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Python Data Visualization Cookbook (Second Edition)

You're reading from  Python Data Visualization Cookbook (Second Edition)

Product type Book
Published in Nov 2015
Publisher
ISBN-13 9781784396695
Pages 302 pages
Edition 1st Edition
Languages

Table of Contents (16) Chapters

Python Data Visualization Cookbook Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface
Preparing Your Working Environment Knowing Your Data Drawing Your First Plots and Customizing Them More Plots and Customizations Making 3D Visualizations Plotting Charts with Images and Maps Using the Right Plots to Understand Data More on matplotlib Gems Visualizations on the Clouds with Plot.ly Index

Drawing polar plots


If the data is already represented using polar coordinates, we can also 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 decide 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 usually leads us to the best 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, you 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, we...

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