Categorical bubble plot for mapping studies - r

Question

How to create a categorical bubble plot, using GNU R, similar to that used in systematic mapping studies (see below)?
EDIT: ok, here's what I've tried so far. First, my dataset (Var1 goes to the x-axis, Var2 goes to the y-axis):
> grid
Var1 Var2 count
1 Does.Not.apply Does.Not.apply 53
2 Not.specified Does.Not.apply 15
3 Active.Learning..general. Does.Not.apply 1
4 Problem.based.Learning Does.Not.apply 2
5 Project.Method Does.Not.apply 4
6 Case.based.Learning Does.Not.apply 22
7 Peer.Learning Does.Not.apply 6
10 Other Does.Not.apply 1
11 Does.Not.apply Not.specified 15
12 Not.specified Not.specified 15
21 Does.Not.apply Active.Learning..general. 1
23 Active.Learning..general. Active.Learning..general. 1
31 Does.Not.apply Problem.based.Learning 2
34 Problem.based.Learning Problem.based.Learning 2
41 Does.Not.apply Project.Method 4
45 Project.Method Project.Method 4
51 Does.Not.apply Case.based.Learning 22
56 Case.based.Learning Case.based.Learning 22
61 Does.Not.apply Peer.Learning 6
67 Peer.Learning Peer.Learning 6
91 Does.Not.apply Other 1
100 Other Other 1
Then, trying to plot the data:
# Based on http://flowingdata.com/2010/11/23/how-to-make-bubble-charts/
grid <- subset(grid, count > 0)
radius <- sqrt( grid$count / pi )
symbols(grid$Var1, grid$Var2, radius, inches=0.30, xlab="Research type", ylab="Research area")
text(grid$Var1, grid$Var2, grid$count, cex=0.5)
Here's the result:
Problems: axis labels are wrong, the dashed grid lines are missing.

Answer 1

Here is ggplot2 solution. First, added radius as new variable to your data frame.
grid$radius <- sqrt( grid$count / pi )
You should play around with size of the points and text labels inside the plot to perfect fit.
library(ggplot2)
ggplot(grid,aes(Var1,Var2))+
geom_point(aes(size=radius*7.5),shape=21,fill="white")+
geom_text(aes(label=count),size=4)+
scale_size_identity()+
theme(panel.grid.major=element_line(linetype=2,color="black"),
axis.text.x=element_text(angle=90,hjust=1,vjust=0))

Answer 2

This will get you started by adding the tick marks to your xaxis.
To add the lines, just add a line at each level
ggs <- subset(gg, count > 0)
radius <- sqrt( ggs$count / pi )
# ggs$Var1 <- as.character(ggs$Var1)
# set up your tick marks
# (this can all be put into a single line in `axis`, but it's placed separate here to be more readable)
#--------------
# at which values to place the x tick marks
x_at <- seq_along(levels(gg$Var1))
# the string to place at each tick mark
x_labels <- levels(gg$Var1)
# use xaxt="n" to supress the standard axis ticks
symbols(ggs$Var1, ggs$Var2, radius, inches=0.30, xlab="Research type", ylab="Research area", xaxt="n")
axis(side=1, at=x_at, labels=x_labels)
text(ggs$Var1, ggs$Var2, ggs$count, cex=0.5)
also, notice that instead of calling the object grid I called it gg, and then ggs for the subset. grid is a function in R. While it is "allowed" to overwrite the function with an object, it is not recommended and can lead to annoying bugs down the line.

Answer 3

Here a version using levelplot from latticeExtra.
library(latticeExtra)
levelplot(count~Var1*Var2,data=dat,
panel=function(x,y,z,...)
{
panel.abline(h=x,v=y,lty=2)
cex <- scale(z)*3
panel.levelplot.points(x,y,z,...,cex=5)
panel.text(x,y,label=z,cex=0.8)
},scales=(x=list(abbreviate=TRUE))) ## to get short labels
To get the size of bubble proprtional to the count , you can do this
library(latticeExtra)
levelplot(count~Var1*Var2,data=dat,
panel=function(x,y,z,...)
{
panel.abline(h=x,v=y,lty=2)
cex <- scale(z)*3
panel.levelplot.points(x,y,z,...,cex=5)
panel.text(x,y,label=z,cex=0.8)
})
I don't display it since the render is not clear as in the fix size case.