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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

What this book covers

Chapter 1, Preparing Your Working Environment, covers a set of installation recipes and advice on how to install the required Python packages and libraries on your platform.

Chapter 2, Knowing Your Data, introduces you to common data formats and how to read and write them, be it CSV, JSON, XSL, or relational databases.

Chapter 3, Drawing Your First Plots and Customizing Them, starts with drawing simple plots and covers some customization.

Chapter 4, More Plots and Customizations, follows up from the previous chapter and covers more advanced charts and grid customization.

Chapter 5, Making 3D Visualizations, covers three-dimensional data visualizations such as 3D bars, 3D histograms, and also matplotlib animations.

Chapter 6, Plotting Charts with Images and Maps, deals with image processing, projecting data onto maps, and creating CAPTCHA test images.

Chapter 7, Using Right Plots to Understand Data, covers explanations and recipes on some more advanced plotting techniques such as spectrograms and correlations.

Chapter 8, More on matplotlib Gems, covers a set of charts such as Gantt charts, box plots, and whisker plots, and it also explains how to use LaTeX for rendering text in matplotlib.

Chapter 9, Visualizations on the Clouds with Plot.ly, introduces how to use Plot.ly to create and share your visualizations on its cloud environment.

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