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

Making use of text and font properties


You already learned how to annotate the plot by adding legends, but sometimes we want more with text. This recipe will explain and demonstrate more features of text manipulation in matplotlib, giving a powerful toolkit for even advanced typesetting needs.

We will not cover LaTeX support in this recipe, as there is a recipe named Rendering text with LaTeX in this chapter.

Getting ready

We start with listing of the most useful set of functions that matplotlib offers. Most of the functions are available via pyplot module's interface, but we map their origin function here to allow you to explore more if a particular text feature is not covered in this recipe.

Basic text manipulations and their mapping in matplotlib OO API is presented in the following table:

matplotlib.pyplot

Matplotlib API

Description

text

matplotlib.axes.Axes.text

Adds text to the axes at the location specified by (x, y). Argument fontdict allows us to override generic font properties...