Chapter 4. Data Types and Structures

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

— Linus Torvalds

This chapter introduces basic data types and data structures of Python. Although the

Python interpreter itself already brings a rich variety of data structures with it, NumPy and

other libraries add to these in a valuable fashion.

The chapter is organized as follows:

Basic data types

The first section introduces basic data types such as int, float, and string.

Basic data structures

The next section introduces the fundamental data structures of Python (e.g., list

objects) and illustrates control structures, functional programming paradigms, and

anonymous functions.

NumPy data structures

The following section is devoted to the characteristics and capabilities of the NumPy

ndarray class and illustrates some of the benefits of this class for scientific and

financial applications.

Vectorization of code

As the final section illustrates, thanks to NumPy’s array class vectorized code is easily

implemented, leading to more compact and also better-performing code.

The spirit of this chapter is to provide a general introduction to Python specifics when it

comes to data types and structures. If you are equipped with a background from another

programing language, say C or Matlab, you should be able to easily grasp the differences

that Python usage might bring along. The topics introduced here are all important and

fundamental for the chapters to come.