Kieran Healy is associate professor of sociology at Duke University. He is the author of Last Best Gifts: Altruism and the Market for Human Blood and Organs.

"[Healy’s] prose is engaging and chatty, and the style of instruction is unpretentious and practical . . . This single volume represents an excellent entry point for those wishing to upskill their abilities in data visualization."---Paul Cuffe, IEEE Transactions

• PrefaceWhat You Will LearnThe Right Frame of MindHow to Use This BookConventionsBefore You Begin1 Look at Data1.1 Why Look at Data?1.2 What Makes Bad Figures Bad?1.3 Perception and Data Visualization1.4 Visual Tasks and Decoding Graphs1.5 Channels for Representing Data1.6 Problems of Honesty and Good Judgment1.7 Think Clearly about Graphs1.8 Where to Go Next2 Get Started2.1 Work in Plain Text, Using RMarkdown2.2 Use R with RStudio2.3 Things to Know about R2.4 Be Patient with R, and with Yourself2.5 Get Data into R2.6 Make Your First Figure2.7 Where to Go Next3 Make a Plot3.1 How Ggplot Works3.2 Tidy Data3.3 Mappings Link Data to Things You See3.4 Build Your Plots Layer by Layer3.5 Mapping Aesthetics vs Setting Them3.6 Aesthetics Can Be Mapped per Geom3.7 Save Your Work3.8 Where to Go Next4 Show the Right Numbers4.1 Colorless Green Data Sleeps Furiously4.2 Grouped Data and the “Group” Aesthetic4.3 Facet to Make Small Multiples4.4 Geoms Can Transform Data4.5 Frequency Plots the Slightly Awkward Way4.6 Histograms and Density Plots4.7 Avoid Transformations When Necessary4.8 Where to Go Next5 Graph Tables, Add Labels, Make Notes5.1 Use Pipes to Summarize Data5.2 Continuous Variables by Group or Category5.3 Plot Text Directly5.4 Label Outliers5.5 Write and Draw in the Plot Area5.6 Understanding Scales, Guides, and Themes5.7 Where to Go Next6 Work with Models6.1 Show Several Fits at Once, with a Legend6.2 Look Inside Model Objects6.3 Get Model-Based Graphics Right6.4 Generate Predictions to Graph6.5 Tidy Model Objects with Broom6.6 Grouped Analysis and List Columns6.7 Plot Marginal Effects6.8 Plots from Complex Surveys6.9 Where to Go Next7 Draw Maps7.1 Map U.S. State-Level Data7.2 America’s Ur-choropleths7.3 Statebins7.4 Small-Multiple Maps7.5 Is Your Data Really Spatial?7.6 Where to Go Next8 Refine Your Plots8.1 Use Color to Your Advantage8.2 Layer Color and Text Together8.3 Change the Appearance of Plots with Themes8.4 Use Theme Elements in a Substantive Way8.5 Case Studies8.6 Where to Go NextAcknowledgmentsAppendix1 A Little More about R2 Common Problems Reading in Data3 Managing Projects and Files4 Some Features of This BookReferencesIndex

Kieran Healy is associate professor of sociology at Duke University. He is the author of Last Best Gifts: Altruism and the Market for Human Blood and Organs.

"[Healy’s] prose is engaging and chatty, and the style of instruction is unpretentious and practical . . . This single volume represents an excellent entry point for those wishing to upskill their abilities in data visualization."---Paul Cuffe, IEEE Transactions

