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Mastering matplotlib
Mastering matplotlib

Mastering matplotlib: A practical guide that takes you beyond the basics of matplotlib and gives solutions to plot complex data

By Duncan M. McGreggor , Duncan M McGreggor
$35.99 $9.99
Book Jun 2015 292 pages 1st Edition
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eBook
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Publication date : Jun 29, 2015
Length 292 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781783987542
Category :
Table of content icon View table of contents Preview book icon Preview Book

Mastering matplotlib

Chapter 1. Getting Up to Speed

Over the past 12 years of its existence, matplotlib has made its way into the classrooms, labs, and hearts of the scientific computing world. With Python's rise in popularity for serious professional and academic work, matplotlib has taken a respected seat beside long-standing giants such as Mathematica by Wolfram Research and MathWorks' MATLAB products. As such, we feel that the time is ripe for an advanced text on matplotlib that guides its more sophisticated users into new territory by not only allowing them to become experts in their own right, but also providing a clear path that will help them apply their new knowledge in a number of environments.

As a part of a master class series by Packt Publishing, this book focuses almost entirely on a select few of the most requested advanced topics in the world of matplotlib, which includes everything from matplotlib internals to high-performance computing environments. In order to best support this, we want to make sure that our readers have a chance to prepare for the material of this book, so we will start off gently.

The topics covered in this chapter include the following:

  • A brief historical overview of matplotlib

  • What's new in matplotlib

  • Who is an advanced, beginner, or an intermediate matplotlib user

  • The software dependencies for many of the book's examples

  • An overview of Python 3

  • An overview of the coding style used in this book

  • References for installation-related instructions

  • A refresher on IPython Notebooks

  • A teaser of a complicated plot in matplotlib

  • Additional resources to obtain advanced beginner and intermediate matplotlib knowledge

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.

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

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Key benefits

What you will learn

Analyze the matplotlib code base and its internals Rerender visualized data on the fly based on changes in the user interface Take advantage of sophisticated thirdparty libraries to plot complex data relationships Create custom styles for use in specialize publications, presentations, or online media Generate consolidated master plots comprising many subplots for dashboardlike results Deploy matplotlib in Cloud environments Utilize matplotlib in big data projects

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Buy Now

Product Details


Publication date : Jun 29, 2015
Length 292 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781783987542
Category :

Table of Contents

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

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