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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

Making pie charts count


Pie charts are special in many ways, the most important being that the dataset they display must sum up to 100 percent or they are just plain not valid.

Getting ready

Pie charts represent numerical proportions, where the arc length of each segment is proportional to the quantity it represents.

They are compact, can look very aesthetically pleasing, but they have been criticized as they can be hard to compare. Another property of pie charts that does not work in their best interest is that pie charts are presented in a specific angle (perspective)—and segments use certain colors—that can skew our perception and influence our conclusion about information presented.

What we will show here is different ways to use pie charts to present data.

How to do it...

As a start, we create a so-called exploded pie chart:

from pylab import *

# make a square figure and axes
figure(1, figsize=(6,6))
ax = axes([0.1, 0.1, 0.8, 0.8])

# the slices will be ordered
# and plotted counter-clockwise...
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