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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 histograms


Histograms are simple, yet it's important to get the right data into them. We will cover histograms in 2D for now.

Histograms are used to visualize estimations of distribution of data. Generally, we use a few terms when speaking of histograms. Vertical rectangles represent frequencies of data points within a particular interval, called a bin. Bins are created at fixed intervals so the total area of a histogram equals the number of data points.

Instead of using absolute values of data, histograms can display relative frequencies of data. When this is the case, the total area equals 1.

Histograms are often used in image manipulation software as a way to visualize image properties, such as distribution of light in a particular color channel. Further, these image histograms can be used in computer vision algorithms to detect peaks aiding in edge detections, image segmentation, and so on.

In Chapter 5, Making 3D Visualizations, we have recipes that deal with 3D histograms.

Getting...

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