Description: PrefaceAbout the AuthorsIntroduction: Data Science, Many SkillsWhat Is Data Science?The Steps in Doing Data ScienceThe Skills Needed to Do Data ScienceChapter 1 * About DataStoring Data--Using Bits and BytesCombining Bytes Into Larger StructuresCreating a Data Set in RChapter 2 * Identifying Data ProblemsTalking to Subject Matter ExpertsLooking for the ExceptionExploring Risk and UncertaintyChapter 3 * Getting Started With RInstalling RUsing RCreating and Using VectorsChapter 4 * Follow the DataUnderstand Existing Data SourcesExploring Data ModelsChapter 5 * Rows and ColumnsCreating DataframesExploring DataframesAccessing Columns in a DataframeChapter 6 * Data MungingReading a CSV Text FileRemoving Rows and ColumnsRenaming Rows and ColumnsCleaning Up the ElementsSorting DataframesChapter 7 * Onward With RStudioUsing an Integrated Development EnvironmentInstalling RStudioCreating R ScriptsChapter 8 * What's My Function?Why Create and Use Functions?Creating Functions in RTesting FunctionsInstalling a Package to Access a FunctionChapter 9 * Beer, Farms, and Peas and the Use of StatisticsHistorical PerspectiveSampling a PopulationUnderstanding Descriptive StatisticsUsing Descriptive StatisticsUsing Histograms to Understand a DistributionNormal DistributionsChapter 10 * Sample in a JarSampling in RRepeating Our SamplingLaw of Large Numbers and the Central Limit TheoremComparing Two SamplesChapter 11 * Storage WarsImporting Data Using RStudioAccessing Excel DataAccessing a DatabaseComparing SQL and R for Accessing a Data SetAccessing JSON DataChapter 12 * Pictures Versus NumbersA Visualization OverviewBasic Plots in RUsing ggplot2More Advanced ggplot2 VisualizationsChapter 13 * Map MashupCreating Map Visualizations With ggplot2Showing Points on a MapA Map Visualization ExampleChapter 14 * Word PerfectReading in Text FilesUsing the Text Mining PackageCreating Word CloudsChapter 15 * Happy Words?Sentiment AnalysisOther Uses of Text MiningChapter 16 * Lining Up Our ModelsWhat Is a Model?Linear ModelingAn Example--Car MaintenanceChapter 17 * Hi Ho, Hi Ho--Data Mining We GoData Mining OverviewAssociation Rules DataAssociation Rules MiningExploring How the Association Rules Algorithm WorksChapter 18 * What's Your Vector, Victor?Supervised and Unsupervised LearningSupervised Learning via Support Vector MachinesSupport Vector Machines in RChapter 19 * Shiny Web AppsCreating Web Applications in RDeploying the ApplicationChapter 20 * Big Data? Big Deal!What Is Big Data?The Tools for Big DataIndex

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