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Jupyter for Data Science

You're reading from   Jupyter for Data Science Exploratory analysis, statistical modeling, machine learning, and data visualization with Jupyter

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781785880070
Length 242 pages
Edition 1st Edition
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Table of Contents (11) Chapters Close

Preface 1. Jupyter and Data Science FREE CHAPTER 2. Working with Analytical Data on Jupyter 3. Data Visualization and Prediction 4. Data Mining and SQL Queries 5. R with Jupyter 6. Data Wrangling 7. Jupyter Dashboards 8. Statistical Modeling 9. Machine Learning Using Jupyter 10. Optimizing Jupyter Notebooks

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.

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