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Learning Jupyter 5

You're reading from   Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab

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Product type Paperback
Published in Aug 2018
Publisher
ISBN-13 9781789137408
Length 282 pages
Edition 2nd Edition
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Jupyter FREE CHAPTER 2. Jupyter Python Scripting 3. Jupyter R Scripting 4. Jupyter Julia Scripting 5. Jupyter Java Coding 6. Jupyter JavaScript Coding 7. Jupyter Scala 8. Jupyter and Big Data 9. Interactive Widgets 10. Sharing and Converting Jupyter Notebooks 11. Multiuser Jupyter Notebooks 12. What's Next? 13. Other Books You May Enjoy

Julia Vega plotting


Another popular graphics package is Vega. The main feature of Vega is the ability to describe your graphic by using language primitives such as JSON. Vega produces most of the standard plots. Here is an example script using Vega for a pie chart:

Pkg.add("Vega") 
using Vega 
stock = ["chairs", "tables", "desks", "rugs", "lamps"]; 
quantity = [15, 10, 10, 5, 20]; 
piechart(x = stock, y = quantity) 

The resultant output in Jupyter may look like the following screenshot:

Note

Note the INFO: Precompiling module Vega. package. Even though the package had been loaded as part of the install or update process, it still needed to adjust the library on first use.

The generated graphic produced under Jupyter is shown in the following screenshot

Vega gives you the option on the resultant display to Save as PNG. I think this is a useful feature, allowing you to embed the generated graphic(s) in another document:

 

 

Julia PyPlot plotting

Another plotting package available is PyPlot. PyPlot is...

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