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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):

Tattar

Bhushan Purushottam Joshi

Sean P Murphy

ABHIJIT DASGUPTA

Anthony Ojeda

+1 more

View More author details

Table of Contents (17) Chapters

Title Page

Credits

About the Authors

About the Reviewer

www.PacktPub.com

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

Discriminant analysis

Discriminant analysis is one of the earliest statistical methods that is used to classify observations into distinct populations. As with many of the earlier pioneering works in statistics, this technique too had been invented by the great Sir R. A. Fisher. The theory of discriminant analysis is beyond the scope of this book. We would simply be content with the use of the lda function from the MASS package. Before applying the lda R technique to the German credit data, we will first apply it on the iris dataset, which is also popular thanks to Fisher. Following the application of the method to the iris dataset, we will then apply it to the German credit data problem.

Getting ready

The requirement of the iris dataset and the MASS package is met by default R software. The reader needs to have prepared the GC2 data frame as in the first section.

How to do it...

We get an initial understanding of the iris data set with simple functions. In this dataset, we have five variables...

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Authors (5)

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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Bhushan Purushottam Joshi

Bhushan 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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Sean P Murphy

Sean P Murphy

Sean Patrick Murphy spent 15 years as a senior scientist at The Johns Hopkins University, Applied Physics Laboratory, where he focused on machine learning, modeling and simulation, signal processing, and high performance computing in the Cloud. Now, he acts as an advisor and data consultant for companies in San Francisco, New York, and Washington DC. He completed graduation from The Johns Hopkins University and got his MBA from the University of Oxford. He currently co-organizes the Data Innovation DC meetup and co-founded the Data Science MD meetup. He is also a board member and cofounder of Data Community DC.

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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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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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