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


Jupyter provides the ability to use a variety of languages when developing a Notebook. Each of the languages is supported through the use of an engine that provides all of the programmatic interface from the coded language instruction that you write with the underlying Notebook. Several of the popular languages in use are Python, R, Julia, JavaScript, and Scala. In this chapter, we will show you the steps to add these engines to your Jupyter installation so that you can script your Notebook in the language you like.


Each Notebook is expected to be written using one language per engine. There are some accommodations for mixing languages in one Notebook, but these are not expected to have a large amount of use.