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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

Chapter 5. High-level Plotting and Data Analysis

A significant aspect of gaining matplotlib mastery is familiarizing oneself with the use of the other Python tools in the scientific programming ecosystem. Libraries such as NumPy, SciPy, Pandas, or SymPy are just the beginning. The tools available in the community cover an enormous amount of ground, entailing the spectrum of many fields and subspecialties. Projects such as scikit-learn, AstroPy, h5py, and so on, build upon the foundations provided by others, thus being able to provide more functionality quicker than, if they had to start from scratch themselves.

Those who may want to look more deeply into these and other tools may benefit from a guided tour into one area that could serve as a template for future exploration into many other areas. This is our mission in this chapter, with our entry points for further examination being the following:

  • A background and overview of high-level plotting
  • Practical high-level plotting, using...
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