Creating arbitrary panes in ggplot2

Question

In base graphics I can create a 4 panel pane of graphics by doing the following:

par(mfrow=c(2,2))
for (i in 1:4){
  plot(density(rnorm(100)))
}

which results in

I'd like to do the same sort of thing with ggplot2, but I can't figure out how to do it. I can't use facets because my real data, unlike this trivial example, is in very different structures and I want two graphs to be point charts and two to be histograms. How can do create panels or panes in ggplot2?

Answer 1

Following Josh O'Brien's example: I'm surprised no one has mentioned grid.arrange from the gridExtra package yet:

library(gridExtra)
grid.arrange(q1,q2,q3,q4,q5,q6,nrow=3)

This seems to be mentioned here: multiple graphs in one canvas using ggplot2

For me, it's much easier than remembering all the viewport stuff.

Answer 2

EDIT: { Ben Bolker points to an even better option -- grid.arrange from the gridExtra package. If you're a ggplot2 user, though, the R Cookbook site is still worth a click-through. }

There's code for a nice multiplot function on this page of the R Cookbook (definitely worth a visit) that's useful for this sort of thing. Quoting directly from that site:

multiplot <- function(..., plotlist=NULL, cols) {
    require(grid)

    # Make a list from the ... arguments and plotlist
    plots <- c(list(...), plotlist)

    numPlots = length(plots)

    # Make the panel
    plotCols = cols                       # Number of columns of plots
    plotRows = ceiling(numPlots/plotCols) # Number of rows needed, calculated from # of cols

    # Set up the page
    grid.newpage()
    pushViewport(viewport(layout = grid.layout(plotRows, plotCols)))
    vplayout <- function(x, y)
        viewport(layout.pos.row = x, layout.pos.col = y)

    # Make each plot, in the correct location
    for (i in 1:numPlots) {
        curRow = ceiling(i/plotCols)
        curCol = (i-1) %% plotCols + 1
        print(plots[[i]], vp = vplayout(curRow, curCol ))
    }

}

Trying it out with 6 plots in a 3-by-2 layout (four of JD Long's plots, and two bonus ones!):

set.seed(2)
q1 <- ggplot(data.frame(x=rnorm(50)), aes(x)) + geom_density()
q2 <- ggplot(data.frame(x=rnorm(50)), aes(x)) + geom_density()
q3 <- ggplot(data.frame(x=rnorm(50)), aes(x)) + geom_density()
q4 <- ggplot(data.frame(x=rnorm(50)), aes(x)) + geom_density()
q5 <- ggplot(data.frame(x=rnorm(50)), aes(x)) + geom_density()
q6 <- ggplot(data.frame(x=rnorm(50)), aes(x)) + geom_density()

multiplot(q1, q2, q3, q4, q5, q6, cols=2)

gives this figure:

If the function doesn't quite fit your needs, at least it gives you a nice starting point!