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Matplotlib for Python Developers

You're reading from   Matplotlib for Python Developers Effective techniques for data visualization with Python

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788625173
Length 300 pages
Edition 2nd Edition
Languages
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Authors (3):
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Claire Chung Claire Chung
Author Profile Icon Claire Chung
Claire Chung
Aldrin Yim Aldrin Yim
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Aldrin Yim
Allen Yu Allen Yu
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Allen Yu
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Table of Contents (11) Chapters Close

Preface 1. Introduction to Matplotlib 2. Getting Started with Matplotlib FREE CHAPTER 3. Decorating Graphs with Plot Styles and Types 4. Advanced Matplotlib 5. Embedding Matplotlib in GTK+3 6. Embedding Matplotlib in Qt 5 7. Embedding Matplotlib in wxWidgets Using wxPython 8. Integrating Matplotlib with Web Applications 9. Matplotlib in the Real World 10. Integrating Data Visualization into the Workflow

Installing Docker

Docker allows developers to run applications in self-contained and lightweight containers. Since its introduction in 2013, Docker has quickly gained popularity among developers. At the center of its technology, Docker uses the resource isolation methods of the Linux kernel instead of a full-blown virtualization hypervisor to run applications.

This enables easier development, packaging, deployment, and management of code. Therefore, all code development work in this chapter will be conducted using a Docker-based environment.

Docker for Windows users

There are two ways to install Docker on Windows: the aptly named Docker for Windows package, and Docker Toolbox. I recommend stable versions of the Docker...

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