2nd Edition

Displaying Time Series, Spatial, and Space-Time Data with R

By Oscar Perpinan Lamigueiro Copyright 2018
    272 Pages
    by Chapman & Hall

    272 Pages
    by Chapman & Hall

    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.

    • 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.


    What This Book Is About

    What You Will Not Find in This Book

    How to Read This Book

    R Graphics


    Software Used to Write This Book

    About the Author


    I Time Series

    Displaying Time Series: Introduction


    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


    A Panel for Each Year

    Interactive Graphics: Animation

    About the Data


    Unemployment in the United States

    Gross National Income and CO Emissions

    II Spatial Data

    Displaying Spatial Data: Introduction


    Further Reading

    Thematic Maps: Proportional Symbol Mapping


    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


    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


    Arrow Plot


    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


    Further Reading

    Spatiotemporal Raster Data


    Level Plots

    Graphical Exploratory Data Analysis

    Space-Time and Time Series Plots

    Spatiotemporal Point Observations


    Graphics with spacetime


    Depicting variable changes over time: raster data

    bDepicting variable changes over time: point space-time data

    Fly-by animation



    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).

    "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

    ". . . 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