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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

R dataset access

For this example, we will use the Iris dataset. Iris is built into R installations and is available directly. Let's just pull in the data, gather some simple statistics, and plot the data. This will show R accessing a dataset in Jupyter, using an R built-in package, as well as some available statistics (since we have R), and the interaction with R graphics.

The script we will use is as follows:

dataset(iris)
summary(iris)
plot(iris)

If we enter this small script into a new R notebook, we get an initial display that looks like the following:

R dataset access

I would expect the standard R statistical summary as output, and I know the Iris plot is pretty interesting. We can see exactly what happened in the following screenshot:

R dataset access

The plot continues in the following screenshot as it wouldn't fit into a single screenshot:

R dataset access

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