Displaying Time Series, Spatial, and Space-Time Data with R: (Chapman & Hall/CRC The R Series)

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.

Table of Contents:
Introduction What This Book Is About What You Will Not Find in This Book How to Read This Book R Graphics Packages Software Used to Write This Book About the Author Acknowledgments I Time Series Displaying Time Series: Introduction Packages Further Reading Time on the Horizontal Axis Time Graph of Variables with Different Scales Time Series of Variables with the Same Scale Stacked Graphs Interactive Graphics Time as a Conditioning or Grouping Variable Scatterplot Matrix: Time as a Grouping Variable Scatterplot with Time as a Conditioning Variable Time as a Complementary Variable Polylines A Panel for Each Year Interactive Graphics: Animation About the Data SIAR Unemployment in the United States Gross National Income and CO Emissions II Spatial Data Displaying Spatial Data: Introduction Packages Further Reading Thematic Maps: Proportional Symbol Mapping Introduction Proportional Symbol Mapping with spplot Proportional Symbol Mapping with ggplot Optimal Classification and Sizes to Improve Discrimination Spatial Context with Underlying Layers and Labels Spatial Interpolation Interactive Graphics Thematic Maps: Choropleth Maps Introduction Quantitative Variable Qualitative Variable Small Multiples with Choropleth Maps Bivariate Map Interactive Graphics Thematic Maps: Raster Maps Quantitative Data Categorical Data bBivariate Legend Interactive Graphics Vector Fields Introduction Arrow Plot Streamlines Physical and Reference Maps Physical Maps Reference maps About the Data Air Quality in Madrid Spanish General Elections CM SAF Land Cover and Population Rasters III Space-Time Data Displaying Spatiotemporal Data: Introduction Packages Further Reading Spatiotemporal Raster Data Introduction Level Plots Graphical Exploratory Data Analysis Space-Time and Time Series Plots Spatiotemporal Point Observations Introduction Graphics with spacetime Animation Depicting variable changes over time: raster data bDepicting variable changes over time: point space-time data Fly-by animation

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).

Review :
"The author is knowledgeable in the different data formats for time series in R as well as various different displays from modern R packages that can be used to present time series data. A small proportion of the material discusses the findings that can be drawn from each time series. The major focus of the book is on how time series are manipulated, or R functions are used to produce a specific figure. Both static and dynamic summaries of data are provided, and much discussion is given to displaying multiple time series." ~Peter Craigmile, The Ohio State University "This book addresses a fundamental gap that makes R a more usable geographic information system for applied statisticians…This book is incredibly useful for any person wanting to do modern spatial and spatio-temporal statistics. This book is technically correct. It is also clearly written and quite easy for a person with a moderate level of R programing experience to use." ~Trevor Hefley, Kansas State University "(This book) should be useful and successful across a range of audiences: researchers and practitioners working with temporal/spatial data; professors using the manuscript to supplement their courses on temporal/spatial data; graduate students learning about temporal/spatial data. I have been a part of these audiences at various stages of my own professional career, and would have loved to be ‘exposed’ to the manuscript earlier." ~Vladas Pipiras, University of North Carolina Chapel Hill "While texts on spatiotemporal data analysis exist, there is a lack of resources and references when it comes to address the challenges of producing spatiotemporal visualizations, particularly in combination with reproducible example code and data. This book aims to address this void, and in this regard, is a very valuable and needed contribution." ~Claudia Engel, Stanford University "This is a book specializing on visualization of time/space data. The topics covered are relevant and interesting…The updates planned for the second edition focus on ggplot2 and interactive web-based plots. These have both become mainstream, so such an update would be appropriate and topical." ~Deepayan Sarkar, Indian Statistical Institute, Delhi "Overall, the book is unique in what it tries to achieve. It is an excellent resource that researchers and other users can use to explore different visualisations and read on how to build them from scratch in R." ~Andrew Zammit Mangion, University of Wollongong "In summary, Displaying Time Series, Spatial, and Space-Time Data with R is a useful handbook for those wanting to learn more about temporal, spatial, and space-time data classes in R; methods for wrangling such data; and, of course, approaches for visualizing the data. Those who are already familiar with temporal/spatial/space-time data may also find it a useful overview of methods they may not have previously encountered. It is well-written and provides a nice synthesis of additional resources for those who might be interested in digging deeper into a particular topic." ~Silas Bergen, Winona State University