Displaying Time Series, Spatial, and Space-Time Data with R 2nd Edition
by Oscar Perpinan Lamigueiro (Author)

About the Author
Oscar Perpiñán-Lamigueiro is an Associate Professor at the Universidad Politécnica de Madrid, involved in teaching and research of Electrical Engineering, Electronics and Programming. He is also a lecturer of Photovoltaic and Solar Energy at the Escuela de Organización Industrial. He holds a Master's Degree in Telecommunications Engineering and a PhD in Industrial Engineering. At present, his research focuses on solar radiation (forecasting, spatial interpolation, open data) and software development with R (packages rasterVis, solaR, meteoForecast, PVF, tdr).

About this book
Focusing on the exploration of data with visual methods, Displaying Time Series, Spatial, and Space-Time Data with R, Second Edition, presents methods and R code for producing high-quality static graphics, interactive visualizations, and animations of time series, spatial, and space-time data. Practical examples using real-world datasets help you understand how to apply the methods and code.
The book illustrates how to display a dataset starting with an easy and direct approach, and progressively adds improvements that involve more complexity. Each of the three parts of the book is devoted to different types of data. In each part, the chapters are grouped according to the various visualization methods or data characteristics.
The first edition of this book was mainly focused on static graphics. Four years later, recent developments in the "htmlwidgets" family of packages are covered in this second edition with many new interactive graphics. In addition, the "ggplot2" approach is now used in most of the spatial graphics, thanks to the new "sf" package. Finally, code has been cleaned and improved, and data has been updated.
Features

• Offers detailed information on producing high-quality graphics, interactive visualizations, and animations
• Uses real data from meteorological, climate, economic, social science, energy, engineering, environmental, and epidemiological research in many practical examples
• Shows how to improve graphics based on visualization theory
• Provides the graphics, data, and R code on the author’s website, enabling you to practice with the methods and modify the code to suit your own needs.
  

Brief contents
1 Introduction 1
    1.1 What This Book Is About 1
    1.2 What You Will Not Find in This Book 2
    1.3 How to Read This Book 3
    1.4 R Graphics 4
    1.5 Packages 8
    1.6 Software Used to Write This Book 8
    1.7 About the Author 9
    1.8 Acknowledgments 9
I Time Series 11
2 Displaying Time Series: Introduction 13
    2.1 Packages 14
    2.2 Further Reading 16
3 Time on the Horizontal Axis 17
    3.1 Time Graph of Variables with Different Scales 18
    3.2 Time Series of Variables with the Same Scale 25
    3.3 Stacked Graphs 35
    3.4 Interactive Graphics 44
4 Time as a Conditioning or Grouping Variable 53
    4.1 Scatterplot Matrix: Time as a Grouping Variable 54
    4.2 Scatterplot with Time as a Conditioning Variable 61
5 Time as a Complementary Variable 65
    5.1 Polylines 66
    5.2 A Panel for Each Year 72
5.3 Interactive Graphics: Animation 80
6 About the Data 87
    6.1 SIAR 87
    6.2 Unemployment in the United States 90
    6.3 Gross National Income and CO2 Emissions 91
II Spatial Data 93
7 Displaying Spatial Data: Introduction 95
    7.1 Packages 96
    7.2 Further Reading 102
8 Thematic Maps: Proportional Symbol Mapping 105
    8.1 Introduction 106
    8.2 Proportional Symbol Mapping with spplot 106
    8.3 Proportional Symbol Mapping with ggplot 107
    8.4 Optimal Classification to Improve Discrimination 108
    8.5 Spatial Context with Underlying Layers and Labels 111
    8.6 Spatial Interpolation 117
    8.7 Interactive Graphics 118
9 Thematic Maps: Choropleth Maps 129
    9.1 Introduction 130
    9.2 Quantitative Variable 132
    9.3 Qualitative Variable 137
    9.4 Small Multiples with Choropleth Maps 141
    9.5 Bivariate Map 141
    9.6 Interactive Graphics 145
10 Thematic Maps: Raster Maps 149
    10.1 Quantitative Data 150
    10.2 Categorical Data 164
    10.3 bBivariate Legend 166
    10.4 Interactive Graphics 170
11 Vector Fields 175
    11.1 Introduction 176
    11.2 Arrow Plot 176
    11.3 Streamlines 178
12 Physical and Reference Maps 181
    12.1 Physical Maps 182
    12.2 Reference maps 186
13 About the Data 193
    13.1 Air Quality in Madrid 193
    13.2 Spanish General Elections 198
    13.3 CM SAF 201
    13.4 Land Cover and Population Rasters 202
III Space-Time Data 205
14 Displaying Spatiotemporal Data: Introduction 207
    14.1 Packages 208
    14.2 Further Reading 210
15 Spatiotemporal Raster Data 213
    15.1 Introduction 214
    15.2 Level Plots 214
    15.3 Graphical Exploratory Data Analysis 216
    15.4 Space-Time and Time Series Plots 217
16 Spatiotemporal Point Observations 225
    16.1 Introduction 226
    16.2 Graphics with spacetime 227
17 Animation 233
    17.1 Depicting Variable Changes Over Time: Raster Data 234
    17.2 bDepicting Variable Changes Over Time: Point Space-Time Data 239
    17.3 Fly-by Animation 245
IV Glossary, Bibliography and Index 251
Bibliography 255
Index 261

Series: Chapman & Hall/CRC The R Series
Pages: 270
Publisher: Chapman and Hall/CRC; 2 edition (August 16, 2018)
Language: English
ISBN-10: 9781138089983
ISBN-13: 978-1138089983