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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

Understanding spectrograms


A spectrogram is a time-varying spectral representation that shows how the spectral density of a signal varies with time.

A spectrogram represents a spectrum of frequencies of the sound or other signal in a visual manner. It is used in various science fields, from sound fingerprinting such as voice recognition, to radar engineering and seismology.

Usually, a spectrogram layout is as follows: the x axis represents time, the y axis represents frequency, and the third dimension is the amplitude of a frequency-time pair, which is color coded. This is three-dimensional data; therefore, we can also create 3D plots where the intensity is represented as the height on the z axis. The problem with 3D charts is that humans are bad at understanding and comparing them. Also, they tend to take more space than 2D charts.

Getting ready

For serious signal processing, we would go into low-level details to be able to detect patterns and autofingerprint certain specifics; but for this...

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