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Learning Jupyter

You're reading from   Learning Jupyter Select, Share, Interact and Integrate with Jupyter Notebook

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Product type Paperback
Published in Nov 2016
Publisher Packt
ISBN-13 9781785884870
Length 238 pages
Edition 1st 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 (11) Chapters Close

Preface 1. Introduction to Jupyter FREE CHAPTER 2. Jupyter Python Scripting 3. Jupyter R Scripting 4. Jupyter Julia Scripting 5. Jupyter JavaScript Coding 6. Interactive Widgets 7. Sharing and Converting Jupyter Notebooks 8. Multiuser Jupyter Notebooks 9. Jupyter Scala 10. Jupyter and Big Data

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) using the add function:

Pkg.add("Gadfly")

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

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 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 all results in this chapter are reproducible.

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

Julia Gadfly histogram

We can produce other graph types as well, for example, a histogram using this script:

using Gadfly
srand(111)
plot(x=randn(113), Geom.histogram(bincount=10))

This script generates...

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