The full problem statement is available to Pro members.
preloaded fixtures
import pandas as pd
import numpy as np
sales = pd.DataFrame({
"order_id": [1, 2, 3, 4, 5, 6, 7, 8],
"customer": ["ada", "grace", "ada", "alan", "grace", "marie", "alan", "ada"],
"country": ["UK", "USA", "UK", "UK", "USA", "France", "UK", "UK"],
"category": ["hardware", "audio", "audio", "furniture", "hardware", "audio", "hardware", "furniture"],
"units": [1, 2, 1, 3, 1, 2, 4, 1],
"price": [129.0, 249.99, 199.0, 420.0, 329.5, 249.99, 59.0, 540.0],
"rating": [4.5, np.nan, 3.0, 5.0, np.nan, 4.0, 4.5, 2.5],
})
customers = pd.DataFrame({
"customer": ["ada", "grace", "alan", "hedy"],
"segment": ["pro", "pro", "starter", "starter"],
})
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“Share of revenue per customer”
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Pro problem
“Share of revenue per customer”
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