Bubble chart for integer variables where the largest bubble has a diameter of 1 (on the x or y axis scale)?

ggplot2, r

Solution

When no ggplot, lattice or other highlevel package seems to do the job without hours of fine tuning I always revert to the base graphics. The following code gets you what you want, and after it I have another example based on how I would have plotted it.

Note however that I have set the maximum radius to 1 cm, but just divide `size.range/2` to get diameter instead. I just thought radius gave me nicer plots, and you'll probably want to adjust things anyways.

size.range <- c(.1, 1) # Min and max radius of circles, in cm

# Calculate the relative radius of each circle
radii <- sqrt(agData$freq)
radii <- diff(size.range)*(radii - min(radii))/diff(range(radii)) + size.range[1]

# Plot in two panels
mar0 <- par("mar")
layout(t(1:2), widths=c(4,1))

# Panel 1: The circles
par(mar=c(mar0[1:3],.5))
symbols(agData$class, agData$drv, radii, inches=size.range[2]/cm(1), bg="black")

# Panel 2: The legend
par(mar=c(mar0[1],.5,mar0[3:4]))
symbols(c(0,0), 1:2, size.range, xlim=c(-4, 4), ylim=c(-2,4),
        inches=1/cm(1), bg="black", axes=FALSE, xlab="", ylab="")
text(0, 3, "Freq")
text(c(2,0), 1:2, range(agData$freq), col=c("black", "white"))

# Reset par settings
par(mar=mar0)

Now follows my suggestion. The largest circle has a radius of 1 cm and area of the circles are proportional to `agData$freq`, without forcing a size of the smallest circle. Personally I think this is easier to read (both code and figure) and looks nicer.

with(agData, symbols(class, drv, sqrt(freq),
     inches=size.range[2]/cm(1), bg="black"))
with(agData, text(class, drv, freq, col="white"))

Problem

I want to achieve the following outcomes: - Rescale the size of the bubbles such that the largest bubble has a diameter of 1 (on whichever has the more compressed scale of the x and y axes). - Rescale the size of the bubbles such that the smallest bubble has a diameter of 1 mm - Have a legend with the first and last points the minimum non-zero frequency and the maximum frequency. The best I have been able to do is as follows, but I need a more general solution where the value of maxSize is computed rather than hard-coded. If I was doing it in the traditional R plots I would use par("pin") to work out the size of plot area and work backwards, but I cannot figure out how to access this information with ggplot2. Any suggestions? ``` library(ggplot2) agData = data.frame( class=rep(1:7,3), drv = rep(1:3,rep(7,3)), freq = as.numeric(xtabs(~class+drv,data = mpg)) ) agData = agData[agData$freq != 0,] rng = range(agData$freq) mn = rng[1] mx = rng[2] minimumArea = mx - mn maxSize = 20 minSize = max(1,maxSize * sqrt(mn/mx)) qplot(class,drv,data = agData, size = freq) + theme_bw() + scale_area(range = c(minSize,maxSize), breaks = seq(mn,mx,minimumArea/4), limits = rng) ``` Here is what it looks like so far:

Original source