Ggplot2 boxplot: horizontal strip on the median?

Question

I would like to make ggplot2 boxplot more meaningful by adding a thick bar to the median (so if the median is equal to none of the lower or upper quartiles, it can be detected to which it is equal). I stumbled upon a recent Kokhske post: Can I get drawer labels in ggplot2? but I didn’t know how to give the “bar” “height”. Then I tried using a rectangle, but it doesn’t work either. Here is a minimal example:

require(ggplot2) require(reshape2) require(plyr) set.seed(1) ## parameters p1 <- c(5, 20, 100) p2 <- c("f1", "f2", "f3", "f4", "f5") p3 <- c("g1","g2","g3","g4","g5") N <- 1000 ## lengths l1 <- length(p1) l2 <- length(p2) l3 <- length(p3) ## build result array containing the measurements arr <- array(rep(NA, l1*l2*l3*N), dim=c(l1, l2, l3, N), dimnames=list( p1=p1, p2=p2, p3=p3, N=1:N)) for(i in 1:l1){ for(j in 1:l2){ for(k in 1:l3){ arr[i,j,k,] <- i+j+k+runif(N, min=-4, max=4) } } } arr <- arr + rexp(3*5*5*N) ## create molten data mdf <- melt(arr, formula = . ~ p1 + p2 + p3 + N) # create molten data frame ## confidence interval calculated by `boxplot.stats` f <- function(x){ ans <- boxplot.stats(x) data.frame(x=x, y=ans$stats[3], ymin=ans$conf[1], ymax=ans$conf[2]) } ## (my poor) trial ggplot(mdf, aes(x=p3, y=value)) + geom_boxplot(outlier.shape=1) + stat_summary(fun.data=f, geom="rectangle", colour=NA, fill="black", xmin=x-0.36, xmax=x+0.36, ymin=max(y-0.2, ymin), ymax=min(y+0.2, ymax)) + facet_grid(p2 ~ p1, scales = "free_y") **SOLUTION** (after the discussion with Kohske below): f <- function(x, height){ ans <- median(x) data.frame(y=ans, ymin=ans-height/2, ymax=ans+height/2) } p <- ggplot(mdf, aes(x=p3, y=value)) + geom_boxplot(outlier.shape=1) + stat_summary(fun.data=f, geom="crossbar", height=0.5, colour=NA, fill="black", width=0.78) + facet_grid(p2 ~ p1, scales = "free_y") pdf() print(p) dev.off() **UPDATE** Hmmm... it not that trivial. The following example shows that the "height" of the crossbar should be adapted to the y-axis scale, otherwise it might be overseen. require(ggplot2) require(reshape2) require(plyr) set.seed(1) ## parameters p1 <- c(5, 20, 100) p2 <- c("f1", "f2", "f3", "f4", "f5") p3 <- c("g1","g2","g3","g4","g5") N <- 1000 ## lengths l1 <- length(p1) l2 <- length(p2) l3 <- length(p3) ## build result array containing the measurements arr <- array(rep(NA, l1*l2*l3*N), dim=c(l1, l2, l3, N), dimnames=list( p1=p1, p2=p2, p3=p3, N=1:N)) for(i in 1:l1){ for(j in 1:l2){ for(k in 1:l3){ arr[i,j,k,] <- i+j^4+k+runif(N, min=-4, max=4) } } } arr <- arr + rexp(3*5*5*N) arr[1,2,5,] <- arr[1,2,5,]+30 arr[1,5,3,] <- arr[1,5,3,]+100 ## create molten data mdf <- melt(arr, formula = . ~ p1 + p2 + p3 + N) # create molten data frame f <- function(x, height){ ans <- median(x) data.frame(y=ans, ymin=ans-height/2, ymax=ans+height/2) } ## plot p <- ggplot(mdf, aes(x=p3, y=value)) + geom_boxplot(outlier.shape=1) + stat_summary(fun.data=f, geom="crossbar", height=0.7, colour=NA, fill="black", width=0.78) + facet_grid(p2 ~ p1, scales = "free_y") pdf() print(p) dev.off() 

Answer 1

here is an example:

 f <- function(x, height) { ans <- median(x) data.frame(ymin = ans-height/2, ymax = ans+height/2, y = ans) } df <- data.frame(x=gl(2,6), y=c(1,1,1,1,3,3, 1,1,3,3,3,3)) ggplot(df, aes(x, y)) + geom_boxplot() + stat_summary(fun.data = f, geom = "crossbar", height = 0.1, colour = NA, fill = "skyblue", width = 0.8, alpha = 0.5) 

If you just want to change the visibility, then here is a quick hack, I do not recommend, but

 df <- data.frame(x=gl(2,6), y=c(c(1,1,1,1,3,3), c(1,1,3,3,3,3)*10)) ggplot(df, aes(x, y)) + geom_boxplot() + facet_grid(x~.) gs <- grid.gget("geom_boxplot", grep = T) if (inherits(gs, "grob")) gs <- list(gs) gss <- llply(gs, function(g) g$children[[length(g$children)]]) l_ply(gss, function(g) grid.edit(g$name, grep=T, just = c("left", "center"), height = unit(0.05, "native"), gp = gpar(fill = "skyblue", alpha = 0.5, col = NA)))