R For Dummies

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.

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, open‐source 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

Distinguishing data types 99

Working with ordered factors 100

Chapter 6: Going on a Date with R 103

Working with Dates 104

Presenting Dates in Different Formats 106

Adding Time Information to Dates 107

Formatting Dates and Times 109

Performing Operations on Dates and Times 109

Addition and subtraction 109

Comparison of dates 110

Extraction 111

Chapter 7: Working in More Dimensions 113

Adding a Second Dimension 113

Discovering a new dimension 114

Combining vectors into a matrix 117

Using the Indices 118

Extracting values from a matrix 118

Replacing values in a matrix 120

Naming Matrix Rows and Columns 121

Changing the row and column names 122

Using names as indices 123

Calculating with Matrices 123

Using standard operations with matrices 124

Calculating row and column summaries 125

Doing matrix arithmetic 126

Adding More Dimensions 127

Creating an array 128

Using dimensions to extract values 129

Combining Different Types of Values in a Data Frame 130

Creating a data frame from a matrix 130

Creating a data frame from scratch 132

Naming variables and observations 133

Manipulating Values in a Data Frame 134

Extracting variables, observations, and values 135

Adding observations to a data frame 136

Adding variables to a data frame 139

Combining Different Objects in a List 140

Creating a list 141

Extracting components from lists 142

Changing the components in lists 144

Reading the output of str( ) for lists 146

Seeing the forest through the trees 148

Part III: Coding in R 149

Chapter 8: Putting the Fun in Functions 151

Moving from Scripts to Functions 151

Making the script 152

Transforming the script 153

Using the function 154

Reducing the number of lines 155

Using Arguments the Smart Way 157

Adding more arguments 157

Conjuring tricks with dots 159

Using functions as arguments 161

Coping with Scoping 163

Crossing the borders 164

Dispatching to a Method 165

Finding the methods behind the function 166

Doing it yourself 168

Chapter 9: Controlling the Logical Flow 171

Making Choices with if Statements 172

Doing Something Else with an if else Statement 174

Vectorizing Choices 176

Looking at the problem 176

Choosing based on a logical vector 176

Making Multiple Choices 178

Chaining if else statements 178

Switching between possibilities 180

Looping Through Values 181

Constructing a for loop 181

Calculating values in a for loop 182

Looping without Loops: Meeting the Apply Family 184

Looking at the family features 185

Meeting three of the members 185

Applying functions on rows and columns 186

Applying functions to listlike objects 188

Chapter 10: Debugging Your Code 193

Knowing What to Look For 193

Reading Errors and Warnings 194

Reading error messages 194

Caring about warnings (or not) 195

Going Bug Hunting 197

Calculating the logit 197

Knowing where an error comes from 197

Looking inside a function 198

Generating Your Own Messages 202

Creating errors 203

Creating warnings 203

Recognizing the Mistakes You’re Sure to Make 204

Starting with the wrong data 204

Having your data in the wrong format 205

Chapter 11: Getting Help 209

Finding Information in the R Help Files 209

When you know exactly what you’re looking for 210

When you don’t know exactly what you’re looking for 211

Searching the Web for Help with R 212

Getting Involved in the R Community 213

Discussing R on Stack Overflow and Stack Exchange 213

Using the R mailing lists 214

Tweeting about R 215

Making a Minimal Reproducible Example 215

Creating sample data with random values 215

Producing minimal code 217

Providing the necessary information 217

Part IV: Making the Data Talk 219

Chapter 12: Getting Data into and out of R 221

Getting Data into R 221

Entering data in the R text editor 222

Using the Clipboard to copy and paste 223

Reading data in CSV files 225

Reading data from Excel 229

Working with other data types 230

Getting Your Data out of R 232

Working with Files and Folders 233

Understanding the working directory 233

Manipulating files 234

Chapter 13: Manipulating and Processing Data 239

Deciding on the Most Appropriate Data Structure 239

Creating Subsets of Your Data 241

Understanding the three subset operators 241

Understanding the five ways of specifying the subset 242

Subsetting data frames 242

Adding Calculated Fields to Data 247

Doing arithmetic on columns of a data frame 247

