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Jupyter Cookbook

You're reading from   Jupyter Cookbook Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788839440
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 (12) Chapters Close

Preface 1. Installation and Setting up the Environment 2. Adding an Engine FREE CHAPTER 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

Installing Jupyter on Linux

Linux is one of the easier installations for Jupyter. Linux has all the tools required to update Jupyter going forward. For Linux, we use similar commands to those shown earlier to install on the Mac from the command line. 

How to do it...

Linux is a very common platform for most programming tasks. Many of the tools used in programming have been developed on Linux and later ported to other operating systems, such as Windows.

We are using Anaconda to install on Linux, but the graphical interface is not available.

The script to install Jupyter on Linux via the command line with the Python 3 engine is:

bash ~/Downloads/Anaconda3-5.0.0.1-Linux-x86_64.sh

Similarly, the command to install with the Python 2 engine is:

bash ~/Downloads/Anaconda2-5.0.0.1-Linux-x86_64.sh

In either case, you will be prompted by some regular install questions:

  • Review and agree to the license agreement
  • Specify whether the standard install directory is OK (if not, you can specify where to install the software)
  • Specify whether to prepend the Anaconda location in your user path (Anaconda recommends this step)

And, as shown earlier under specify Windows and Mac installation sections, you can have the Python 2 and Python 3 engines available using similar steps.

At this point, you should be able to start Anaconda Navigator with the command line:

anaconda-navigator

Or you can run Jupyter directly using the regular command line:

jupyter notebook
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