I'm attempting to display a grid figure of summarized weekly data of several variables. The two components of this graph that are most pertinent are a distributional summary graph (so box plot or violin plot) of the values that a certain variables took over a given week and a cumulative count graph of an integer variable accumulating over weeks (so a step plot). I would like to plot these two graphs in on an aligned x-axis using grid. I'll be using ggplot2 to make the individual graphs, because I've got a crush on Hadley Wickham (j/k, ggplot is just really, really nice).
The problem is that geom_boxplot only takes factors for x-axis and the geom_step only takes continuous data for the x-axis. These don't necessarily align even if you force similar x-limits with coord_cartesian or scale_x_....
I've cobbled together a hack using geom_rect that will work for this specific application, but that will be a pain to adapt if, for example, I have some other factor that results in multiple boxes for a single week.
The obligatory reproducible:
library(ggplot2) library(grid) var1 <- data.frame(val = rnorm(300), week = c(rep(25, 100), rep(26, 100), rep(27, 100)) ) var2 <- data.frame(cumul = cumsum(c(0, rpois(2, 15))), week = c(25, 26, 27) ) g1 <- ggplot(var1, aes(x = factor(week), y = val)) + geom_boxplot() g2 <- ggplot(var2, aes(x = week, y = cumul)) + geom_step() + scale_x_continuous(breaks = 25:27) grid.newpage() grid.draw(rbind(ggplotGrob(g1), ggplotGrob(g2), size = "last")) 
And the kludge:
library(dplyr) chiggity_check <- var1 %>% group_by(week) %>% summarise(week.avg = mean(val), week.25 = quantile(val)[2], week.75 = quantile(val)[4], week.05 = quantile(val)[1], week.95 = quantile(val)[5]) riggity_rect <- ggplot(chiggity_check) + geom_rect(aes(xmin = week - 0.25, xmax = week + 0.25, ymin = week.25, ymax = week.75)) + geom_segment(aes(x = week - 0.25, xend = week + 0.25, y = week.avg, yend=week.avg), color = "white") + geom_segment(aes(x = week, xend = week , y = week.25, yend=week.05)) + geom_segment(aes(x = week, xend = week , y = week.75, yend=week.95)) + coord_cartesian(c(24.5,27.5)) + scale_x_continuous(breaks = 25:27) grid.newpage() grid.draw(rbind(ggplotGrob(riggity_rect), ggplotGrob(g2 + coord_cartesian(c(24.5,27.5))), size = "last")) 
So the question(s) is/are: is there a way to force geom_boxplot to a continuous axis or geom_step to a factor axis? Or is there some other implementation, perhaps stat_summary that will be a bit more flexible so that I can align axes and also potentially easily add in things like grouping color variables?
limits = c(24.55, 27.45)to the continuous scale seems to work for your example.