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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 2. The matplotlib Architecture FREE CHAPTER 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

Other visualization tools


The matplotlib module was originally designed for use on workstations and desktops, not servers. Its design did not arise from use cases for high-volume or large datasets. However, as you saw in this chapter, by using the right tools and taking the appropriate measures, matplotlib can perform admirably with hundreds of millions of data points.

Should you ever hit insurmountable barriers for matplotlib (such as real-time visualization and user interaction with billions of data points), you can make use of the following open source projects that were originally designed by keeping large datasets in mind:

  • ParaView (http://www.paraview.org/): This is an open source, multiplatform data analysis and visualization application. ParaView was developed to analyze extremely large datasets by using distributed memory computing resources. It can be run on supercomputers to analyze datasets of petascale size as well as on laptops for smaller data. Paraview also offers the Python...

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