#### 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
Other Books You May Enjoy

# Creating interactive plots with Bokeh

Test statistics and numerical reasoning are good for systematically analyzing sets of data. However, they don't really give us a good picture of the whole set of data like a plot would. Numerical values are definitive but can be difficult to understand, especially in statistics, whereas a plot instantly illustrates differences between sets of data and trends. For this reason, there is a large number of libraries for plotting data in ever more creative ways. One particularly interesting package for producing plots of data is Bokeh, which allows us to create interactive plots in the browser by leveraging JavaScript libraries.

In this recipe, we will see how to use Bokeh to create an interactive plot that can be displayed in the browser.