Nested Data Structures
Nested data structures are collections that contain other collections as their elements. This nesting can occur in multiple patterns: a list of dictionaries represents a table of records, similar to rows in a database. A dictionary with list values groups related items by category. A dictionary containing other dictionaries models hierarchical relationships like organizational structures or configuration settings. Understanding these patterns is essential because they mirror the structure of JSON data, database query results, and configuration files that you encounter daily in data engineering. The key insight is that Python allows any data structure to contain any other data structure. Lists can hold dictionaries, dictionaries can hold lists, and you can nest these combinations arbitraril
About This Interactive Section
This section is part of the Data Structures: Intermediate lesson on DataDriven, a free data engineering interview prep platform. Each section includes explanations, worked examples, and hands-on code challenges that execute in real time. SQL queries run against a live PostgreSQL database. Python runs in a sandboxed Docker container. Data modeling problems validate against interactive schema canvases. All content is framed around what data engineering interviewers actually test at companies like Meta, Google, Amazon, Netflix, Stripe, and Databricks.
How DataDriven Lessons Work
DataDriven combines four interview rounds (SQL, Python, Data Modeling, Pipeline Architecture) with adaptive difficulty and spaced repetition. Easy problems get harder as you improve. Weak concepts resurface until you master them. Your readiness score tracks progress across every topic interviewers test. Every lesson section ends with problems you solve by writing and running real code, not by picking multiple-choice answers.