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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

Plotting with filled areas


In this recipe, we will show you how to fill the area under a curve or in between two different curves.

Getting ready

Library matplotlib allows us to fill areas in between and under the curves with color so that we can display the value of that area to the spectator. Sometimes, it is necessary for readers (viewers) to comprehend the given specialization.

How to do it...

Here's one example of how to fill areas between two contours:

from matplotlib.pyplot import figure, show, gca
import numpy as np

x = np.arange(0.0, 2, 0.01)

# two different signals are measured
y1 = np.sin(2*np.pi*x)
y2 = 1.2*np.sin(4*np.pi*x)

fig = figure()
ax = gca()

# plot and
# fill between y1 and y2 where a logical condition is met
ax.plot(x, y1, x, y2, color='black')

ax.fill_between(x, y1, y2, where=y2>=y1, facecolor='darkblue', interpolate=True)
ax.fill_between(x, y1, y2, where=y2<=y1, facecolor='deeppink', interpolate=True)

ax.set_title('filled between')

show()

How it works...

After...

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