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Jupyter Cookbook

You're reading from Jupyter Cookbook

Product type Book

Published in Apr 2018

Publisher Packt

ISBN-13 9781788839440

Pages 238 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Dan Toomey

Table of Contents (17) Chapters

Title Page

Copyright and Credits

Packt Upsell

Contributors

Preface

1. Installation and Setting up the Environment

2. Adding an Engine

3. Accessing and Retrieving Data

4. Visualizing Your Analytics

5. Working with Widgets

6. Jupyter Dashboards

7. Sharing Your Code

8. Multiuser Jupyter

9. Interacting with Big Data

10. Jupyter Security

11. Jupyter Labs

Index

Adding the R engine

R is both a programming language and a software environment geared toward statistical computing and associated graphics. R has a clean syntax, providing access to a large set of statistical packages, publicly available for free use.

How to do it...

We can add the R engine to our Jupyter installation using Anaconda Navigator or the command line.

Installing the R engine using Anaconda Navigator

R is included with the R Studio option in Anaconda Navigator, as shown in this partial screenshot:

As noted in the screen, the R Studio installation includes R essentials and Notebooks (Notebook engine support).

Note

This screenshot shows R after it has been installed (see the Launch button). Whereas before it is installed, the rstudio graphic icon will display in Anaconda Navigator with an Install button.

Once you select the Install button, Anaconda will automatically install R in your environment and bring you back to the Navigator screen, now showing the Launch button as shown in the...

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Authors (1)

Dan Toomey

Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.

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