The Column Transformer
A easy Python mock interview question on DataDriven. Practice with AI-powered feedback, real code execution, and a hire/no-hire decision.
- Domain
- Python
- Difficulty
- easy
- Seniority
- L3
Interview Prompt
An ETL step ships its per-column transforms as configuration: `transforms` maps a column name to a string of Python lambda source such as `'lambda x: x.upper()'`, while `rows` is a list of same-keyed dicts. Turn each source string into a callable and apply it to that column's value in every row, returning new rows with the untransformed columns and each row's key order intact and the input rows left unmodified.
Summary
Each column gets its function.
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