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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

The matplotlib object-oriented API

Before we begin, a caveat about the terminology is in order. We use the phrase matplotlib object-oriented API to refer to a direct access to matplotlib's artist and backend layers. The pyplot scripting layer is also object-oriented in that it is composed of functions and instances that are object-oriented by design. The pyplot interface is built upon the OOP methodologies utilized by matplotlib. The distinction that we attempt to make in this section is that we will be creating these objects directly instead of using a scripting layer that does the same for us.

As with the previous section, we acknowledge that the object-oriented API for matplotlib has been covered in great detail in other materials and we will therefore simply provide an overview of the interface via an example, much like with the pyplot API overview.

Of the many circumstances that require fine-grained control over the elements of a plot or the customized use of the backend, a very...

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