The plot shows that the relationship between January and July precipitation indeed varies with elevation. 375, 1, 1), more=T) print( plot(Elevation), position= c(. Library(lattice) attach(scanvote) coplot(Yes ~ log10(Pop) | Country, columns= 3, panel= function(x,y.), xlab = "APJul", ylab = "APJan") print(plot2, position= c( 0.
The map() function generates the outlines of a map of Oregon counties, and stores them in or.map, then the colors are figured out, and finally a 3-D scatter plot is made (using the scatterplot3d() function, and finally a 3-D scatter plot is made (using the scatterplot3d() function, and the points and droplines are added. Library(maps) # get points that define Oregon county outlines or_map <- map( "county", "oregon", xlim= c( - 125, - 114), ylim= c( 42, 47), plot= FALSE) # get colors for labeling the points plotvar <- orstationc $pann # pick a variable to plot nclr <- 8 # number of colors plotclr <- brewer.pal(nclr, "PuBu") # get the colors colornum <- cut( rank(plotvar), nclr, labels= FALSE) colcode <- plotclr # assign color # scatterplot and map plot.angle <- 135 s3d <- scatterplot3d(orstationc $lon, orstationc $lat, plotvar, type= "h", angle=plot.angle, color=colcode, pch= 20, cex.symbols= 2, col.axis= "gray", col.grid= "gray") s3d $ points3d(or_map $x,or_map $y, rep( 0, length(or_map $x)), type= "l") Exercise 05 - Data wrangling and matrix algebra.Exercise 03 - Bivariate plots and descriptive statistics.