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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

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, which is called Gadfly. You will have to go through similar steps as to the ones we went through in the previous section to install the package before operating the script.

Enter the following script into separate cells of your Notebook:

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

RDatasets is a library that contains several of the commonly used R datasets, such as iris. This is a simple script—we define the 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 will end up with a starting screen that looks like the...

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