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R Data Analysis Cookbook - Second Edition

You're reading from R Data Analysis Cookbook - Second Edition

Product type Book

Published in Sep 2017

Publisher Packt

ISBN-13 9781787124479

Pages 560 pages

Edition 2nd Edition

Languages

Concepts

Authors (3):

Kuntal Ganguly

Shanthi Viswanathan

Viswa Viswanathan

View More author details

Table of Contents (14) Chapters

Preface

1. Acquire and Prepare the Ingredients - Your Data

2. What's in There - Exploratory Data Analysis

3. Where Does It Belong? Classification

4. Give Me a Number - Regression

5. Can you Simplify That? Data Reduction Techniques

6. Lessons from History - Time Series Analysis

7. How does it look? - Advanced data visualization

8. This may also interest you - Building Recommendations

9. It's All About Your Connections - Social Network Analysis

10. Put Your Best Foot Forward - Document and Present Your Analysis

11. Work Smarter, Not Harder - Efficient and Elegant R Code

12. Where in the World? Geospatial Analysis

13. Playing Nice - Connecting to Other Systems

Performing preliminary analyses on time series data

Before creating proper time series objects, we may want to do some preliminary analyses. This recipe shows you how.

Getting ready

The base R package provides all the necessary functionality. If you have not already downloaded the data files for this chapter, please do it now, and ensure that they are located in your R working directory.

How to do it...

Read the file. We will use a data file that has the share prices of Walmart (downloaded from Yahoo Finance) between March 11, 1999 and January 15, 2015:

> wm <...

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Authors (3)

Kuntal Ganguly

Kuntal Ganguly is a big data analytics engineer focused on building large-scale, data-driven systems using big data frameworks and machine learning. He has around 7 years experience of building big data and machine learning applications. Kuntal provides solutions to cloud customers in building real-time analytics systems using managed cloud services and open source Hadoop ecosystem technologies such as Spark, Kafka, Storm, Solr, and so on, along with machine learning and deep learning frameworks. Kuntal enjoys hands-on software development and has single-handedly conceived, architected, developed, and deployed several large-scale distributed applications. He is a machine learning and deep learning practitioner and is very passionate about building intelligent applications.

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Shanthi Viswanathan

nan

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Viswa Viswanathan

Viswa Viswanathan is an associate professor of Computing and Decision Sciences at the Stillman School of Business in Seton Hall University. After completing his PhD in Artificial Intelligence, Viswa spent a decade in academia and then switched to a leadership position in the software industry for another decade during which he worked for Infosys, Igate, and Starbase. He embraced academia once again in 2001. Viswa has taught extensively in fields ranging from operations research, computer science, software engineering, management information systems, and enterprise systems. In addition to university teaching, Viswa has conducted training programs for industry professionals and has written several peer-reviewed research publications in journals such as Operations Research, IEEE Software, Computers and Industrial Engineering, and International Journal of Artificial Intelligence in Education. He has authored a book titled Data Analytics with R:A hands-on approach. Viswa thoroughly enjoys hands-on software development and has single-handedly conceived, architected, developed, and deployed several web-based applications. Apart from his deep interest in technical fields such as data analytics, artificial intelligence, computer science, and software engineering, Viswa harbors a deep interest in education with special emphasis on the roots of learning and methods to foster deeper learning. He has done research in this area and hopes to pursue the subject further. Viswa would like to express deep gratitude to professors Amitava Bagchi and Anup Sen, who were inspirational forces during his early research career. He is also grateful to several extremely intelligent colleagues, notable among them being Rajesh Venkatesh, Dan Richner, and Sriram Bala, who significantly shaped his thinking. His aunt, Analdavalli; his sister, Sankari; and his wife, Shanthi, taught him much about hard work, and even the little he has absorbed has helped him immensely. His sons, Nitin and Siddarth, have helped with numerous insightful comments on various topics.

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