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Mastering Matplotlib

You're reading from Mastering Matplotlib A practical guide that takes you beyond the basics of matplotlib and gives solutions to plot complex data

Product type Paperback

Published in Jun 2015

Publisher

ISBN-13 9781783987542

Length 292 pages

Edition 1st Edition

Languages

Python

Tools

Matplotlib

Concepts

Data Visualization

Author (1):

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 FREE CHAPTER

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

What's new in matplotlib 1.4

In the past 12 years, a great deal has happened in the matplotlib codebase. Of particular interest are the new features that have been added to the most recent release at the time of writing this book—version 1.4.3. Here are some of its highlights:

A new IPython Notebook backend for interactive matplotlib plot support
A new style package that allows for greater control over the visual presentation of plots
The new Qt5 backend
Google App Engine integration
New plotting features
New configuration options

You have been reading a chapter from

Mastering Matplotlib

Published in: Jun 2015

Publisher:

ISBN-13: 9781783987542

© 2015 Packt Publishing Limited All Rights Reserved

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Authors (1)

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.

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