
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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