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Python Data Visualization Cookbook

You're reading from  Python Data Visualization Cookbook

Product type Book
Published in Nov 2013
Publisher Packt
ISBN-13 9781782163367
Pages 280 pages
Edition 1st Edition
Languages
Author (1):
Igor Milovanovic Igor Milovanovic
Profile icon Igor Milovanovic

Table of Contents (15) Chapters

Python Data Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Preparing Your Working Environment 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

Creating 3D histograms


Similar to 3D bars, we might want to create 3D histograms. They are used to easily spot correlation between three independent variables. They can be used to extract information from images where the third dimension could be the intensity of a channel in (x,y) space of the image under analysis.

In this recipe, we will learn how to create 3D histograms.

Getting ready

To recall, a histogram represents a number of occurrences of some value in a particular column (usually called "bin"). The three-dimensional histogram, then, represents a number of occurrences in a grid. This grid is rectangular, over two variables that are data in the two columns.

How to do it...

For this computation, we will:

  1. Use NumPy because it has the function to compute a histogram of two variables.

  2. Generate x and y from normal distributions but with different parameters to be able to distinct the correlation in the resulting histogram.

  3. Plot the scatter plot of the same dataset to demonstrate how different...

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