[R] plotting many unique colors with categorical data

[Sarah Goslee]

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 <rloiselle at 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