12/month. Cancel before your trial ends and you pay nothing.
or keep practicing free problems →Secure checkout by Paddle · instant access · cancel anytime from your account