On 18 Dec 2007, at 2:42 pm, Duncan Murdoch wrote:
>> (I must admit to being very surprised that jittering and
>> sunflower plots have been suggested for a dataset of 5000
>> points. Do those who mentioned these methods have examples on
>> that scale where they are effective?)
>
> Sure. The original post said there were about 50-60 unique
> locations. This plot:
>
> x <- rbinom(5000, 20, 0.15)
> y <- rbinom(5000, 20, 0.15)
> plot(x,y)
>
> has a few more unique locations; tune those probabilities if you
> want it closer. Due to the overlap, the distribution is very
> unclear. But this plot
>
> plot(jitter(x), jitter(y))
>
> makes the distribution quite clear.
No it doesn't! It makes it moderately clearer than the plot without
jittering. One good alternative here is the fluctuation diagram
variant of a mosaic plot:
xx<-as.factor(x)
yy<-as.factor(y)
imosaic(xx,yy, type="f")
Using jittering for categorical data is really not to be recommended
and will certainly degrade in performance as the dataset gets bigger.
Antony Unwin
Professor of Computer-Oriented Statistics and Data Analysis,
University of Augsburg,
Germany
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