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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

Python, R, and Java

A Julia/Python interface has been supported since the early version of Julia but only to the work of Steven G. Johnson, of MIT, on the PyCall module. Further, this was used in creating the PyPlot visualization package, which is a wrapper around the Python matplotlib package.

We will see this already in this book and will be discussing it in more detail in the chapter on Graphics. Also, Steven Johnson wrote a kernel interface to the IPython IDE (viz. IJulia), and the work between the IPython and Julia teams led to a new version of the former, Jupyter, in which the code examples accompanying this book have been distributed.

These modules are now supported by the JuliaPy community group, and in addition, there is a “reverse” package, PyJulia, which permits Julia to be called from Python; I will describe that briefly shortly.

In addition, there are some wrapper packages, notably those that implement the Pandas, scikit-learn, Seaborn, and SymPy...

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