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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

matplotlib in other frameworks


In general, third-party libraries that depend on or provide support to the process of interfacing with matplotlib do so mostly through the scripting layer. Here is a quick summary of a few libraries that use matplotlib:

  • Seaborn: This library uses all the matplotlib.pyplot functions.

  • NetworkX: This library essentially uses all the matplotlib.pyplot functions, with the only exception being some backend and artist layer interfacing that is used to generate the project's gallery (which is another good example of the programmatic approach for batched jobs).

  • Pandas: This library mostly uses matplotlib.pyplot, but it sometimes also uses the deprecated pylab interface. It also has some custom transforms and tickers in its time series converter code.

  • scikit-learn: This library mostly uses matplotlib.pyplot along with some custom use of the font manager and color mapping. It also takes advantage of the collections, finance, and mpl_toolkits modules, among others. Additionally...

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