book

Learning R Programming

by Kun Ren

October 2016

Beginner to intermediate

582 pages

11h 26m

English

Packt Publishing

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What this book covers

Downloading the example codeErrataPiracyQuestions
Introducing RR as a programming languageR as a computing environmentR as a communityR as an ecosystem
RStudio's user interfaceThe consoleThe editorThe Environment paneThe History paneThe File paneThe Plots paneThe Packages paneThe Help paneThe Viewer paneRStudio Server
VectorNumeric vectorLogical vectorCharacter vectorSubsetting vectorsNamed vectorsExtracting an elementTelling the class of vectorsConverting vectorsArithmetic operators for numeric vectors
Creating a matrixNaming rows and columnsSubsetting a matrixUsing matrix operators
Creating an arraySubsetting an array
Creating a listExtracting an element from a listSubsetting a listNamed listsSetting valuesOther functions
Creating a data frameNaming rows and columnsSubsetting a data frameSubsetting a data frame as a listSubsetting a data frame as a matrixFiltering dataSetting valuesSetting values as a listSetting values as a matrixFactorsUseful functions for data framesLoading and writing data on disk
Creating a functionCalling a functionDynamic typingGeneralizing a functionDefault value for function arguments
R's working directoryCreating an R project in RStudioComparing absolute and relative pathsManaging project files
Inspecting existing symbolsViewing the structure of an objectRemoving symbols
Modifying the number of digits to printModifying the warning level
Getting to know a packageInstalling packages from CRANUpdating packages from CRANInstalling packages from online repositoriesUsing package functionsMasking and name conflictsChecking whether a package is installed
Assignment expressionsAlternative assignment operatorsUsing backticks with non-standard names
Using if as a statementUsing if as an expressionUsing if with vectorsUsing vectorized if: ifelseUsing switch to branch values
Using the for loopManaging the flow of a for loopCreating nested for loopsUsing the while loop
Using object functionsTesting object typesAccessing object classes and typesAccessing data dimensionsGetting data dimensionsReshaping data structuresIterating over one dimension
Logical operatorsLogical functionsAggregating logical vectorsAsking which elements are TRUEDealing with missing valuesLogical coercion
Basic functionsNumber rounding functionsTrigonometric functionsHyperbolic functionsExtreme functions
Root findingCalculusDerivativesIntegration
Sampling from a vectorWorking with random distributionsComputing summary statisticsComputing covariance and correlation matrix
lapplysapplyvapplymapplyapply
Getting started with stringsPrinting textsConcatenating stringsTransforming textsChanging casesCounting charactersTrimming leading and trailing whitespacesSubstringSplitting textsFormatting textsUsing Python string functions in R
Parsing text as date/timeFormatting date/time to strings
Finding a string patternUsing groups to extract the dataReading data in customizable ways
Reading and writing dataReading and writing text-format data in a fileImporting data via RStudio IDEImporting data using built-in functionsImporting data using the readr packageWriting a data frame to a fileReading and writing Excel worksheetsReading and writing native data filesReading and writing a single object in native formatSaving and restoring the working environmentLoading built-in datasets
Creating scatter plotsCustomizing chart elementsCustomizing point stylesCustomizing point colorsCreating line plotsCustomizing line type and widthPlotting lines in multiple periodsPlotting lines with pointsPlotting a multi-series chart with a legendCreating bar chartsCreating pie chartsCreating histogram and density plotsCreating box plots
Fitting a linear modelFitting a regression tree
Understanding lazy evaluation
Modifying objects outside a function
Knowing the environment objectCreating and chaining environmentsAccessing an environmentChaining environmentsUsing environments for reference semanticsKnowing the built-in environmentsUnderstanding environments associated with a function
Understanding functional programmingCreating and using closuresCreating a simple closureMaking specialized functionsFitting normal distribution with maximal likelihood estimationUsing higher-order functionsCreating aliases for functionsUsing functions as variablesPassing functions as arguments
Capturing and modifying expressionsCapturing expressions as language objectsModifying expressionsCapturing expressions of function argumentsConstructing function callsEvaluating expressionsUnderstanding non-standard evaluationImplementing quick subsetting using non-standard evaluationUnderstanding dynamic scopingUsing formulas to capture expression and environmentImplementing subset with metaprogramming
Introducing object-oriented programmingUnderstanding classes and methodsUnderstanding inheritance
Understanding generic functions and method dispatchWorking with built-in classes and methodsDefining generic functions for existing classesCreating objects of new classesUsing list as the underlying data structureUsing an atomic vector as the underlying data structureUnderstanding S3 inheritance
Defining S4 classesUnderstanding S4 inheritanceDefining S4 generic functionsUnderstanding multiple dispatch
Working with relational databasesCreating a SQLite databaseWriting multiple tables to a databaseAppending data to a tableAccessing tables and table fieldsLearning SQL to query relational databasesFetching query results chunk by chunkUsing transactions for consistencyStoring data in files to a database
Working with MongoDBQuerying data from MongoDBCreating and removing indexesUsing RedisAccessing Redis from RSetting and getting values from the Redis server
Using built-in functions to manipulate data framesUsing built-in functions to manipulate data framesReshaping data frames using reshape2
Using key to access rowsSummarizing data by groupsReshaping data.tableUsing in-place set functionsUnderstanding dynamic scoping of data.table
Understanding code performance issuesMeasuring code performance
Profiling code with RprofProfiling code with profvisUnderstanding why code can be slow
Using built-in functionsUsing vectorizationUsing byte-code compilerUsing Intel MKL-powered R distributionUsing parallel computingUsing parallel computing on WindowsUsing parallel computing on Linux and MacOSUsing RcppOpenMPRcppParallel
Looking inside web pages
Writing R Markdown documentsGetting to know markdownIntegrating R into MarkdownEmbedding tables and chartsEmbedding tablesEmbedding charts and diagramsEmbedding interactive plots
Creating a shiny appUsing shinydashboard

Overview

This book provides a comprehensive introduction to R programming, a powerful tool for data science and statistics. Throughout the book, readers will explore programming constructs, data structures, and popular R packages, gaining the skills needed for practical applications and problem-solving.

What this Book will help me do

Understand R's foundational concepts like variables, data types, and functions.
Learn how to use R for data analysis, visualization, and machine learning tasks.
Develop advanced R skills such as meta-programming and performance optimization.
Master object-oriented programming using R's S3, S4, and R6 systems.
Gain confidence in utilizing R for creating web scraping scripts and interactive reports.

Author(s)

None Ren, an experienced software developer and educator, specializes in languages for data analysis, including R. With years of practical experience and teaching R programming, they bring clarity and depth to complex topics. Their approachable writing style ensures learners at any level can engage effectively.

Who is it for?

This book is ideal for professionals in data science, statistics, and related fields with basic programming skills looking to delve into R programming. It caters to beginners and those consolidating their knowledge of R, aiming to develop practical skills for data manipulation and analysis.