Implement a pivot table transformation
Company: Instacart
Role: Software Engineer
Category: Data Manipulation (SQL/Python)
Difficulty: Medium
Interview Round: Onsite
Given a dataset of transactions with columns: user_id (string), category (string), subcategory (string), amount (float), ts (ISO timestamp), implement a pivot table transformation:
(a) rows = category; columns = month (YYYY-MM derived from ts); values = sum(amount), filling missing cells with 0;
(b) rows = (user_id, category); columns = subcategory; values = count(*). Write a Python solution (pandas or pure Python), and outline an equivalent SQL approach. Discuss handling nulls, time zones, very large data (streaming/chunking), and limiting the number of columns (top-K with an OTHER bucket). State time and space complexity.
Quick Answer: This question evaluates competency in data transformation and aggregation, specifically pivot operations, time-based grouping, null handling, dimensionality reduction (top‑K/OTHER), scalability for large datasets, and expressing solutions in both Python (pandas or pure) and SQL within the Data Manipulation (SQL/Python) domain.