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
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface

Summary


In this chapter, we installed Scala for Jupyter. We used Scala coding to access data sets. We also saw how Scala can manipulate arrays. And we generated random numbers in Scala. There were examples of higher-order functions and pattern matching. We used case classes, saw examples of immutability in Scala, built collections using Scala packages, and looked at Scala traits.

In the next chapter, we will be looking at using big data in Jupyter.