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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

Perl one-liners

Perl has fallen out of fashion somewhat with the current popularity of Python but, in my opinion, remains one of the best languages for data munging.

Unix distros and OS X (normally) have Perl available, but on Windows, it needs to be installed and on the executable path.

Julia’s performance in handling strings is not one of its greatest strengths, so where normal Unix utilities fall short, the processing of large files can be successfully done using Perl.

Julia introduced an analytical engine (JuliaDB) to tackle the processing and analysis of large datasets, which soon was relegated to unmaintained status. Much of its functionality has been incorporated in the DataFrames and DTables packages, which we will look at when discussing the processing of data files in more detail later in the book.

Here, I’ll restrict myself to using Perl in creating some quite powerful one-liners that can be adapted for use of the run() command in the same sense...

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