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

Customizing matplotlib with style


The default style configuration of matplotlib is made to satisfy the requirements of a wide audience, but this means that we always have to spend some time customizing the details that we care about. In this recipe, we want to show how to create custom and reusable styles for matplotlib so that we make our changes only once.

Getting ready

All the styles that matplotlib can use are stored in a directory called stylelib, under the configuration directory of matplotlib. To check the path of this directory, we can use the get_configdir() method:

In [1]: import matplotlib

In [2]: matplotlib.get_configdir()
Out[2]: u'~/.matplotlib'

In this directory we will store the files that specify our custom styles.

How to do it...

First, we will create the file that contains all the specifications of our style:

axes.titlesize : 12
lines.linewidth : 2
xtick.labelsize : 8
ytick.labelsize : 8
figure.facecolor: white
figure.edgecolor: 555555
xtick.color: 555555

axes.color_cycle:...