As explained at the start of this chapter, Matplotlib was not originally designed for making animations, and there are GPU-accelerated Python animation packages that may be more suitable for such a task (such as PyGame). However, since we are already familiar with Matplotlib, it is quite easy to adapt existing plots to animations.
Matplotlib 2.x By Example
By :
Matplotlib 2.x By Example
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Overview of this book
Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization.
Matplotlib 2.x By Example illustrates
the methods and applications of various plot types through real world examples.
It begins by giving readers the basic
know-how on how to create and
customize plots by Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize geographical data on maps and implement interactive charts.
By the end of this book, you will become well versed with Matplotlib in your day-to-day work to perform advanced data visualization. This book will guide you to prepare high quality figures for manuscripts and presentations. You will learn to create intuitive info-graphics and reshaping your message crisply understandable.
Table of Contents (9 chapters)
Preface
Free Chapter
Hello Plotting World!
Figure Aesthetics
Figure Layout and Annotations
Visualizing Online Data
Visualizing Multivariate Data
Adding Interactivity and Animating Plots
A Practical Guide to Scientific Plotting
Exploratory Data Analytics and Infographics
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