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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

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Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781783987542
Length 292 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) Chapters Close

Preface 1. Getting Up to Speed 2. The matplotlib Architecture FREE CHAPTER 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

A brief historical overview of matplotlib

The open source project that we now know as matplotlib had its inception at the beginning of the millennium when John Hunter and his colleagues were conducting epilepsy research using proprietary data analysis software. They migrated to MATLAB as it was more flexible and less expensive. However, it was not designed to handle the data formats and diverse data sources that they had to contend with on a daily basis.

It was with this realization that John Hunter created the first version of matplotlib—a GTK+ visualization tool for electroencephalography and electrocorticography analysis. Having been built in Python, adding support for new features as the team needed them was a straightforward task. Before long, this led to the idea of providing a similar interactive command mode to generate plots on the fly, as MATLAB does.

One of the oldest sources available for matplotlib code online is the GitHub repository. The first commit in this repository was with regard to migration from Subversion to Git, though the original repository was CVS. This commit was authored in May 2003, though this repository records a CHANGELOG file whose first entry was made in December 2002. By the time this book goes into publication, matplotlib will have celebrated its 13th birthday.

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