CiNii 図書 - 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.

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

「Nielsen BookData」より

R for dummies

著者

書誌事項

電子リソースにアクセスする全1件

大学図書館所蔵全2件

この図書・雑誌をさがす

注記

収録内容

内容説明・目次

関連文献： 1件中 1-1を表示

詳細情報

書き出し