Jupyter Cookbook

Practical recipes on interactive dashboards, visual analytics, big data interaction, and notebook widgets

Key Features

• Take your data science skills to the next level by creating and sharing interactive documents containing live code, text, visualizations, and more
• Perform efficient data exploration, and integrate popular programming languages such as Python, R, Julia, JavaScript, Scala, and big data tools such as Spark with Jupyter
• Cutting-edge recipes on data visualization, widgets, microservices and interactive dashboards

Book Description

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.

What you will learn

• Steps to install Jupyter and configure different language engines
• Accessing and retrieving data on Jupyter Notebooks
• Create interactive visualizations and dashboards for different scenarios
• Convert and Share your dynamic codes using HTML, JavaScript, Docker, and more
• Create custom user data interactions using Jupyter widgets, and build RESTful microservices
• Manage user authentication and file permissions
• Interact with big data to perform numerical computing, statistical modeling, and much more
• Get familiar with Jupyter’s next-gen user interface: JupyterLab

Who This Book Is For

This cookbook is for data science professionals, developers, technical data analysts, and programmers who want to execute technical coding, visualize output, and do scientific computing in one tool. Prior understanding of data science concepts will be helpful, but not mandatory, to use this book.

Table of Contents

Chapter 1. Installation and Setting up the Environment
Chapter 2. Adding an Engine
Chapter 3. Accessing and Retrieving Data
Chapter 4. Visualizing Your Analytics
Chapter 5. Working with Widgets
Chapter 6. Jupyter Dashboards
Chapter 7. Sharing Your Code
Chapter 8. Multiuser Jupyter
Chapter 9. Interacting with Big Data
Chapter 10. Jupyter Security
Chapter 11. Jupyter Labs