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E-raamat: R For Dummies

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Joris Meys, Andrie de Vries

Formaat: PDF+DRM
Ilmumisaeg: 18-Jun-2015
Kirjastus: For Dummies
Keel: eng
ISBN-13: 9781119055853

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Mathematical & statistical software

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Formaat: PDF+DRM
Ilmumisaeg: 18-Jun-2015
Kirjastus: For Dummies
Keel: eng
ISBN-13: 9781119055853

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Mathematical & statistical software

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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

(8)

About This Book

(1)

Changes in the Second Edition

(1)

Conventions Used in This Book

(1)

What You're Not to Read

(1)

Foolish Assumptions

(1)

How This Book Is Organized

(1)

Part I: Getting Started with R Programming

(1)

Part II: Getting Down to Work in R

(1)

Part III: Coding in R

(1)

Part IV: Making the Data Talk

(1)

Part V: Working with Graphics

(1)

Part VI: The Part of Tens

(1)

Icons Used in This Book

(1)

Beyond the Book

(1)

Where to Go from Here

(2)

Part 1: Getting Started with R Programming

(40)

Chapter 1 Introducing R: The Big Picture

(8)

Recognizing the Benefits of Using R

(3)

It comes as free, open-source code

(1)

It runs anywhere

(1)

It supports extensions

(1)

It provides an engaged community

(1)

It connects with other languages

(1)

Looking At Some of the Unique Features of R

(4)

Performing multiple calculations with vectors

(1)

Processing more than just statistics

(1)

Running code without a compiler

(3)

Chapter 2 Exploring R

(16)

Working with a Code Editor

(5)

Exploring RGui

(2)

Dressing up with RStudio

(2)

Starting Your First R Session

(4)

Saying hello to the world

(1)

Doing simple math

(1)

Using vectors

(1)

Storing and calculating values

(1)

Talking back to the user

(1)

Sourcing a Script

(3)

Echoing your work

(2)

Navigating the Environment

(3)

Manipulating the content of the environment

(1)

Saving your work

(1)

Retrieving your work

(1)

Chapter 3 The Fundamentals of R

(14)

Using the Full Power of Functions

(5)

Vectorizing your functions

(1)

Putting the argument in a function

(2)

Making history

(1)

Keeping Your Code Readable

(5)

Following naming conventions

(3)

Structuring your code

(2)

Adding comments

(1)

Getting from Base R to More

(6)

Finding packages

(1)

Installing packages

(1)

Loading and unloading packages

(3)

Part II: Getting Down to Work in R

(100)

Chapter 4 Getting Started with Arithmetic

(28)

Working with Numbers, Infinity, and Missing Values

(9)

Doing basic arithmetic

(2)

Using mathematical functions

(3)

Calculating whole vectors

(1)

To infinity and beyond

(2)

Organizing Data in Vectors

(5)

Discovering the properties of vectors

(2)

Creating vectors

(1)

Combining vectors

(1)

Repeating vectors

(1)

Getting Values in and out of Vectors

(3)

Understanding indexing in R

(1)

Extracting values from a vector

(1)

Changing values in a vector

(1)

Working with Logical Vectors

(5)

Comparing values

(1)

Using logical vectors as indices

(1)

Combining logical statements

(1)

Summarizing logical vectors

(1)

Powering Up Your Math

(6)

Using arithmetic vector operations

(3)

Recycling arguments

(3)

Chapter 5 Getting Started with Reading and Writing

(24)

Using Character Vectors for Text Data

(5)

Assigning a value to a character vector

(1)

Creating a character vector with more than one element

(1)

Extracting a subset of a vector

(1)

Naming the values in your vectors

(2)

Manipulating Text

(10)

String theory: Combining and splitting strings

(4)

Sorting text

(1)

Finding text inside text

(2)

Substituting text

(1)

Revving up with regular expressions

(2)

Factoring in Factors

(9)

Creating a factor

(1)

Converting a factor

(2)

Looking at levels

(1)

Distinguishing data types

(1)

Working with ordered factors

100

(3)

Chapter 6 Going on a Date with R

103

(10)

Working with Dates

104

(2)

Presenting Dates in Different Formats

106

(1)

Adding Time Information to Dates

107

(2)

Formatting Dates and Times

109

(1)

Performing Operations on Dates and Times

109

(4)

Addition and subtraction

109

(1)

Comparison of dates

110

(1)

Extraction

111

(2)

Chapter 7 Working in More Dimensions

113

(36)

Adding a Second Dimension

113

(5)

Discovering a new dimension

114

(3)

Combining vectors into a matrix

117

(1)

Using the Indices

118

(3)

Extracting values from a matrix

118

(2)

Replacing values in a matrix

120

(1)

Naming Matrix Rows and Columns

121

(2)

Changing the row and column names

122

(1)

Using names as indices

123

(1)

Calculating with Matrices

123

(4)

Using standard operations with matrices

124

(1)

Calculating row and column summaries

125

(1)

Doing matrix arithmetic

126

(1)

Adding More Dimensions

127

(3)

