Data Types

Concepts covered: pyDataTypes

Every value in Python has a type that determines what operations you can perform on it. Understanding data types helps you work with different kinds of information correctly. Core Built-in Types Python has four fundamental types you will use constantly: strings for text, integers for whole numbers, floats for decimals, and booleans for true/false values. Choosing the right data type matters. Performing math on strings or logic on integers leads to unexpected results or errors.

About This Interactive Section

This section is part of the Python Foundations: Beginner 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.