col=sample(colors()[-1], ncol(dataframe), replace = FALSE)
This may help but since it's randomized it's a crap shoot but the colors are
likely to be more distinct.
> Date: Fri, 5 Aug 2011 15:38:57 -0400
> From: sarah.gos...@gmail.com
> To: rloise...@usgs.gov
> CC: r-help@r-project.org
> Subject: Re: [R] plotting many unique colors with categorical data
>
> That's far too many to easily distinguish by color, especially if they
> need to be
> distinct, and not levels within a larger class. For the latter, you could get
> by with say 10 shades of red, 10 shades of blue, etc for related factors.
> But it doesn't sound like that's what you have. I don't think there's any
> way to create a palette of 75 distinguishable colors.
>
> If you really want to try, colors() gives you all the named colors. You
> can also use c() to combine several brewer palettes.
>
> One thing that I've done in similar cases (for viewing and data snooping,
> not for presentation), is to set up a loop through all the factor levels.
> Set par(ask=TRUE), and for each iteration plot all the points in black,
> except make that level a brighter color, and maybe larger symbol.
>
> It gives you a quick way to start to see the differences between groups,
> though obviously isn't suitable for publication.
>
> Sarah
>
> On Fri, Aug 5, 2011 at 1:46 PM, SavageMaDaMe <rloise...@usgs.gov> wrote:
> > Hi- I am trying to plot a matrix of categorical values across time using
> > color to represent each individual factor. For example:
> >
> > 1982 1983 1984 1985 1986 1987
> > 1 19 19 68 68 19 19 68
> > 2 68 68 19 19 68 68 19
> > 3 26 26 34 34 26 26 26
> > 4 57 34 57 57 34 57 34
> > 5 34 57 26 26 57 34 57
> > 6 28 28 28 28 28 58 58
> > 7 60 10 58 58 58 28 28
> > 8 58 58 42 27 10 39 39
> > 9 22 39 22 42 42 27 42
> > 10 39 22 10 39 39 20 10
> >
> >
> > I have 75 factors which could be in different positions through out time
> > (26 years). I've successfully created a plot using both ggplot() and
> > color2D.matplot(), but can not select enough distinct colors from the
> > default color palettes available to be able to view differences in the data.
> > I've tried messing with RGB values, Brewer palettes, etc.
> >
> > How can I select colors from a list of available colors without choosing
> > ones which are too close in similarity to each other. For instance, I could
> > have several very similar blues, but if the Hue or saturation was different
> > on each, it would be fairly easy to tell the difference?
> >
> > Maybe there are too many factors to make this visual representation
> > effective?
> >
> > Thanks in advance for your help!
> >
> --
> Sarah Goslee
> http://www.functionaldiversity.org
>
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