Message-ID: <4767CE3B.7070603@stats.uwo.ca>
Date: 2007-12-18T13:42:19Z
From: Duncan Murdoch
Subject: Scatterplot Showing All Points
In-Reply-To: <E1AFA099-E78C-4595-BD75-570B65E59766@math.uni-augsburg.de>
On 18/12/2007 7:31 AM, Antony Unwin wrote:
> Wayne,
>
> Try the iplot command in iPlots. You can then vary both the
> pointsize and the transparency of your scatterplot interactively and
> decide which scatterplot conveys the information best. Sometimes
> it's helpful to use more than one scatterplot when presenting your
> results.
>
> (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.
I wouldn't use the default pch if I had 50000 points, but with pch=".",
it's not so bad even in that case.
Duncan Murdoch