Python for Finance, 3rd Edition

Chapter 4. Data Types and Structures

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Bad programmers worry about the code. Good programmers worry about data structures and their relationships.

Linus Torvalds

This chapter builds a modern foundation for working with Python’s core data types and containers. It shows how to choose between built-in types, avoid common pitfalls with mutability and copying, and write concise, readable transformations that prepare data for later chapters on NumPy, pandas, and beyond.

The chapter covers core scalars such as int, float, bool, and str; core containers such as list, tuple, dict, and set; concise transformations with comprehensions and unpacking; and copying fundamentals that help prevent subtle bugs. It also shows how Python’s dynamic typing works, how type hints document intent, where floating-point precision can surprise you, and when decimal is the safer tool.

To follow along, you need a working python 3.11+ interpreter (see Chapter 3) and basic shell skills to run short scripts. No external packages ...