Book description
Learn how to write code, mathematics, graphics, and output, all in a single document, as well as in a web browser using Project Jupyter
About This Book
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
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.
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
In Detail
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.
Style and approach
This comprehensive practical guide will teach you how to work with the Jupyter Notebook system. It demonstrates the integration of various programming languages with Jupyter Notebook through hands-on examples in every chapter.
Table of contents
-
Learning Jupyter
- Learning Jupyter
- Credits
- About the Author
- About the Reviewer
- www.PacktPub.com
- Preface
- 1. Introduction to Jupyter
- 2. Jupyter Python Scripting
- 3. Jupyter R Scripting
- 4. Jupyter Julia Scripting
-
5. Jupyter JavaScript Coding
- Adding JavaScript scripting to your installation
- JavaScript Hello World Jupyter Notebook
- Basic JavaScript in Jupyter
- JavaScript limitations in Jupyter
- Node.js d3 package
- Node.js stats-analysis package
- Node.js JSON handling
- Node.js canvas package
- Node.js plotly package
- Node.js asynchronous threads
- Node.js decision-tree package
- Summary
- 6. Interactive Widgets
- 7. Sharing and Converting Jupyter Notebooks
- 8. Multiuser Jupyter Notebooks
- 9. Jupyter Scala
- 10. Jupyter and Big Data
Product information
- Title: Learning Jupyter
- Author(s):
- Release date: November 2016
- Publisher(s): Packt Publishing
- ISBN: 9781785884870
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