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Python Data Visualization Cookbook

You're reading from   Python Data Visualization Cookbook As a developer with knowledge of Python you are already in a great position to start using data visualization. This superb cookbook shows you how in plain language and practical recipes, culminating with 3D animations.

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Product type Paperback
Published in Nov 2013
Publisher Packt
ISBN-13 9781782163367
Length 280 pages
Edition 1st Edition
Languages
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Author (1):
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Igor Milovanovic Igor Milovanovic
Author Profile Icon Igor Milovanovic
Igor Milovanovic
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Toc

Table of Contents (15) Chapters Close

Python Data Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
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 Right Plots to Understand Data 8. More on matplotlib Gems Index

Rendering text with LaTeX


If we want to plot more scientific graphics and explain math as it should be using scientific notations and complex equations on the figures, we need support from the best.

Although matplotlib has support for math text rendering, the best support comes from the LaTeX community, proven in the task being used for many decades.

LaTeX is a high-quality typesetting system for the production of scientific and technical documentation, being a de facto standard for scientific typesetting or publication. It is a free software, available on the majority of desktop platforms used today as prepackages binary installation; hence, it is easy to install.

The basic syntax of LaTeX is similar to markup languages; so to produce satisfactory content, one would write focusing more on the structure than on the look and style. For example:

\documentclass{article}
\title{This here is a title of my document}
\author{Peter J. S. Smith}
\date{September 2013}
\begin{document}
   \maketitle
 ...
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