The full problem statement is available to Pro members.
preloaded fixtures
import pandas as pd
import numpy as np
plays = pd.DataFrame({
"play_id": range(1, 13),
"user": ["u1", "u1", "u2", "u2", "u3", "u1", "u4", "u2", "u3", "u1", "u2", "u4"],
"artist": ["Nova Wave", "Nova Wave", "Nova Wave", "Maren Cruz", "The Quiet Hours", "Nova Wave",
"Maren Cruz", "Basement Theory", "The Quiet Hours", "Maren Cruz", "Nova Wave", "Nova Wave"],
"played_on": pd.to_datetime(["2024-01-05", "2024-01-05", "2024-01-06", "2024-01-06", "2024-01-07",
"2024-01-08", "2024-01-09", "2024-01-10", "2024-01-11", "2024-02-01",
"2024-02-02", "2024-02-03"]),
"ms_played": [215000, 50000, 200000, 196000, 240000, 215000, 100000, 178000, 300000, 196000, 215000, 215000],
})
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“Skip rate per user”
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Pro problem
“Skip rate 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