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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

Advanced plots – a preview

To give a taste of what's to come, let's start up a matplotlib IPython Notebook and look at an example. You will need to download the example from a GitHub repository first:

$ git clone https://github.com/masteringmatplotlib/preview.git
$ cd preview

You only need to do the following in order to bootstrap an environment with all the notebook dependencies and start up the notebook server:

$ make

This will do several things for you automatically, some of which are as follows:

  • Clone a support repository holding various include files
  • Create a Python virtual environment
  • Install matplotlib and other scientific computing Python modules into this virtual environment
  • Start an IPython Notebook server that runs on local host
  • Open a browser window and load the preview notebook in it

In this browser window, you can run the code yourself by selecting each code section and hitting the Shift and Enter keys to execute it. Let's go through an example.

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