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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 2. Jupyter Python Scripting FREE CHAPTER 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

Basic Julia in Jupyter


In this example we will use the Iris dataset for some standard analysis. So, start a new Julia notebook and call it Julia Iris. We can enter a small script to see how the steps progress for a Julia script.

This script uses another package for plotting, Gadfly. You would have to go through similar steps as before to install the package before operating the script.

Enter the following script into separate cells of your notebook:

using RDatasets, DataFrames, Gadfly
set_default_plot_size(5inch, 5inch/golden);
plot(dataset("datasets","iris"), x="SepalWidth",
        y="SepalLength", color="Species")

RDataSets is a library containing several of the commonly used R datasets, such as Iris. This is a simple script-we define our libraries that we are going to use, set the size of the plot area, and plot out the Iris data points (color coded to species).

So, you would end up with a starting screen that looks like the following screenshot:

We should take note of a few aspects...

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