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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

Generating controlled random datasets


In this recipe, we will show different ways of generating random number sequences and word sequences. Some of the examples use standard Python modules, and some use NumPy/SciPy functions.

We will go into some statistics terminology, but we will explain every term so you don't have to have a statistical reference book with you while reading this recipe.

We generate artificial datasets using common Python modules. By doing so, we are able to understand distributions, variance, sampling, and similar statistical terminology. More importantly, we can use this fake data as a way to understand if our statistical method is capable of discovering models we want to discover. We can do that because we know the model in advance and verify our statistical method by applying it over our known data. In real life, we don't have that ability and there is always a percentage of uncertainty that we must assume, giving way to errors.

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