The full problem statement is available to Pro members.
preloaded fixtures
import pandas as pd
import numpy as np
listings = pd.DataFrame({
"listing_id": [1, 2, 3, 4, 5, 6, 7, 8, 9],
"host": ["Mika", "Mika", "Kenji", "Kenji", "Aria", "Aria", "Lou", "Lou", "Sam"],
"city": ["SF", "SF", "Tokyo", "Tokyo", "SF", "Tokyo", "Paris", "Paris", "Berlin"],
"price": [120, 65, 200, 80, 150, 35, 110, 55, 90],
"nights_booked": [5, 1, 5, 0, 2, 4, 7, 0, 0],
})
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“Occupancy revenue per host”
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Pro problem
“Occupancy revenue per host”
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