Hi:

Another approach might be to use the melt() function in package reshape
before creating the plot with xyplot, something along the lines of the
following:

library(reshape)
mdat <- melt(data, id = 'X')

This should create a data frame with three columns: X, variable (all the D*
names as factor levels) and value (stacked version of the D*s). Then use
something like

xyplot(value ~ X, data = mdat, groups = 'variable', ...)
xyplot(value ~ X | variable, data = mdat, ...)

One advantage of this approach is that you'll get the same structure out of
melt() no matter how many D* columns you have;
another is that the code block is small and relatively easy to remember six
months from now.  Here's a simple toy example:

library(reshape)
library(lattice)
d <- data.frame(x = 1:20, y1 = rnorm(20), y2 = rnorm(20), y3 = rnorm(20))

# Reshape the data:
m <- melt(d, id = 'x')

# xyplot with a basic legend

# melted data
xyplot(value ~ x, data = m, groups = variable,
    auto.key = list(space = 'right', points = TRUE, lines = FALSE))
# plot from the original data
xyplot(y1 + y2 + y3 ~ x, data = d,
    auto.key = list(space = 'right', points = TRUE, lines = FALSE))   #
identical except for y label

HTH,
Dennis

On Mon, Jul 26, 2010 at 7:26 PM, Rajarshi Guha <rajarshi.guha@gmail.com>wrote:

> Hi, I have a data.frame with columns named X, D1, D2, D3
>
> I know I can get a single plot with 3 curves by doing
>
> xyplot(D1 + D2 + D3 ~ X, data)
>
> but in some cases I might have columns D1 ...  D10.
>
> Is there a way to plot all 10 columns without having to specify each
> individual term?
>
> (By analogy with formulae in lm, I thought, xyplot(. ~ X, data) would
> work, but it didn't)
>
> Thanks,
>
> --
> Rajarshi Guha
> NIH Chemical Genomics Center
>
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