The Pandas Pivot
A medium Python mock interview question on DataDriven. Practice with AI-powered feedback, real code execution, and a hire/no-hire decision.
- Domain
- Python
- Difficulty
- medium
- Seniority
- L4
Interview Prompt
Given a list of event dicts (each with 'user_id', 'event_type', 'amount'), pivot so each user becomes one dict containing one column per distinct event_type (whose value is the sum of that user's amounts for that event_type) plus a final 'user_id' column. Only include event_type columns the user actually has (a sparse pivot; missing event_types are simply absent). Within each user's dict, place the event_type columns first, ordered by descending summed amount, and put 'user_id' last. Return the list of per-user dicts sorted by user_id ascending.
Summary
Rows become columns. Columns become power.
How This Interview Works
- Read the vague prompt (just like a real interview)
- Ask clarifying questions to the AI interviewer
- Write your python solution with real code execution
- Get instant feedback and a hire/no-hire decision