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Mastering matplotlib

You're reading from  Mastering matplotlib

Product type Book
Published in Jun 2015
Publisher
ISBN-13 9781783987542
Pages 292 pages
Edition 1st Edition
Languages
Authors (2):
Duncan M. McGreggor Duncan M. McGreggor
Profile icon Duncan M. McGreggor
Duncan M McGreggor Duncan M McGreggor
Profile icon Duncan M McGreggor
View More author details

Table of Contents (16) Chapters

Mastering matplotlib
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Getting Up to Speed 2. The matplotlib Architecture 3. matplotlib APIs and Integrations 4. Event Handling and Interactive Plots 5. High-level Plotting and Data Analysis 6. Customization and Configuration 7. Deploying matplotlib in Cloud Environments 8. matplotlib and Big Data 9. Clustering for matplotlib Index

High-level plotting


In this book, when we mention high-level, we are referring not to some assessment of value or improvement over something, but rather to layers of abstraction, or more precisely, layers of interaction. When engaged in high-level plotting, we expect that users and developers will be creating visualizations of complex data with fewer commands or steps required than by using matplotlib's basic functionality directly. This is a result of complex tasks wrapping a greater number of smaller, simpler tasks.

Plotting itself is a high-level activity: raw data and often calculations on that data are combined, processed, some more in anticipation of user consumption, arranged or grouped in ways suitable for conveying the desired information, and then applied to some medium in ways that one hopes will render greater insight. By our definition, each activity upon that original raw data is, in some way, high-level.

Before we look at examples of modern high-level plotting, let us gain some...

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