Creating an array

128

(1)

Using dimensions to extract values

129

(1)

Combining Different Types of Values in a Data Frame

130

(4)

Creating a data frame from a matrix

130

(2)

Creating a data frame from scratch

132

(1)

Naming variables and observations

133

(1)

Manipulating Values in a Data Frame

134

(6)

Extracting variables, observations, and values

135

(1)

Adding observations to a data frame

136

(3)

Adding variables to a data frame

139

(1)

Combining Different Objects in a List

140

(11)

Creating a list

141

(1)

Extracting components from lists

142

(2)

Changing the components in lists

144

(2)

Reading the output of str() for lists

146

(2)

Seeing the forest through the trees

148

(1)

Part III: Coding in R

149

(70)

Chapter 8 Putting the Fun in Functions

151

(20)

Moving from Scripts to Functions

151

(6)

Making the script

152

(1)

Transforming the script

153

(1)

Using the function

154

(1)

Reducing the number of lines

155

(2)

Using Arguments the Smart Way

157

(6)

Adding more arguments

157

(2)

Conjuring tricks with dots

159

(2)

Using functions as arguments

161

(2)

Coping with Scoping

163

(2)

Crossing the borders

164

(1)

Dispatching to a Method

165

(6)

Finding the methods behind the function

166

(2)

Doing it yourself

168

(3)

Chapter 9 Controlling the Logical Flow

171

(22)

Making Choices with if Statements

172

(2)

Doing Something Else with an if...else Statement

174

(2)

Vectorizing Choices

176

(2)

Looking at the problem

176

(1)

Choosing based on a logical vector

176

(2)

Making Multiple Choices

178

(3)

Chaining if...else statements

178

(2)

Switching between possibilities

180

(1)

Looping Through Values

181

(3)

Constructing a for loop

181

(1)

Calculating values in a for loop

182

(2)

Looping without Loops: Meeting the Apply Family

184

(9)

Looking at the family features

185

(1)

Meeting three of the, members

185

(1)

Applying functions on rows and columns

186

(2)

Applying functions to listlike objects

188

(5)

Chapter 10 Debugging Your Code

193

(16)

Knowing What to Look For

193

(1)

Reading Errors and Warnings

194

(3)

Reading error messages

194

(1)

Caring about warnings (or not)

195

(2)

Going Bug Hunting

197

(5)

Calculating the logit

197

(1)

Knowing where an error comes from

197

(1)

Looking inside a function

198

(4)

Generating Your Own Messages

202

(2)

Creating errors

203

(1)

Creating warnings

203

(1)

Recognizing the Mistakes You're Sure to Make

204

(5)

Starting with the wrong data

204

(1)

Having your data in the wrong format

205

(4)

Chapter 11 Getting Help

209

(10)

Finding Information in the R Help Files

209

(3)

When you know exactly what you're looking for

210

(1)

When you don't know exactly what you're looking for

211

(1)

Searching the Web for Help with R

212

(1)

Getting Involved in the R Community

213

(2)

Discussing R on Stack Overflow and Stack Exchange

213

(1)

Using the R mailing lists

214

(1)

Tweeting about R

215

(1)

Making a Minimal Reproducible Example

215

(6)

Creating sample data with random values

215

(2)

Producing minimal code

217

(1)

Providing the necessary information

217

(2)

Part Ilk Making the Data Talk

219

(106)

Chapter 12 Getting Data into and out of R

221

(18)

Getting Data into R

221

(11)

Entering data in the R text editor

222

(1)

Using the Clipboard to copy and paste

223

(2)

Reading data in CSV files

225

(4)

Reading data from Excel

229

(1)

Working with other data types

230

(2)

Getting Your Data out of R

232

(1)

Working with Files and Folders

233

(6)

Understanding the working directory

233

(1)

Manipulating files

234

(5)

Chapter 13 Manipulating and Processing Data

239

(36)

Deciding on the Most Appropriate Data Structure

239

(2)

Creating Subsets of Your Data

241

(6)

Understanding the three subset operators

241

(1)

Understanding the five ways of specifying the subset

242

(1)

Subsetting data frames

242

(5)

Adding Calculated Fields to Data

247

(4)

Doing arithmetic on columns of a data frame

247

(1)

Using with and transform to improve code readability

248

(1)

Creating subgroups or bins of data

249

(2)

Combining and Merging Data Sets

251

(6)

Creating sample data to illustrate merging

252

(1)

Using the merge() function

253

(2)

Working with lookup tables

255

(2)

Sorting and Ordering Data

257

(3)

Sorting vectors

257

(1)

Sorting data frames

258

(2)

Traversing Your Data with the Apply Functions

260

(6)

Using the apply() function to summarize arrays

261

(2)

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

263

(1)

Using tapply() to create tabular summaries

264

(2)

Getting to Know the Formula Interface

266

(2)

Whipping Your Data into Shape

268

(7)

Understanding data in long and wide formats

269

(1)

Getting started with the reshape2 package

270

(1)

Melting data to long format

270

(1)

