Learning ggplot2: 2D plot with histograms for each dimension

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I have two 2D distributions and want to show on a 2D plot how they are related, but I also want to show the histograms (actually, density plots in this case) for each dimension. Thanks to ggplot2 and a Learning R post, I have sort of managed to do what I want to have:

There are still two problems: The overlapping labels for the bottom-right density axis, and a tiny bit of misalignment between the left side of the graphs on the left. I think that the dot in the labels for the density pushes the plot a tiny bit to the right compared with the 2D plot. Any ideas?

Here’s the code (strongly based on the afore-linked post on Learning R):

p <- qplot(data = mtcars, mpg, hp, geom = "point", colour = cyl)

p1 <- p + opts(legend.position = "none")

p2 <- ggplot(mtcars, aes(x=mpg, group=cyl, colour=cyl))
p2 <- p2 + stat_density(fill = NA, position="dodge")
p2 <- p2 + opts(legend.position = "none", axis.title.x=theme_blank(),

p3 <- ggplot(mtcars, aes(x=hp, group=cyl, colour=cyl))
p3 <- p3 + stat_density(fill = NA, position="dodge") + coord_flip()
p3 <- p3 + opts(legend.position = "none", axis.title.y=theme_blank(),

legend <- p + opts(keep= "legend_box")

## Plot Layout Setup
Layout <- grid.layout( nrow = 2, ncol = 2,
widths = unit (c(2,1), c("null", "null")),
heights = unit (c(1,2), c("null", "null"))
vplayout <- function (...) {
pushViewport(viewport(layout= Layout))
subplot <- function(x, y) viewport(layout.pos.row=x, layout.pos.col=y)

# Plotting
print(p1, vp=subplot(2,1))
print(p2, vp=subplot(1,1))
print(p3, vp=subplot(2,2))
print(legend, vp=subplot(1,2))

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