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Practical Data Science Cookbook, Second Edition

You're reading from Practical Data Science Cookbook, Second Edition Data pre-processing, analysis and visualization using R and Python

Product type Paperback

Published in Jun 2017

Publisher Packt

ISBN-13 9781787129627

Length 434 pages

Edition 2nd Edition

Languages

Python

Concepts

Data Analysis

Authors (5):

Anthony Ojeda

Prabhanjan Narayanachar Tattar

ABHIJIT DASGUPTA

Sean P Murphy

Bhushan Purushottam Joshi

+1 more

View More author details

Table of Contents (12) Chapters

Preface

1. Preparing Your Data Science Environment FREE CHAPTER

2. Driving Visual Analysis with Automobile Data with R

3. Creating Application-Oriented Analyses Using Tax Data and Python

4. Modeling Stock Market Data

5. Visually Exploring Employment Data

6. Driving Visual Analyses with Automobile Data

7. Working with Social Graphs

8. Recommending Movies at Scale (Python)

9. Harvesting and Geolocating Twitter Data (Python)

10. Forecasting New Zealand Overseas Visitors

11. German Credit Data Analysis

Exploring the characteristics of entire networks

In the next set of recipes, we will characterize our social network as a whole, rather than from the perspective of individual actors. This task is usually secondary to getting a feel of the most important nodes, but it is a chicken and an egg problem; determining the techniques to analyze and splitting the whole graph can be informed by key player analyses, and vice versa.

Getting ready

If you completed the previous recipes, you will be ready to proceed with this one.

How to do it...

The following steps will walk us through our first exploration of graph characteristics at the level of the whole graph:

Let's compute both the density of the entire network and that of the ego graphs:

>>> nx.density(graph)
0.00810031232554
>>> ego = nx.ego_graph(graph, "LONGBOW/AMELIA GREER")
>>> nx.density(ego)
0.721014492754

As you can see, our heroic social network is not very dense; it's not very cliquish as a whole. However, Longbow...

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Authors (5)

Purushottam Joshi

Purushottam Joshi

Bhushan Purushottam Joshi is a teacher of computer science and has around 11 years of experience in teaching. He started his career as a programmer in a software firm but found true joy in teaching. He is a teacher by choice and not by chance. He teaches computer science courses such as MCA, MSc IT, BSc IT, and BSc CS at various colleges in Mumbai. He is a master at presenting technical as well as conceptual subjects in the most simplified manner. He has exemplary skills in relating daily life examples to technical concepts, which facilitates understanding of the subject matter. He enjoys teaching technical as well as conceptual subjects such as web design, Java, C#, C++, operating systems, computer networks, data structures, and ethical hacking. He is quite popular and appreciated among his students for his able guidance in their project work

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Tattar

Tattar

Prabhanjan Narayanachar Tattar is a lead statistician and manager at the Global Data Insights & Analytics division of Ford Motor Company, Chennai. He received the IBS(IR)-GK Shukla Young Biometrician Award (2005) and Dr. U.S. Nair Award for Young Statistician (2007). He held SRF of CSIR-UGC during his PhD. He has authored books such as Statistical Application Development with R and Python, 2nd Edition, Packt; Practical Data Science Cookbook, 2nd Edition, Packt; and A Course in Statistics with R, Wiley. He has created many R packages.

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Anthony Ojeda

Anthony Ojeda

Tony Ojeda is an accomplished data scientist and entrepreneur, with expertise in business process optimization and over a decade of experience creating and implementing innovative data products and solutions. He has a master's degree in finance from Florida International University and an MBA with a focus on strategy and entrepreneurship from DePaul University. He is the founder of District Data Labs, is a cofounder of Data Community DC, and is actively involved in promoting data science education through both organizations.

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ABHIJIT DASGUPTA

ABHIJIT DASGUPTA

<p>Abhijit Dasgupta is a data consultant working in the greater DC-Maryland-Virginia area, with several years of experience in biomedical consulting, business analytics, bioinformatics, and bioengineering consulting. He has a PhD in biostatistics from the University of Washington and over 40 collaborative peer-reviewed manuscripts, with strong interests in bridging the statistics/machine-learning divide. He is always on the lookout for interesting and challenging projects, and is an enthusiastic speaker and discussant on new and better ways to look at and analyze data. He is a member of Data Community DC and a founding member and co-organizer of Statistical Programming DC (formerly R Users DC)</p>

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Sean P Murphy

Sean P Murphy

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