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Python Data Visualization Cookbook (Second Edition)

You're reading from   Python Data Visualization Cookbook (Second Edition) Visualize data using Python's most popular libraries

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781784396695
Length 302 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) Chapters Close

Preface 1. Preparing Your Working Environment FREE CHAPTER 2. Knowing Your Data 3. Drawing Your First Plots and Customizing Them 4. More Plots and Customizations 5. Making 3D Visualizations 6. Plotting Charts with Images and Maps 7. Using the Right Plots to Understand Data 8. More on matplotlib Gems 9. Visualizations on the Clouds with Plot.ly 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...

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