Book Image

Matplotlib for Python Developers - Second Edition

By : Aldrin Yim, Claire Chung, Allen Yu
Book Image

Matplotlib for Python Developers - Second Edition

By: Aldrin Yim, Claire Chung, Allen Yu

Overview of this book

Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library. Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you’ll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You’ll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you’ll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples. By the end of this book, you’ll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations.
Table of Contents (16 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

Chapter 4. Advanced Matplotlib

In previous chapters, we have learnt the versatile usage of basic Matplotlib APIs to create and customize various plot types. In order to create more suitable visuals for our data, there are more advanced techniques to make more refined figures. In fact, we can leverage not only the native Matplotlib functionalities but also a number of third-party packages built on top of Matplotlib. They provide easy ways to create more advanced plots that are also aesthetically styled by default. We can then make use of Matplotlib techniques to refine our data plots.

In this chapter, we would further explore the advanced usage of Matplotlib. We would learn how to group multiple relevant plots into subplots in one figure, using non-linear scale axis scales, plotting images, and creating advanced plots with the help of some popular third-party packages. Here are the detailed list of topics we would cover:

  • Drawing subplots
  • Using non-linear axis scales
  • Plotting images
  • Using Pandas...