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Mastering matplotlib

You're reading from  Mastering matplotlib

Product type Book
Published in Jun 2015
Publisher
ISBN-13 9781783987542
Pages 292 pages
Edition 1st Edition
Languages
Authors (2):
Duncan M. McGreggor Duncan M. McGreggor
Profile icon Duncan M. McGreggor
Duncan M McGreggor Duncan M McGreggor
Profile icon Duncan M McGreggor
View More author details

Table of Contents (16) Chapters

Mastering matplotlib
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Getting Up to Speed 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 7. Deploying matplotlib in Cloud Environments

With this chapter, we will move into the topics that focus on the computationally intensive matplotlib tasks. This is not something that is usually associated with matplotlib directly, but rather with libraries like NumPy, Pandas, or scikit-learn, which are often brought to bear on large number-crunching jobs. However, there are a number of situations in which organizations or individual researchers need to generate a large number of plots. In the remainder of the book, our exploration of matplotlib in advanced usage scenarios will rely on the free or low-cost modern techniques that are available to the public. In the early 1960s, the famous computer scientist John McCarthy predicted a day when computational resources would be available like the public utilities of electricity and water. This has indeed come to pass, and we will now turn our focus to these types of environments.

We will cover the following topics in this chapter:

  • Making...

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