Spis treści: „Data Visualization (a practical introduction)”

Spis treści publikacji pt. „Data Visualization (a practical introduction)”.

Tytuł: „Data Visualization (a practical introduction)”
Autor: Kieran Healy
Wydawca: Princeton University Press
Data wydania: 2019-01-01
Język: Angielski
Liczba stron: 296

Spis treści

Spis treści / Table of contents

Preface / XI

What YouWill Learn / XII

The Right Frame of Mind / XIV

How to Use This Book / XV

Conventions / XVI

Before You Begin / XVII

1. Look at Data / 1

1.1. Why Look at Data? / 2

1.2. What Makes Bad Figures Bad? / 5

1.3. Perception and Data Visualization / 14

1.4. Visual Tasks and Decoding Graphs / 23

1.5. Channels for Representing Data / 26

1.6. Problems of Honesty and Good Judgment / 27

1.7. Think Clearly about Graphs / 29

1.8. Where to Go Next / 31

2. Get Started / 32

2.1. Work in Plain Text, Using RMarkdown / 32

2.2. Use R with RStudio / 35

2.3. Things to Know about R / 38

2.4. Be Patient with R, and with Yourself / 48

2.5. Get Data into R / 49

2.6. Make Your First Figure / 51

2.7. Where to Go Next / 52

3. Make a Plot / 54

3.1. How GgplotWorks / 54

3.2. Tidy Data / 56

3.3. Mappings Link Data to Things You See / 56

3.4. Build Your Plots Layer by Layer / 59

3.5. Mapping Aesthetics vs Setting Them / 63

3.6. Aesthetics Can Be Mapped per Geom / 66

3.7. Save YourWork / 68

3.8. Where to Go Next / 71

4. Show the Right Numbers / 73

4.1. Colorless Green Data Sleeps Furiously / 74

4.2. Grouped Data and the “Group” Aesthetic / 74

4.3. Facet to Make Small Multiples / 76

4.4. Geoms Can Transform Data / 80

4.5. Frequency Plots the Slightly AwkwardWay / 82

4.6. Histograms and Density Plots / 85

4.7. Avoid TransformationsWhen Necessary / 88

4.8. Where to Go Next / 91

5. Graph Tables, Add Labels, Make Notes / 93

5.1. Use Pipes to Summarize Data / 94

5.2. Continuous Variables by Group or Category / 102

5.3. Plot Text Directly / 115

5.4. Label Outliers / 121

5.5. Write and Draw in the Plot Area / 124

5.6. Understanding Scales, Guides, and Themes / 125

5.7. Where to Go Next / 131

6. Work with Models / 134

6.1. Show Several Fits at Once, with a Legend / 135

6.2. Look Inside Model Objects / 137

6.3. Get Model-Based Graphics Right / 141

6.4. Generate Predictions to Graph / 143

6.5. Tidy Model Objects with Broom / 146

6.6. Grouped Analysis and List Columns / 151

6.7. Plot Marginal Effects / 157

6.8. Plots from Complex Surveys / 161

6.9. Where to Go Next / 168

7. Draw Maps / 173

7.1. Map U.S. State-Level Data / 175

7.2. America’s Ur-choropleths / 182

7.3. Statebins / 189

7.4. Small-Multiple Maps / 191

7.5. Is Your Data Really Spatial? / 194

7.6. Where to Go Next / 198

8. Refine Your Plots / 199

8.1. Use Color to Your Advantage / 201

8.2. Layer Color and Text Together / 205

8.3. Change the Appearance of Plots with Themes / 208

8.4. Use Theme Elements in a SubstantiveWay / 211

8.5. Case Studies / 215

8.6. Where to Go Next / 230

Acknowledgments / 233

Appendix / 235

1. A Little More about R / 235
2. Common Problems Reading in Data / 245
3. Managing Projects and Files / 253
4. Some Features of This Book / 257

References / 261

Index / 267

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