The Month-by-Month Snapshot
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 sales records (each a dict with 'employee_id', 'month', 'sales_amount'), return a list of per-employee dicts. For each employee, spread their sales across keys named after each month they sold in, using the month's lowercased three-letter abbreviation (e.g. 'January' -> 'jan', 'February' -> 'feb') as the key and the total sales for that employee-month as the value. Sum the amounts when the same employee has multiple records in the same month. Each output dict also carries the 'employee_id' key. Within each dict, place the month keys first in alphabetical order, then 'employee_id' last. The list of employee dicts is sorted alphabetically by employee_id.
Summary
Every salesperson has a story. The months just tell it sideways.
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