Learning Jupyter

Key Features

Learn to write, execute, and comment your live code and formulae all under one roof using this unique guide

This one-stop solution on Project Jupyter will teach you everything you need to know to perform scientific computation with ease

This easy-to-follow, highly practical guide lets you forget your worries in scientific application development by leveraging big data tools such as Apache Spark, Python, R etc

Book Description

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.

What you will learn

Install and run the Jupyter Notebook system on your machine

Implement programming languages such as R, Python, Julia, and JavaScript with Jupyter Notebook

Use interactive widgets to manipulate and visualize data in real time

Start sharing your Notebook with colleagues

Invite your colleagues to work with you in the same Notebook

Organize your Notebook using Jupyter namespaces

Access big data in Jupyter

Who this book is for

This book caters to all developers, students, or educators who want to execute code, see output, and comment all in the same document, in the browser. Data science professionals will also find this book very useful to perform technical and scientific computing in a graphical, agile manner.