Book Image

Learning Jupyter

By : Dan Toomey
Book Image

Learning Jupyter

By: Dan Toomey

Overview of this book

Jupyter Notebook is a web-based environment that enables interactive computing in notebook documents. It allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, machine learning, and much more. This book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next we’ll help you will learn to integrate Jupyter system with different programming languages such as R, Python, JavaScript, and Julia and explore the various versions and packages that are compatible with the Notebook system. Moving ahead, you master interactive widgets, namespaces, and working with Jupyter in a multiuser mode. Towards the end, you will use Jupyter with a big data set and will apply all the functionalities learned throughout the book.
Table of Contents (16 chapters)
Learning Jupyter
About the Author
About the Reviewer


In this chapter, we learned how to add JavaScript to our Jupyter Notebook. We saw some of the limitations of using JavaScript in Jupyter. We had a look at examples of several packages that are typical of Node.js coding, including d3 for graphics, stats-analysis for statistics, built-in JSON handling, canvas for creating graphics files, and plotly used for generating graphics with a third party tool. We also saw how multi-threaded applications can be developed using Node.JS under Jupyter. Lastly, we saw how to use machine learning to develop a decision tree.

In the next chapter, we will see how to create interactive widgets that can be used in your notebook.