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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
Languages
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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 visualizations in Jupyter


The most popular tool for visualizations in Julia is the Gadfly package. We can add the Gadfly package (as described at the beginning of this chapter) by using the add function:

Pkg.add("Gadfly") 

 

From then on, we can make reference to the Gadfly package in any script by using the following:

using Gadfly 

Julia Gadfly scatterplot

We can use the plot() function with standard defaults (no type arguments) to generate a scatterplot. For example, with the following simple script:

using Gadfly 
srand(111) 
plot(x=rand(7), y=rand(7)) 

Note

We use the srand() function in all examples that use random results. The srand() function sets the random number seed value so that all of the results in this chapter are reproducible.

We generate a nice, clean scatterplot, as shown in the following screenshot:

 

I did notice that if you click on the ? symbol that appears in the top-right of the graphic if you click on the graphic, a message box is displayed that enables finer control over...

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