Hadley Wickham is Chief Scientist at RStudio, an Adjunct Professor at Stanford University and the University of Auckland, and a member of the R Foundation. He is the lead developer of the tidyverse, a collection of R packages, including ggplot2 and dplyr, designed to support data science. He is also the author of R for Data Science (with Garrett Grolemund), R Packages, and ggplot2: elegant graphics for data analysis.

IntroductionWhy R?Who should read this bookWhat you will get out of this bookWhat you will not learnMeta-techniquesRecommended readingGetting helpAcknowledgmentsConventionsColophonI FoundationsIntroductionNames and valuesIntroductionBinding basicsCopy-on-modifyObject sizeModify-in-placeUnbinding and the garbage collectorAnswersVectorsIntroductionAtomic vectorsAttributesS atomic vectorsListsData frames and tibblesNULLAnswersSubsettingIntroductionSelecting multiple elementsSelecting a single elementSubsetting and assignmentApplicationsAnswersControl flowIntroductionChoicesLoopsAnswersFunctionsIntroductionFunction fundamentalsFunction compositionLexical scopingLazy evaluation(dot-dot-dot)Exiting a functionFunction formsQuiz answersEnvironmentsIntroductionEnvironment basicsRecursing over environmentsSpecial environmentsThe call stackAs data structuresQuiz answersConditionsIntroductionSignalling conditionsIgnoring conditionsHandling conditionsCustom conditionsApplicationsQuiz answersII Functional programmingIntroductionFunctionalsIntroductionMy first functional: map()Purrr styleMap variantsReducePredicate functionalsBase functionalsFunction factoriesIntroductionFactory fundamentalsGraphical factoriesStatistical factoriesFunction factories + functionalsFunction operatorsIntroductionExisting function operatorsCase study: creating your own function operatorsIII Object oriented programmingIntroductionBase typesIntroductionBase vs OO objectsBase typesS3IntroductionBasicsClassesGenerics and methodsObject stylesInheritanceDispatch detailsR6IntroductionClasses and methodsControlling accessReference semanticsWhy R?S4IntroductionBasicsClassesGenerics and methodsMethod dispatchS and STrade-offsIntroductionS vs SR vs SIV MetaprogrammingIntroductionBig pictureIntroductionCode is dataCode is a treeCode can generate codeEvaluation runs codeCustomising evaluation with functionsCustomising evaluation with dataQuosuresExpressionsIntroductionAbstract syntax treesExpressionsParsing and grammarWalking the AST with recursive functionsSpecialised data structuresQuasiquotationIntroductionMotivationQuotingUnquotingNon-quotingDot-dot-dot ()Case studiesHistoryEvaluationIntroductionEvaluation basicsQuosuresData masksUsing tidy evaluationBase evaluationTranslating R codeIntroductionHTMLLaTeXV TechniquesIntroductionDebuggingIntroductionOverall approachLocate the errorThe interactive debuggerNon-interactive debuggingNon-error failuresMeasuring performanceIntroductionProfilingMicrobenchmarkingImproving performanceIntroductionCode organisationCheck for existing solutionsDo as little as possibleVectoriseAvoid copiesCase study: t-testOther techniquesRewriting R code in C++IntroductionGetting started with C++Other classesMissing valuesThe STLCase studiesUsing Rcpp in a packageLearning moreAcknowledgments

Advanced R helps you understand how R works at a fundamental level. It is designed for R programmers who want to deepen their understanding of the language, and programmers experienced in other languages who want to understand what makes R different and special. This book will teach you the foundations of R; three fundamental programming paradigms (functional, object-oriented, and metaprogramming); and powerful techniques for debugging and optimisingyour code.By reading this book, you will learn: The difference between an object and its name, and why the distinction is important The important vector data structures, how they fit together, and how you can pull them apart using subsetting The fine details of functions and environments The condition system, which powers messages, warnings, and errors The powerful functional programming paradigm, which can replace many for loops The three most important OO systems: S3, S4, and R6 The tidy eval toolkit for metaprogramming, which allows you to manipulate code and control evaluation Effective debugging techniques that you can deploy, regardless of how your code is run How to find and remove performance bottlenecks The second edition is a comprehensive update: New foundational chapters: "Names and values," "Control flow," and "Conditions" comprehensive coverage of object oriented programming with chapters on S3, S4, R6, and how to choose between them Much deeper coverage of metaprogramming, including the new tidy evaluation framework use of new package like rlang , which provides a clean interface to low-level operations, and purr for functional programming Use of color in code chunks and figuresHadley Wickham is Chief Scientist at RStudio, an Adjunct Professor at Stanford University and the University of Auckland, and a member of the R Foundation. He is the lead developer of the tidyverse, a collection of R packages, including ggplot2 and dplyr, designed to support data science. He is also the author of R for Data Science (with Garrett Grolemund), R Packages, and ggplot2: Elegant Graphics for Data Analysis.