# Map Attribute Data in R using GGPLOT2 In this post I map some attribute data using the R software package GGPLOT2. The code primarily comes from James Cheshire excellent GIS site, Spatial Analysis. This site offers many resources, including a number of step-by-step tutorials on introductory and advanced GIS mapping in R. A couple tutorials I found useful describe how to map attribute data in R. His code is concise and well written, but doesn’t explicitly describe how to map observations made on a continuous attribute variable at discrete levels. This is something standard with ArcGIS software and probably something people want to do, or, at least, are use to doing. Think of this code as a mix between Cheshire’s posts Creating a Map with R and Creating a map with R using ggplot2.

In the following code I essentially take the observed values on continuous attribute variable, break them into intervals and plot them on a map of Irish Republic counties. The continuous variable used here was broken into five categories, though the code is modifiable enough to accommodate different numbers of break points. You’ll need to use the R packages maptools, ggplot2, RColorBrewer and classInt the for this one.

# Identify and save 5 lower and 1 upper break values
# i.e. [),[),[),[),[]
brks <- classIntervals(contVariable,n=5,style="quantile")

# Save and extract break values
# Round values to two decimals
brks <- round(brks$brks,digits=2) # Save categorical break value for each observed values of the continuous variable catVariable <- findInterval(contVariable,brks,all.inside=TRUE) # Add attribute data to SpatialPolygonsDataFrame shapefile object counties <- spCbind(counties,catVariable) # Make SpatialPolygonsDataFrame shapefile object compatible with GGPLOT2 # The function poly_coord_function.r is available through Cheshire's "Creating a map with R using ggplot2" post names(counties) <- "ID" source("~/poly_coords_function.r") counties_geom <- poly_coords(counties) # Plot and save map map <- qplot(PolyCoordsY,PolyCoordsX,data=counties_geom,group=Poly_Name,fill=catVarible, geom="polygon") # Create labels from break values intLabels <- matrix(1:(length(brks)-1)) for(i in 1:length(intLabels )){intLabels [i] <- paste(as.character(brks[i]),"-",as.character(brks[i+1]))} # Re-Map data # Include a categorical legend # Add the continuous break point label to legend map + scale_fill_gradientn(colours=brewer.pal(5, "Set2"),guide="legend",label=intLabels,name="contVariable name",min(contVariable),max(contVariable))  Advertisement # Add Attribute Data to object of class SpatialPolygonsDataFrame in R Here we discuss the R software package maptools, which lets us add attribute data to an object of class SpatialPolygonsDataFrame. We can import GIS data, if stored as a shapefile, using the command gisData <- readShapePoly("NameOfShapeFile.shp"). We know it’s an object type SpatialPolygonsDataFrame from the output given by entering the command class(gisData). We can see the attributes of this data object by following the name of the object by an @ symbol and the word data, i.e. gisData@data. The output to this command should look like a typical data set from any introductory discussion of statistics, with variables along columns and subjects across rows. In fact, we can save information from this data object for later manipulation using a command such as gDVN <- gisData@data$VariableName.

At this point modifying the attribute data of a GIS object is easy. For instance, if you wanted to change values of some variable from counts to percentages you could divide each count value of each subject on the variable of interest by the total number of counts. More concretely, we could divide the number of people in each area by the total population of the entire study region. This can be done using a command such as gisData@data\$VariableName/n, where n is some number, possible the total population size.

But what if we wanted to add a new attribute to the SpatialPolygonsDataFrame object? This can be done using the function spCbind from the R software package maptools. Something like gisData <- spCbind(gisData,1:nrow(gisData)), where nrow(gisData) is the number of rows in the attribute data matrix of your GIS object, should add a column of values, ranging from 1 to nrow(gisData) to your GIS data object attribute matrix.

As always, for more information consult the help files, in this case, by entering the command ?spCbind into an active R session.