(This article was first published on

**SAS and R**, and kindly contributed to R-bloggers)Kudos to several of our readers, who suggested simpler ways to craft the graphical display (combination dotplot/boxplot) from our most recent example.

Yihui Xie combines a boxplot with a coarsened version of the PCS scores (using the

`round()`function) used in the

`stripchart()`function.

ds = read.csv("http://www.math.smith.edu/r/data/help.csv")

smallds = subset(ds, female==1)

boxplot(pcs~homeless, data=smallds,

horizontal=TRUE)

stripchart(round(pcs)~homeless,

method='stack', data=smallds,

add=TRUE)

This is far simpler than the code we provided, though aesthetically is perhaps less pleasing.

An alternative approach was suggested by

*NetDoc*, who creatively utilizes the

`ggplot2`package authored by Hadley Wickham. This demonstrates how a complex plot can be crafted by building up components using this powerful system. This approach

*dodges*points so that they don't overlap.

source("http://www.math.smith.edu/sasr/examples/wild-helper.R")

ds = read.csv("http://www.math.smith.edu/r/data/help.csv")

female = subset(ds, female==1)

theme_update(panel.background = theme_rect(fill="white", colour=NA))

theme_update(panel.grid.minor=theme_line(colour="white", size=NA))

p = ggplot(female, aes(factor(homeless), pcs))

p + geom_boxplot(outlier.colour="transparent") +

geom_point(position=position_dodge(width=0.2), pch="O") +

opts(title = "PCS by Homeless") +

labs(x="Homeless", y="PCS") +

coord_flip() +

opts(axis.colour="white")

This is also simpler than the approach taken by Wild and colleagues. The increased complexity of Wild's function is the cost of maintaining a consistent integrated appearance with the other pieces of their package. In addition, the additional checking of appropriate arguments is also important for code used by others.

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