R in 24 Hours, Sams Teach Yourself

In just 24 lessons of one hour or less, Sams Teach Yourself R in 24 Hours helps you learn all the R skills you need to solve a wide spectrum of real-world data analysis problems. You'll master the entire data analysis workflow, learning to build code that's efficient, reproducible, and suitable for sharing with others.

Preface xiiHOUR 1: The R Community 1A Concise History of R 1The R Community 3R Development 7Summary 8Q&A 8Workshop 9Activities 9HOUR 2: The R Environment 11Integrated Development Environments 11R Syntax 14R Objects 16Using R Packages 23Internal Help 28Summary 29Q&A 30Workshop 30Activities 32HOUR 3: Single-Mode Data Structures 33The R Data Types 33Vectors, Matrices, and Arrays 34Vectors 35Matrices 49Arrays 58Relationship Between Single-Mode Data Objects 60Summary 62Q&A 62Workshop 63Activities 64HOUR 4: Multi-Mode Data Structures 67Multi-Mode Structures 67Lists 68Data Frames 86Exploring Your Data 93Summary 98Q&A 98Workshop 100Activities 101HOUR 5: Dates, Times, and Factors 103Working with Dates and Times 103The lubridate Package 107Working with Categorical Data 108Summary 112Q&A 112Workshop 113Activities 114HOUR 6: Common R Utility Functions 115Using R Functions 115Functions for Numeric Data 117Logical Data 121Missing Data 122Character Data 123Summary 125Q&A 126Workshop 126Activities 127HOUR 7: Writing Functions: Part I 129The Motivation for Functions 129Creating a Simple Function 130The If/Else Structure 136Summary 146Q&A 147Workshop 148Activities 149HOUR 8: Writing Functions: Part II 151Errors and Warnings 151Checking Inputs 155The Ellipsis 157Checking Multivalue Inputs 162Using Input Definition 164Summary 168Q&A 168Workshop 170Activities 171HOUR 9: Loops and Summaries 173Repetitive Tasks 173The "apply" Family of Functions 181The apply Function 183The lapply Function 195The sapply Function 204The tapply Function 208Summary 213Q&A 213Workshop 214Activities 216HOUR 10: Importing and Exporting 217Working with Text Files 217Relational Databases 223Working with Microsoft Excel 226Summary 231Q&A 232Workshop 232Activities 233HOUR 11: Data Manipulation and Transformation 235Sorting 236Appending 237Merging 238Duplicate Values 241Restructuring 242Data Aggregation 249Summary 258Q&A 258Workshop 259Activities 259HOUR 12: Efficient Data Handling in R 261dplyr: A New Way of Handling Data 261Efficient Data Handling with data table 273Summary 282Q&A 283Workshop 283Activities 284HOUR 13: Graphics 287Graphics Devices and Colors 287High-Level Graphics Functions 289Low-Level Graphics Functions 298Graphical Parameters 304Controlling the Layout 305Summary 308Q&A 309Workshop 309Activities 311HOUR 14: The ggplot2 Package for Graphics 313The Philosophy of ggplot2 313Quick Plots and Basic Control 314Changing Plot Types 317Aesthetics 320Paneling (a k a Faceting) 328Custom Plots 333Themes and Layout 338The ggvis Evolution 342Summary 342Q&A 343Workshop 343Activities 344HOUR 15: Lattice Graphics 345The History of Trellis Graphics 345The Lattice Package 346Creating a Simple Lattice Graph 346Graph Options 356Multiple Variables 358Groups of Data 360Using Panels 362Controlling Styles 372Summary 376Q&A 377Workshop 378Activities 378HOUR 16: Introduction to R Models and Object Orientation 379Statistical Models in R 379Simple Linear Models 380Assessing a Model in R 382Multiple Linear Regression 391Interaction Terms 396Factor Independent Variables 398Variable Transformations 402R and Object Orientation 405Summary 407Q&A 408Workshop 408Activities 409HOUR 17: Common R Models 411Generalized Linear Models 411Nonlinear Models 423Survival Analysis 430Time Series Analysis 441Summary 452Q&A 452Workshop 452Activities 453HOUR 18: Code Efficiency 455Determining Efficiency 455Initialization 458Vectorization 459Using Alternative Functions 462Managing Memory Usage 463Integrating with C++ 464Summary 468Q&A 469Workshop 469Activities 470HOUR 19: Package Building 471Why Build an R Package? 471The Structure of an R Package 472Code Quality 476Automated Documentation with roxygen2 477Building a Package with devtools 482Summary 485Q&A 485Workshop 486Activities 487HOUR 20: Advanced Package Building 489Extending R Packages 489Developing a Test Framework 490Including Data in Packages 494Including a User Guide 496Code Using Rcpp 501Summary 502Q&A 502Workshop 503Activities 504HOUR 21: Writing R Classes 505What Is a Class? 505Creating a New S3 Class 509Generic Functions and Methods 511Inheritance in S3 516Documenting S3 518Limitations of S3 518Summary 519Q&A 519Workshop 520Activities 520HOUR 22: Formal Class Systems 523S4 523Reference Classes 535R6 Classes 542Other Class Systems 544Summary 544Q&A 545Workshop 545Activities 546HOUR 23: Dynamic Reporting 547What Is Dynamic Reporting? 547An Introduction to knitr 548Simple Reports with RMarkdown 548Reporting with LaTeX 553Summary 557Q&A 558Workshop 558Activities 559HOUR 24: Building Web Applications with Shiny 561A Simple Shiny Application 561Reactive Functions 566Interactive Documents 569Sharing Shiny Applications 570Summary 571Q&A 571Workshop 571Activities 572APPENDIX: Installation 573Installing R 573Installing Rtools for Windows 575Installing the RStudio IDE 577Index 579