Book Image

Jupyter Cookbook

By : Dan Toomey
Book Image

Jupyter Cookbook

By: Dan Toomey

Overview of this book

Jupyter has garnered a strong interest in the data science community of late, as it makes common data processing and analysis tasks much simpler. This book is for data science professionals who want to master various tasks related to Jupyter to create efficient, easy-to-share, scientific applications. The book starts with recipes on installing and running the Jupyter Notebook system on various platforms and configuring the various packages that can be used with it. You will then see how you can implement different programming languages and frameworks, such as Python, R, Julia, JavaScript, Scala, and Spark on your Jupyter Notebook. This book contains intuitive recipes on building interactive widgets to manipulate and visualize data in real time, sharing your code, creating a multi-user environment, and organizing your notebook. You will then get hands-on experience with Jupyter Labs, microservices, and deploying them on the web. By the end of this book, you will have taken your knowledge of Jupyter to the next level to perform all key tasks associated with it.
Table of Contents (17 chapters)
Title Page
Copyright and Credits
Packt Upsell

Converting your Notebook into a different format

Another mechanism is to convert your Notebook into a different, normally non-interactive format. This allows you to distribute the Notebook result to users without access to your server. A Notebook can be converted to a set of formats discussed in this section.


Sharing your Notebook using kyso: kyso is a Notebook sharing site particularly for scientists to exchange Notebook information. I do not think it would be a good idea for me to push a sample Notebook onto the site. You can get various sorts of subscription access to kyso.

How to do it...

For the conversions, we will be using a minimal R script that describes the iris dataset. The code is:


Producing the now-familiar data points for the iris set and the corresponding plot:

With the corresponding graph of the iris data:

We will be using the Jupyter File menu options for this section, as you can see here:

Where the choices listed are:

  • Notebook:...