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Big Data Analytics with R

You're reading from  Big Data Analytics with R

Product type Book
Published in Jul 2016
Publisher Packt
ISBN-13 9781786466457
Pages 506 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Simon Walkowiak Simon Walkowiak
Profile icon Simon Walkowiak

Table of Contents (16) Chapters

Big Data Analytics with R
Credits
About the Author
Acknowledgement
About the Reviewers
www.PacktPub.com
Preface
1. The Era of Big Data 2. Introduction to R Programming Language and Statistical Environment 3. Unleashing the Power of R from Within 4. Hadoop and MapReduce Framework for R 5. R with Relational Database Management Systems (RDBMSs) 6. R with Non-Relational (NoSQL) Databases 7. Faster than Hadoop - Spark with R 8. Machine Learning Methods for Big Data in R 9. The Future of R - Big, Fast, and Smart Data

Chapter 2. Introduction to R Programming Language and Statistical Environment

In Chapter 1, The era of "Big Data", you have become familiar with the most useful Big Data terminology, and a small selection of typical tools applied to unusually large or complex data sets. You have also gained essential insights into how R was developed and how it became the leading statistical computing environment and programming language favored by technology giants and the best universities in the world. In this chapter you will have the opportunity to learn some most important R functions from base R installation and well-known third party packages used for data crunching, transformation, and analysis. More specifically in this chapter you will:

  • Understand the landscape of available R data structures

  • Be guided through a number of R operations allowing you to import data from standard and proprietary data formats

  • Carry out essential data cleaning and processing activities such as subsetting, aggregating, creating...

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