Casting data to wide format

271

(4)

Chapter 14 Summarizing Data

275

(24)

Starting with the Right Data

275

(3)

Using factors or numeric data

276

(1)

Counting unique values

277

(1)

Preparing the data

277

(1)

Describing Continuous Variables

278

(3)

Talking about the center of your data

278

(1)

Describing the variation

279

(1)

Checking the quantiles

279

(2)

Describing Categories

281

(2)

Counting appearances

281

(1)

Calculating proportions

282

(1)

Finding the center

282

(1)

Describing Distributions

283

(4)

Plotting histograms

283

(2)

Using frequencies or densities

285

(2)

Describing Multiple Variables

287

(6)

Summarizing a complete dataset

287

(1)

Plotting quantiles for subgroups

288

(2)

Tracking correlations

290

(3)

Working with Tables

293

(6)

Creating a two-way table

294

(1)

Converting tables to a data frame

295

(1)

Looking at margins and proportions

296

(3)

Chapter 15 Testing Differences and Relations

299

(26)

Taking a Closer Look at Distributions

300

(5)

Observing beavers

300

(1)

Testing normality graphically

301

(1)

Using quantile plots

302

(2)

Testing normality in a formal way

304

(1)

Comparing Two Samples

305

(4)

Testing differences

305

(3)

Comparing paired data

308

(1)

Testing Counts and Proportions

309

(4)

Checking out proportions

309

(1)

Analyzing tables

310

(2)

Extracting test results

312

(1)

Working with Models

313

(14)

Analyzing variances

313

(2)

Evaluating the differences

315

(3)

Modeling linear relations

318

(2)

Evaluating linear models

320

(3)

Predicting new values

323

(2)

Part V: Working With Graphics

325

(50)

Chapter 16 Using Base Graphics

327

(16)

Creating Different Types of Plots

327

(7)

Getting an overview of plot

328

(1)

Adding points and lines to a plot

329

(3)

Different plot types

332

(2)

Controlling Plot Options and Arguments

334

(6)

Adding titles and axis labels

335

(1)

Changing plot options

335

(4)

Putting multiple plots on a single page

339

(1)

Saving Graphics to Image Files

340

(3)

Chapter 17 Creating Faceted Graphics with Lattice

343

(18)

Creating a Lattice Plot

344

(4)

Loading the lattice package

345

(1)

Making a lattice scatterplot

345

(1)

Adding trend lines

346

(2)

Changing Plot Options

348

(3)

Adding titles and labels

348

(1)

Changing the font size of titles and labels

349

(1)

Using themes to modify plot options

350

(1)

Plotting Different Types

351

(3)

Making a bar chart

352

(1)

Making a box-and-whisker plot

353

(1)

Plotting Data in Groups

354

(3)

Using data in tall format

354

(2)

Creating a chart with groups

356

(1)

Adding a key

356

(1)

Printing and Saving a Lattice Plot

357

(4)

Assigning a lattice plot to an object

358

(1)

Printing a lattice plot in a script

358

(1)

Saving a lattice plot to file

358

(3)

Chapter 18 Looking At ggplot2 Graphics

361

(14)

Installing and Loading ggplot2

361

(1)

Looking At Layers

362

(1)

Using Geoms and Stats

363

(6)

Defining what data to use

364

(1)

Mapping data to plot aesthetics

364

(1)

Getting geoms

365

(4)

Sussing Stats

369

(2)

Adding Facets, Scales, and Options

371

(3)

Adding facets

371

(1)

Changing options

372

(2)

Getting More Information

374

(1)

Part VI: The Part of Tens

375

(20)

Chapter 19 Ten Things You Can Do in R That You Would've Done in Microsoft Excel

377

(10)

Adding Row and Column Totals

377

(1)

Formatting Numbers

378

(2)

Sorting Data

380

(1)

Making Choices with If

380

(1)

Calculating Conditional Totals

381

(1)

Transposing Columns or Rows

382

(1)

Finding Unique or Duplicated Values

383

(1)

Working with Lookup Tables

383

(1)

Working with Pivot Tables

384

(1)

Using the Goal Seek and Solver

385

(2)

Chapter 20 Ten Tips on Working with Packages

387

(8)

Poking Around the Nooks and Crannies of CRAN

387

(1)

Finding Interesting Packages

388

(1)

Installing Packages

389

(1)

Loading Packages

389

(1)

Reading the Package Manual and Vignette

390

(1)

Updating Packages

390

(1)

Forging Ahead with R-Forge

391

(1)

Getting packages from github

392

(1)

Conducting Installations from BioConductor

392

(1)

Reading the R Manual

393

(2)

Appendix A: Installing R and RStudio

395

(6)

Installing and Configuring R

395

(3)

Installing R

395

(1)

Configuring R

396

(2)

Installing and Configuring RStudio

398

(3)

Installing RStudio

398

(1)

Configuring RStudio

398

(3)

Appendix B: The rfordummies Package

401

(2)

Using rfordummies

401

(2)

Index

403

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.

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