Book Image

Python Data Visualization Cookbook (Second Edition)

Book Image

Python Data Visualization Cookbook (Second Edition)

Overview of this book

Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that will guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts. Python Data Visualization Cookbook starts by showing how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how to build them. In the last chapter, it includes explanation on how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python.
Table of Contents (16 chapters)
Python Data Visualization Cookbook Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Index

Using subplots


If you are reading this book from the beginning, you are probably familiar with the subplot class, a descendant of axes that lives on the regular grid of subplot instances. We are going to explain and demonstrate how to use subplots in advanced ways.

In this recipe, you will be learning how to create custom subplot configurations on our plots.

Getting ready

The base class for subplots is matplotlib.axes.SubplotBase. These subplots are matplotlib.axes.Axes instances, but provide helper methods for generating and manipulating a set of Axes within a figure.

There is a class matplotlib.figure.SubplotParams, which holds all the parameters for subplot. The dimensions are normalized to the width or height of the figure. As we already know, if we don't specify any custom values, they will be read from the rc parameters.

The scripting layer (matplotlib.pyplot) holds a few helper methods to manipulate subplots.

matplotlib.pyplot.subplots is used for the easy creation of common layouts of...