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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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Author (1):
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Duncan M. McGreggor Duncan M. McGreggor
Author Profile Icon Duncan M. McGreggor
Duncan M. McGreggor
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Table of Contents (16) Chapters Close

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

matplotlib modules


When discussing the architecture of software libraries, it is of great use to relate a conceptual overview to concrete software components. This not only increases the immediate knowledge with more definite context, but also provides a foundation for a quicker learning process during future explorations. Let's examine the modules in the matplotlib Python package.

Exploring the filesystem

Start by obtaining the IPython Notebook for this chapter, installing the dependencies, starting up the IPython server, and loading the notebook in your browser in the following way:

$ git clone https://github.com/masteringmatplotlib/architecture.git
$ cd architecture
$ make

Once the notebook is loaded, go ahead and run the initial setup commands:

In [1]: import matplotlib
        matplotlib.use('nbagg')
        %matplotlib inline

Now let's create two sets of imports, one for our dependencies and the other for modules that we've created specifically for this notebook:

In [2]: from glob import...
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