Series: Chapman & Hall/CRC The R Series
200 pages, 76 colour illustrations
A data graphic is not only a static image, but it also tells a story about the data. It activates cognitive processes that are able to detect patterns and discover information not readily available with the raw data. This is particularly true for time series, spatial, and space-time datasets.
Focusing on the exploration of data with visual methods, Displaying Time Series, Spatial, and Space-Time Data with R presents methods and R code for producing high-quality graphics of time series, spatial, and space-time data. Practical examples using real-world datasets help you understand how to apply the methods and code.
Displaying Time Series, Spatial, and Space-Time Data with R illustrates how to display a dataset starting with an easy and direct approach and progressively adding improvements that involve more complexity. Each of Displaying Time Series, Spatial, and Space-Time Data with R's three parts is devoted to different types of data. In each part, the chapters are grouped according to the various visualization methods or data characteristics.
Web Resource Along with the main graphics from the text, the author's website offers access to the datasets used in the examples as well as the full R code. This combination of freely available code and data enables you to practice with the methods and modify the code to suit your own needs.
" [...] a practical guide for producing high-quality graphics for time series, spatial data and space-time data using the statistical software package R. [...] recommended as a practical guide for readers with fair knowledge of programming with R. All visualization methods are presented by means of real data sets and programming code is available."
– Zentralblatt MATH 1306
" [...] a researcher in this field will particularly benefit from this compact account of some elegant visualization techniques implemented in R for time, space, and timespace data. [...] Colorful illustrations that nicely complement the descriptive aspects of the book help in the process of understanding. [...] a valuable source of graphical visualization analyses in R [...] "
– International Statistical Review, 2015
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
Displaying Time Series: Introduction
Time on the Horizontal Axis
Time Graph of Different Meteorological Variables
Time Series of Variables with the Same Scale
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
Labels to Show Time Information
Country Names: Positioning Labels
A Panel for Each Year
About the Data
Unemployment in the United States
Gross National Income and CO2 Emissions
Displaying Spatial Data: Introduction
Proportional Symbol Mapping
Reference and Physical Maps
OpenStreetMap with Hill Shade Layers
About the Data
Air Quality in Madrid
Spanish General Elections
Land Cover and Population Rasters
Displaying Spatiotemporal Data: Introduction
Spatiotemporal Raster Data
Graphical Exploratory Data Analysis
Space-Time and Time Series Plots
Spatiotemporal Point Observations
Data and Spatial Information
Graphics with spacetime
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Oscar Perpiñán Lamigueiro is a lecturer of photovoltaic and solar energy at the Escuela de Organizacion Industrial (EOI) and an assistant professor of electrical engineering at the Universidad Politecnica de Madrid (UPM). He develops R packages that provide graphical methods to display multivariate time series, spatial data, and space-time data (rasterVis and solaR).