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Mastering Julia

You're reading from   Mastering Julia Enhance your analytical and programming skills for data modeling and processing with Julia

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781805129790
Length 506 pages
Edition 2nd Edition
Languages
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Author (1):
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Malcolm Sherrington Malcolm Sherrington
Author Profile Icon Malcolm Sherrington
Malcolm Sherrington
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Table of Contents (14) Chapters Close

Preface 1. Chapter 1: The Julia Environment 2. Chapter 2: Developing in Julia FREE CHAPTER 3. Chapter 3: The Julia Type System 4. Chapter 4: The Three Ms 5. Chapter 5: Interoperability 6. Chapter 6: Working with Data 7. Chapter 7: Scientific Programming 8. Chapter 8: Visualization 9. Chapter 9: Database Access 10. Chapter 10: Networks and Multitasking 11. Chapter 11: Julia’s Back Pages 12. Index 13. Other Books You May Enjoy

Basic graphic packages

These packages are, confusingly, supported by two Julia groups, namely JuliaGraphics (https://github.com/JuliaGraphics), and JuliaPlots (https://github.com/JuliaPlots), so these are both great sources of reference.

First, we will shift to more familiar territory by discussing the graphics implemented through Python modules. We will cover ones we have met on various occasions throughout this book already – that is, PyPlot and its cousin, PythonPlot.

PyPlot and PythonPlot

PyPlot is a part of the work of Steven Johnson of MIT, which arose from the previous development of the PyCall module. We have used it extensively in the previous chapters and will take a little time to discuss it further here.

Note that PyPlot is one of the graphics packages that can be used as a backend for the Plots API, with the others being GR and PlotlyJS. We will cover these later in this chapter.

PyPlot provides an interface to the matplotlib plotting library from...

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