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E-raamat: Data Visualization: A Practical Introduction

  • Formaat: 296 pages
  • Ilmumisaeg: 10-Sep-2024
  • Kirjastus: Princeton University Press
  • Keel: eng
  • ISBN-13: 9780691270845
  • Formaat - EPUB+DRM
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  • Formaat: 296 pages
  • Ilmumisaeg: 10-Sep-2024
  • Kirjastus: Princeton University Press
  • Keel: eng
  • ISBN-13: 9780691270845

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An accessible primer on how to create effective graphics from data

This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way.

Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible.

Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings.

  • Provides hands-on instruction using R and ggplot2
  • Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent
  • Includes a library of data sets, code, and functions

Arvustused

"[ Healys] 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 "Undoubtedly, this book is an excellent introduction to an essential tool for anyone who needs to collect and present data." * Conservation Biology *

Preface xi
What You Will 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(31)
1.1 Why Look at Data?
2(3)
1.2 What Makes Bad Figures Bad?
5(9)
1.3 Perception and Data Visualization
14(9)
1.4 Visual Tasks and Decoding Graphs
23(3)
1.5 Channels for Representing Data
26(1)
1.6 Problems of Honesty and Good Judgment
27(2)
1.7 Think Clearly about Graphs
29(2)
1.8 Where to Go Next
31(1)
2 Get Started
32(22)
2.1 Work in Plain Text, Using RMarkdown
32(3)
2.2 Use R with RStudio
35(3)
2.3 Things to Know about R
38(10)
2.4 Be Patient with R, and with Yourself
48(1)
2.5 Get Data into R
49(2)
2.6 Make Your First Figure
51(1)
2.7 Where to Go Next
52(2)
3 Make a Plot
54(19)
3.1 How Ggplot Works
54(2)
3.2 Tidy Data
56(1)
3.3 Mappings Link Data to Things You See
56(3)
3.4 Build Your Plots Layer by Layer
59(4)
3.5 Mapping Aesthetics vs Setting Them
63(3)
3.6 Aesthetics Can Be Mapped per Geom
66(2)
3.7 Save Your Work
68(3)
3.8 Where to Go Next
71(2)
4 Show the Right Numbers
73(20)
4.1 Colorless Green Data Sleeps Furiously
74(1)
4.2 Grouped Data and the "Group" Aesthetic
74(2)
4.3 Facet to Make Small Multiples
76(4)
4.4 Geoms Can Transform Data
80(2)
4.5 Frequency Plots the Slightly Awkward Way
82(3)
4.6 Histograms and Density Plots
85(3)
4.7 Avoid Transformations When Necessary
88(3)
4.8 Where to Go Next
91(2)
5 Graph Tables, Add Labels, Make Notes
93(41)
5.1 Use Pipes to Summarize Data
94(8)
5.2 Continuous Variables by Group or Category
102(13)
5.3 Plot Text Directly
115(6)
5.4 Label Outliers
121(3)
5.5 Write and Draw in the Plot Area
124(1)
5.6 Understanding Scales, Guides, and Themes
125(6)
5.7 Where to Go Next
131(3)
6 Work with Models
134(39)
6.1 Show Several Fits at Once, with a Legend
135(2)
6.2 Look Inside Model Objects
137(4)
6.3 Get Model-Based Graphics Right
141(2)
6.4 Generate Predictions to Graph
143(3)
6.5 Tidy Model Objects with Broom
146(5)
6.6 Grouped Analysis and List Columns
151(6)
6.7 Plot Marginal Effects
157(4)
6.8 Plots from Complex Surveys
161(7)
6.9 Where to Go Next
168(5)
7 Draw Maps
173(26)
7.1 Map U.S. State-Level Data
175(7)
7.2 America's Ur-choropleths
182(7)
7.3 Statebins
189(2)
7.4 Small-Multiple Maps
191(3)
7.5 Is Your Data Really Spatial?
194(4)
7.6 Where to Go Next
198(1)
8 Refine Your Plots
199(34)
8.1 Use Color to Your Advantage
201(4)
8.2 Layer Color and Text Together
205(3)
8.3 Change the Appearance of Plots with Themes
208(3)
8.4 Use Theme Elements in a Substantive Way
211(4)
8.5 Case Studies
215(15)
8.6 Where to Go Next
230(5)
Acknowledgments 233(2)
Appendix 235(26)
1 A Little More about R
235(10)
2 Common Problems Reading in Data
245(8)
3 Managing Projects and Files
253(4)
4 Some Features of This Book
257(4)
References 261(6)
Index 267
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.