What This Book Is About
What You Will Not Find in This Book
How to Read This Book
Software Used to Write This Book
About the Author
AcknowledgmentsI 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
Oscar Perpinan-Lamigueiro is an Associate Professor at the Universidad Politecnica 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 Organizacion 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).
"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
~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
~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 ". . . this book is a detailed guide for several appealing visualisation methods for time/spatial data, using the freely available R software, and provides real examples of data visualisation. The language is accessible and its step-by-step format makes it easy to read and understand . . ."
~Rute Vieira, ISCB