Data Manipulation with R.
This book is for all those who wish to learn about data manipulation from scratch and excel at aggregating data effectively. It is expected that you have basic knowledge of R and have previously done some basic administration work with R.
Read More ↓Title Statements
- Full title :Data Manipulation with R.
Summary
This book is for all those who wish to learn about data manipulation from scratch and excel at aggregating data effectively. It is expected that you have basic knowledge of R and have previously done some basic administration work with R.
Read More ↓Edition Statements
- Publication Date:2015.
- Edition:2nd ed
Publication Statements
- Publisher(s):Packt Publishing
- Place of Publication:Birmingham
- Language:eng
- Publication Date:2015.
The Physical Object
- Description:1 online resource (130 pages)
Edition Identifiers
- ISBN:1785288814, 9781785288814, 1785288504, 9781785288500
- oclc:ocn994577462
Table of Contents
Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Introduction to R Data Types and Basic Operations; Getting different versions of R; Installing R on different platforms; Installing and using R libraries; Manually downloading and installing packages; Installing packages within the R shell; Comparing R with other software; R as an enterprise solution; Writing commands in R; R data types and basic operations; Modes and classes of R objects; The R object structure and mode conversion; Vector; Factor and its types.
Data frameMatrices; Arrays; List; Missing values in R; Summary; Chapter 2: Basic Data Manipulation; Acquiring data; Vector and matrix operations; Factor manipulation; Factors from numeric variables; Date processing using lubridate; Character manipulation; Subscripting and subsetting; Summary; Chapter 3: Data Manipulation using plyr and dplyr; Applying the split-apply-combine strategy; Introducing the plyr and dplyr libraries; plyr's utilities; Intuitive function names in the plyr library; Inputs and arguments; Multiargument functions; Comparing base R and plyr.
Powerful data manipulation with dplyrF…
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