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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 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