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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 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

An example – AWS and Docker


The rest of this chapter is dedicated to the running of the matplotlib USGS/EROS image generation task in AWS using EC2, S3, and Docker. We are going to need to perform two stages of preparation—work that needs to be done locally and the setup that needs to happen in the Cloud. With these complete, we will be ready to execute our prepared task.

Getting set up locally

Your local setup will include an installation of Docker (and boot2docker if you are using Mac or Windows). It will create or download Dockerfiles, generate images from these files, extend the base images as necessary, and start up a Docker image to ensure that everything is in working order.

Requirements

Here's what you will need for the remainder of this chapter:

  • Docker

  • boot2docker (for easily using Docker from Windows or Mac)

If you're running Linux, you can skip the rest of this section. If you haven't run boot2docker before, you'll need to run the following command first:

$ boot2docker init

If you have...

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