R For Dummies

Mastering R has never been easier

Picking up R can be tough, even for seasoned statisticians and
data analysts. R For Dummies, 2nd Edition
provides a quick and painless way to master all the R you'll ever
need. Requiring no prior programming experience and packed with
tons of practical examples, step-by-step exercises, and sample
code, this friendly and accessible guide shows you how to know your
way around lists, data frames, and other R data structures, while
learning to interact with other programs, such as Microsoft Excel.
You'll learn how to reshape and manipulate data, merge data sets,
split and combine data, perform calculations on vectors and arrays,
and so much more.

R is an open source statistical environment and programming
language that has become very popular in varied fields for the
management and analysis of data. R provides a wide array of
statistical and graphical techniques, and has become the standard
among statisticians for software development and data analysis.
R For Dummies, 2nd Edition takes the intimidation
out of working with R and arms you with the knowledge and know-how
to master the programming language of choice among statisticians
and data analysts worldwide.

• Covers downloading, installing, and configuring R

• Includes tips for getting data in and out of R

• Offers advice on fitting regression models and ANOVA

• Provides helpful hints for working with graphics

R For Dummies, 2nd Edition is an ideal
introduction to R for complete beginners, as well as an excellent
technical reference for experienced R programmers.

Autorentext

Andrie de Vries is a leading R expert and Business Services Director for Revolution Analytics. With over 20 years of experience, he provides consulting and training services in the use of R. Joris Meys is a statistician, R programmer and R lecturer with the faculty of Bio-Engineering at the University of Ghent.

Zusammenfassung
Mastering R has never been easier Picking up R can be tough, even for seasoned statisticians and data analysts. R For Dummies, 2nd Edition provides a quick and painless way to master all the R you'll ever need. Requiring no prior programming experience and packed with tons of practical examples, step-by-step exercises, and sample code, this friendly and accessible guide shows you how to know your way around lists, data frames, and other R data structures, while learning to interact with other programs, such as Microsoft Excel. You'll learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and so much more.

R is an open source statistical environment and programming language that has become very popular in varied fields for the management and analysis of data. R provides a wide array of statistical and graphical techniques, and has become the standard among statisticians for software development and data analysis. R For Dummies, 2nd Edition takes the intimidation out of working with R and arms you with the knowledge and know-how to master the programming language of choice among statisticians and data analysts worldwide.

• Covers downloading, installing, and configuring R
• Includes tips for getting data in and out of R
• Offers advice on fitting regression models and ANOVA
• Provides helpful hints for working with graphics
  R For Dummies, 2nd Edition is an ideal introduction to R for complete beginners, as well as an excellent technical reference for experienced R programmers.

Inhalt

Introduction 1

About This Book 1

Changes in the Second Edition 2

Conventions Used in This Book 3

What You're Not to Read 4

Foolish Assumptions 4

How This Book Is Organized 5

Part I: Getting Started with R Programming 5

Part II: Getting Down to Work in R 5

Part III: Coding in R 5

Part IV: Making the Data Talk 5

Part V: Working with Graphics 6

Part VI: The Part of Tens 6

Icons Used in This Book 6

Beyond the Book 7

Where to Go from Here 7

Part I: Getting Started with R Programming 9

Chapter 1: Introducing R: The Big Picture 11

Recognizing the Benefits of Using R 12

It comes as free, opensource code 12

It runs anywhere 13

It supports extensions 13

It provides an engaged community 13

It connects with other languages 14

Looking At Some of the Unique Features of R 15

Performing multiple calculations with vectors 15

Processing more than just statistics 16

Running code without a compiler 16

Chapter 2: Exploring R 19

Working with a Code Editor 20

Exploring RGui 21

Dressing up with RStudio 23

Starting Your First R Session 25

Saying hello to the world 25

Doing simple math 26

Using vectors 26

Storing and calculating values 27

Talking back to the user 28

Sourcing a Script 29

Echoing your work 30

Navigating the Environment 32

Manipulating the content of the environment 32

Saving your work 33

Retrieving your work 34

Chapter 3: The Fundamentals of R 35

Using the Full Power of Functions 35

Vectorizing your functions 36

Putting the argument in a function 37

Making history 39

Keeping Your Code Readable 40

Following naming conventions 40

Structuring your code 43

Adding comments 45

Getting from Base R to More 45

Finding packages 45

Installing packages 46

Loading and unloading packages 46

Part II: Getting Down to Work in R 49

Chapter 4: Getting Started with Arithmetic 51

Working with Numbers, Infinity, and Missing Values 51

Doing basic arithmetic 52

Using mathematical functions 54

Calculating whole vectors 57

To infinity and beyond 58

Organizing Data in Vectors 60

Discovering the properties of vectors 61

Creating vectors 63

Combining vectors 64

Repeating vectors 64

Getting Values in and out of Vectors 65

Understanding indexing in R 65

Extracting values from a vector 66

Changing values in a vector 67

Working with Logical Vectors 68

Comparing values 69

Using logical vectors as indices 70

Combining logical statements 71

Summarizing logical vectors 72

Powering Up Your Math 73

Using arithmetic vector operations 73

Recycling arguments 76

Chapter 5: Getting Started with Reading and Writing 79

Using Character Vectors for Text Data 79

Assigning a value to a character vector 80

Creating a character vector with more than one element 80

Extracting a subset of a vector 81

Naming the values in your vectors 82

Manipulating Text 84

String theory: Combining and splitting strings 84

Sorting text 88

Finding text inside text 89

Substituting text 91

Revving up with regular expressions 92

Factoring in Factors 94

Creating a factor 95

Converting a factor 96

Looking at levels 98 Distin...