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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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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

Creating 3D bars


Although matplotlib is mainly focused on plotting and mainly in two dimensions, there are different extensions that enable us to plot over geographical maps, to integrate more with Excel and plot in 3D. These extensions are called toolkits in the matplotlib world. Toolkit is a collection of specific function that focuses on one topic, such as plotting in 3D.

Popular toolkits are Basemap, GTK Tools, Excel Tools, Natgrid, AxesGrid, and mplot3d.

We will explore more of mplot3d in this recipe. The toolkit mpl_toolkits.mplot3d provides some basic 3D plotting. Plots supported are scatter, surf, line, and mesh. Although this is not the best 3D plotting library, it comes with matplotlib and we are already familiar with the interface.

Getting ready

Basically, we still need to create a figure and add desired axes to it. The difference is that we specify 3D projection for the figure, and the axes we add are Axes3D.

Now, we can use almost the same functions for plotting. Of course, what...

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