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

Arbitrary search of ratings


Since we have the data in an easily loadable format we can search for arbitrary conditions, such as Personal Chefs that allow dogs-maybe they will custom cook for your dog.

We could use a script as follows: for line in lines:

    line = unicode(line, errors='ignore')    obj = json.loads(line)    if obj['categories'] == None:        continue    if 'Personal Chefs' in obj['categories']:        if obj['attributes'] == None:            continue        for attr in obj['attributes']:            print (attr)

Where we do something useful with the items that filter out. This script would display the attributes only for Personal Chefs. As can be seen in the following display:

We could just as easily performed some calculation or other manipulation to narrow down and focus on a very specific portion of the data easily.