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

Versioning a notebook


A common practice in the programming world is to maintain a history of the changes made to a program. Over time the different versions of the program are maintained in a software repository where the programmer can retrieve prior versions to return to an older, working state of their program.

In the previous section we mentioned placing your notebook on GitHub. Git is a software repository in wide use. GitHub is an internet-based instance of Git. Once you have any software in Git it will automatically be versioned. The next time you update your notebook in GitHub. Git will take the current instance, store it as a version in your history, and place the new instance as the current—where anyone accessing your GitHub repository will see the latest version by default.