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Python Data Visualization Cookbook (Second Edition)

You're reading from   Python Data Visualization Cookbook (Second Edition) Visualize data using Python's most popular libraries

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781784396695
Length 302 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) Chapters Close

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 the Right Plots to Understand Data 8. More on matplotlib Gems 9. Visualizations on the Clouds with Plot.ly Index

Understanding spectrograms


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

It 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 like voice recognition to radar engineering and seismology.

Usually spectrogram layout is as following: x-axis represents time, y-axis represents frequency, and the third dimension is amplitude of a frequency-time pair, which is color coded. This is three-dimensional data, therefore, we can also create 3D plot where the intensity is represented as 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 auto fingerprint certain specific, but for this data visualization recipe we, will...

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