• PrefaceWhat You Will LearnThe Right Frame of MindHow to Use This BookConventionsBefore You Begin1 Look at Data1.1 Why Look at Data?1.2 What Makes Bad Figures Bad?1.3 Perception and Data Visualization1.4 Visual Tasks and Decoding Graphs1.5 Channels for Representing Data1.6 Problems of Honesty and Good Judgment1.7 Think Clearly about Graphs1.8 Where to Go Next2 Get Started2.1 Work in Plain Text, Using RMarkdown2.2 Use R with RStudio2.3 Things to Know about R2.4 Be Patient with R, and with Yourself2.5 Get Data into R2.6 Make Your First Figure2.7 Where to Go Next3 Make a Plot3.1 How Ggplot Works3.2 Tidy Data3.3 Mappings Link Data to Things You See3.4 Build Your Plots Layer by Layer3.5 Mapping Aesthetics vs Setting Them3.6 Aesthetics Can Be Mapped per Geom3.7 Save Your Work3.8 Where to Go Next4 Show the Right Numbers4.1 Colorless Green Data Sleeps Furiously4.2 Grouped Data and the “Group” Aesthetic4.3 Facet to Make Small Multiples4.4 Geoms Can Transform Data4.5 Frequency Plots the Slightly Awkward Way4.6 Histograms and Density Plots4.7 Avoid Transformations When Necessary4.8 Where to Go Next5 Graph Tables, Add Labels, Make Notes5.1 Use Pipes to Summarize Data5.2 Continuous Variables by Group or Category5.3 Plot Text Directly5.4 Label Outliers5.5 Write and Draw in the Plot Area5.6 Understanding Scales, Guides, and Themes5.7 Where to Go Next6 Work with Models6.1 Show Several Fits at Once, with a Legend6.2 Look Inside Model Objects6.3 Get Model-Based Graphics Right6.4 Generate Predictions to Graph6.5 Tidy Model Objects with Broom6.6 Grouped Analysis and List Columns6.7 Plot Marginal Effects6.8 Plots from Complex Surveys6.9 Where to Go Next7 Draw Maps7.1 Map U.S. State-Level Data7.2 America’s Ur-choropleths7.3 Statebins7.4 Small-Multiple Maps7.5 Is Your Data Really Spatial?7.6 Where to Go Next8 Refine Your Plots8.1 Use Color to Your Advantage8.2 Layer Color and Text Together8.3 Change the Appearance of Plots with Themes8.4 Use Theme Elements in a Substantive Way8.5 Case Studies8.6 Where to Go NextAcknowledgmentsAppendix1 A Little More about R2 Common Problems Reading in Data3 Managing Projects and Files4 Some Features of This BookReferencesIndex

Kieran Healy is associate professor of sociology at Duke University. He is the author of Last Best Gifts: Altruism and the Market for Human Blood and Organs.

"[Healy’s] prose is engaging and chatty, and the style of instruction is unpretentious and practical . . . This single volume represents an excellent entry point for those wishing to upskill their abilities in data visualization."---Paul Cuffe, IEEE Transactions

• PrefaceWhat You Will LearnThe Right Frame of MindHow to Use This BookConventionsBefore You Begin1 Look at Data1.1 Why Look at Data?1.2 What Makes Bad Figures Bad?1.3 Perception and Data Visualization1.4 Visual Tasks and Decoding Graphs1.5 Channels for Representing Data1.6 Problems of Honesty and Good Judgment1.7 Think Clearly about Graphs1.8 Where to Go Next2 Get Started2.1 Work in Plain Text, Using RMarkdown2.2 Use R with RStudio2.3 Things to Know about R2.4 Be Patient with R, and with Yourself2.5 Get Data into R2.6 Make Your First Figure2.7 Where to Go Next3 Make a Plot3.1 How Ggplot Works3.2 Tidy Data3.3 Mappings Link Data to Things You See3.4 Build Your Plots Layer by Layer3.5 Mapping Aesthetics vs Setting Them3.6 Aesthetics Can Be Mapped per Geom3.7 Save Your Work3.8 Where to Go Next4 Show the Right Numbers4.1 Colorless Green Data Sleeps Furiously4.2 Grouped Data and the “Group” Aesthetic4.3 Facet to Make Small Multiples4.4 Geoms Can Transform Data4.5 Frequency Plots the Slightly Awkward Way4.6 Histograms and Density Plots4.7 Avoid Transformations When Necessary4.8 Where to Go Next5 Graph Tables, Add Labels, Make Notes5.1 Use Pipes to Summarize Data5.2 Continuous Variables by Group or Category5.3 Plot Text Directly5.4 Label Outliers5.5 Write and Draw in the Plot Area5.6 Understanding Scales, Guides, and Themes5.7 Where to Go Next6 Work with Models6.1 Show Several Fits at Once, with a Legend6.2 Look Inside Model Objects6.3 Get Model-Based Graphics Right6.4 Generate Predictions to Graph6.5 Tidy Model Objects with Broom6.6 Grouped Analysis and List Columns6.7 Plot Marginal Effects6.8 Plots from Complex Surveys6.9 Where to Go Next7 Draw Maps7.1 Map U.S. State-Level Data7.2 America’s Ur-choropleths7.3 Statebins7.4 Small-Multiple Maps7.5 Is Your Data Really Spatial?7.6 Where to Go Next8 Refine Your Plots8.1 Use Color to Your Advantage8.2 Layer Color and Text Together8.3 Change the Appearance of Plots with Themes8.4 Use Theme Elements in a Substantive Way8.5 Case Studies8.6 Where to Go NextAcknowledgmentsAppendix1 A Little More about R2 Common Problems Reading in Data3 Managing Projects and Files4 Some Features of This BookReferencesIndex