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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

Drawing polar plots


If the data is already represented using polar coordinates, we can as well display it using polar figures. Even if the data is not in polar coordinates, we should consider converting it to polar form and draw on polar plots.

To answer whether we want to do this, we need to understand what the data represents and what we are hoping to display to the end user. Imagining what the user will read and decode from our figures leads us usually to the best of visualizations.

Polar plots are commonly used to display information that is radial in nature. For example, in sun path diagrams—we see the sky in radial projection, and the radiation maps of antennas radiate differently at different angles. You can learn more about this at: http://www.astronwireless.com/topic-archives-antenna-radiation-patterns.asp.

In this recipe, we will learn how to change the coordinate system used in the plot and to use the polar coordinate system instead.

Getting ready

To display data in polar coordinates...

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