Using with and transform to improve code readability 248

Creating subgroups or bins of data 249

Combining and Merging Data Sets 251

Creating sample data to illustrate merging 252

Using the merge( ) function 253

Working with lookup tables 255

Sorting and Ordering Data 257

Sorting vectors 257

Sorting data frames 258

Traversing Your Data with the Apply Functions 260

Using the apply( ) function to summarize arrays 261

Using lapply( ) and sapply( ) to traverse a list or data frame 263

Using tapply( ) to create tabular summaries 264

Getting to Know the Formula Interface 266

Whipping Your Data into Shape 268

Understanding data in long and wide formats 269

Getting started with the reshape2 package 270

Melting data to long format 270

Casting data to wide format 271

Chapter 14: Summarizing Data 275

Starting with the Right Data 275

Using factors or numeric data 276

Counting unique values 277

Preparing the data 277

Describing Continuous Variables 278

Talking about the center of your data 278

Describing the variation 279

Checking the quantiles 279

Describing Categories 281

Counting appearances 281

Calculating proportions 282

Finding the center 282

Describing Distributions 283

Plotting histograms 283

Using frequencies or densities 285

Describing Multiple Variables 287

Summarizing a complete dataset 287

Plotting quantiles for subgroups 288

Tracking correlations 290

Working with Tables 293

Creating a two‐way table 294

Converting tables to a data frame 295

Looking at margins and proportions 296

Chapter 15: Testing Differences and Relations 299

Taking a Closer Look at Distributions 300

Observing beavers 300

Testing normality graphically 301

Using quantile plots 302

Testing normality in a formal way 304

Comparing Two Samples 305

Testing differences 305

Comparing paired data 308

Testing Counts and Proportions 309

Checking out proportions 309

Analyzing tables 310

Extracting test results 312

Working with Models 313

Analyzing variances 313

Evaluating the differences 315

Modeling linear relations 318

Evaluating linear models 320

Predicting new values 323

Part V: Working with Graphics 325

Chapter 16: Using Base Graphics 327

Creating Different Types of Plots 327

Getting an overview of plot 328

Adding points and lines to a plot 329

Different plot types 332

Controlling Plot Options and Arguments 334

Adding titles and axis labels 335

Changing plot options 335

Putting multiple plots on a single page 339

Saving Graphics to Image Files 340

Chapter 17: Creating Faceted Graphics with Lattice 343

Creating a Lattice Plot 344

Loading the lattice package 345

Making a lattice scatterplot 345

Adding trend lines 346

Changing Plot Options 348

Adding titles and labels 348

Changing the font size of titles and labels 349

Using themes to modify plot options 350

Plotting Different Types 351

Making a bar chart 352

Making a box‐and‐whisker plot 353

Plotting Data in Groups 354

Using data in tall format 354

Creating a chart with groups 356

Adding a key 356

Printing and Saving a Lattice Plot 357

Assigning a lattice plot to an object 358

Printing a lattice plot in a script 358

Saving a lattice plot to file 358

Chapter 18: Looking At ggplot 2 Graphics 361

Installing and Loading ggplot2 361

Looking At Layers 362

Using Geoms and Stats 363

Defining what data to use 364

Mapping data to plot aesthetics 364

Getting geoms 365

Sussing Stats 369

Adding Facets, Scales, and Options 371

Adding facets 371

Changing options 372

Getting More Information 374

Part VI: The Part of Tens 375

Chapter 19: Ten Things You Can Do in R That You Would’ve Done in Microsoft Excel 377

Adding Row and Column Totals 377

Formatting Numbers 378

Sorting Data 380

Making Choices with If 380

Calculating Conditional Totals 381

Transposing Columns or Rows 382

Finding Unique or Duplicated Values 383

Working with Lookup Tables 383

Working with Pivot Tables 384

Using the Goal Seek and Solver 385

Chapter 20: Ten Tips on Working with Packages 387

Poking Around the Nooks and Crannies of CRAN 387

Finding Interesting Packages 388

Installing Packages 389

Loading Packages 389

Reading the Package Manual and Vignette 390

Updating Packages 390

Forging Ahead with R‐Forge 391

Getting packages from github 392

Conducting Installations from BioConductor 392

Reading the R Manual 393

Appendix A: Installing R and RStudio 395

Installing and Configuring R 395

Installing R 395

Configuring R 396

Installing and Configuring RStudio 398

Installing RStudio 398

Configuring RStudio 398

Appendix B: The r fordummies Package 401

Using rfordummies 401

Index 403