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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

Concepts

Data Visualization

Authors (2):

Duncan M. McGreggor

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

The intermediate matplotlib user

If you've read the preface, then you know who this book is for—developers with intermediate or advanced knowledge of matplotlib as well as the motivated beginners. But who are they exactly? What do such users know?

Answers to such questions are fairly open-ended. We have the following guidelines. The intermediate matplotlib user should have some limited knowledge to passing experience with the following:

Installation of matplotlib in multiple environments
Creation of basic to moderately complicated matplotlib plots
Basic matplotlib APIs, styling, backends, and customizations
Using matplotlib objects, subplots, and overlays
Advanced third-party tools such as Seaborn, Pandas, ggplot, distributed IPython, and StarCluster
Completed reading most or all of the following books, Matplotlib for Python Developers, Sandro Tosi, Packt Publishing, and matplotlib Plotting Cookbook, Alexandre Devert, Packt Publishing

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Mastering matplotlib

Published in: Jun 2015 Publisher: ISBN-13: 9781783987542

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Authors (2)

Duncan M. McGreggor

Duncan M. McGreggor, having programmed with GOTOs in the 1980s, has made up for that through community service by making open source contributions for more than 20 years. He has spent a major part of the past 10 years dealing with distributed and scientific computing (in languages ranging from Python, Common Lisp, and Julia to Clojure and Lisp Flavored Erlang). In the 1990s, after serving as a linguist in the US Army, he spent considerable time working on projects related to MATLAB and Mathematica, which was a part of his physics and maths studies at the university. Since the mid 2000s, matplotlib and NumPy have figured prominently in many of the interesting problems that he has solved for his customers. With the most recent addition of the IPython Notebook, matplotlib and the suite of the Python scientific computing libraries remain some of his most important professional tools.

See other products by Duncan M. McGreggor

Duncan M McGreggor

Duncan M. McGreggor, having programmed with GOTOs in the 1980s, has made up for that through community service by making open source contributions for more than 20 years. He has spent a major part of the past 10 years dealing with distributed and scientific computing (in languages ranging from Python, Common Lisp, and Julia to Clojure and Lisp Flavored Erlang). In the 1990s, after serving as a linguist in the US Army, he spent considerable time working on projects related to MATLAB and Mathematica, which was a part of his physics and maths studies at the university. Since the mid 2000s, matplotlib and NumPy have figured prominently in many of the interesting problems that he has solved for his customers. With the most recent addition of the IPython Notebook, matplotlib and the suite of the Python scientific computing libraries remain some of his most important professional tools.

See other products by Duncan M McGreggor

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