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Code and Methods for Creating High-Quality Data Graphics

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.

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

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.

The book illustrates how to display a dataset starting with an easy and direct approach and progressively adding improvements that involve more complexity. Each of the book’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.

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  • Offers detailed information on producing high-quality graphics
  • 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


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 

Displaying Time Series: Introduction 
Further Reading

Time on the Horizontal Axis 
Time Graph of Different Meteorological Variables 
Time Series of Variables with the Same Scale 
Stacked Graphs

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 
Choosing Colors 
Labels to Show Time Information 
Country Names: Positioning Labels 
A Panel for Each Year 
Traveling Bubbles

About the Data 
Unemployment in the United States 
Gross National Income and CO2 Emissions

Displaying Spatial Data: Introduction 
Further Reading

Thematic Maps 
Proportional Symbol Mapping 
Choropleth Maps 
Raster Maps 
Vector Fields

Reference and Physical Maps 
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 
Further Reading

Spatiotemporal Raster Data 
Level Plots 
Graphical Exploratory Data Analysis 
Space-Time and Time Series Plots 

Spatiotemporal Point Observations 
Data and Spatial Information 
Graphics with spacetime 



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