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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
Languages
Tools
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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

Sharing your Notebook using nbviewer


Built into Jupyter is a tool called nbviewer, responsible for exposing your Notebook as a web page. nbviewer is used through a public Notebook sharing service, the Notebook Viewer, at http://nbviewer.ipython.org.

nbviewer is fully supported by the Jupyter project. So, if you encounter any issues they will help.

You can use nbviewer in conjunction with Docker or standalone.

How to do it...

To use nbviewer with Docker, you can use Docker commands directly to load your Notebook:

$ docker pull jupyter/nbviewer
$ docker run -p 8080:8080 jupyter/nbviewer

These commands are as follows:

  • The docker pull command downloads nbviewer from the code repository where all Jupyter products are maintained onto your machine
  • The docker run command executes nbviewer (just downloaded) and exposes Jupyter at port 8080 (which is a standard HTTP port address)

Once executed, if you open a browser to the local machine and port 8080, you see the standard Jupyter home page. You can then add...

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