#### Overview of this book

Python, one of the world's most popular programming languages, has a number of powerful packages to help you tackle complex mathematical problems in a simple and efficient way. These core capabilities help programmers pave the way for building exciting applications in various domains, such as machine learning and data science, using knowledge in the computational mathematics domain. The book teaches you how to solve problems faced in a wide variety of mathematical fields, including calculus, probability, statistics and data science, graph theory, optimization, and geometry. You'll start by developing core skills and learning about packages covered in Python’s scientific stack, including NumPy, SciPy, and Matplotlib. As you advance, you'll get to grips with more advanced topics of calculus, probability, and networks (graph theory). After you gain a solid understanding of these topics, you'll discover Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code. By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science.
Preface
Basic Packages, Functions, and Concepts
Free Chapter
Mathematical Plotting with Matplotlib
Working with Randomness and Probability
Geometric Problems
Finding Optimal Solutions
Miscellaneous Topics
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# Visualizing two-dimensional geometric shapes

The focus of this chapter is on two-dimensional geometry, so our first task is to learn how to visualize two-dimensional geometric figures. Some of the techniques and tools mentioned here might be applicable to three-dimensional geometric figures, but generally, this will require more specialized packages and tools.

A geometric figure, at least in the context of this book, is any point, line, curve, or closed region (including the boundary) whose boundary is a collection of lines and curves. Simple examples include points and lines (obviously), rectangles, polygons, and circles.

In this recipe, we will learn how to visualize geometric figures using Matplotlib.