Book Image

Jupyter for Data Science

By : Dan Toomey
Book Image

Jupyter for Data Science

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 documents that contain live code, equations, and visualizations. This book is a comprehensive guide to getting started with data science using the popular Jupyter notebook. If you are familiar with Jupyter notebook and want to learn how to use its capabilities to perform various data science tasks, this is the book for you! From data exploration to visualization, this book will take you through every step of the way in implementing an effective data science pipeline using Jupyter. You will also see how you can utilize Jupyter's features to share your documents and codes with your colleagues. The book also explains how Python 3, R, and Julia can be integrated with Jupyter for various data science tasks. By the end of this book, you will comfortably leverage the power of Jupyter to perform various tasks in data science successfully.
Table of Contents (17 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

How to set up R for Jupyter


In the past, it was necessary to install the separate components of Jupyter, Python, and so on to have a working system. With Continuum Analytics, the process of installing Jupyter and adding the R engine to the solution set for Jupyter is easy and works on both Windows and Mac.

Assuming you have installed conda already, we have one command to add support for R programming to Jupyter:

conda install -c r r-essentials

Note

At this point, when you start Jupyter, one of the kernels listed will now be R.