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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

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 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
   Hello...
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