Hi:

Here's another take with ggplot2:

library(ggplot2)

# Define the basic plot elements. First argument is the data frame.
# aes() refers to the plot's aesthetics, which refer to the variables
# mapped to specific 'roles' in the plot 'geoms'

g <- ggplot(x, aes(x = Age, y = Trait))
g + geom_point(size = 2.5) + facet_wrap(~ Group) + theme_bw()

geom_point() produces a scatterplot; it picks up its x and y from the
aesthetics in g. The default point size in geom_point() is 2, which I upped
a bit. facet_wrap() produces individual plots by group; it serves the same
purpose as the conditioning variable in lattice. The default theme in
ggplot2 is to produce a grey background; theme_bw() changes the background
to white and changes a few other defaults.

HTH,
Dennis

On Wed, Oct 27, 2010 at 2:21 AM, Rosario Garcia Gil <
M.Rosario.Garcia@genfys.slu.se> wrote:

> Hello
>
> I have a data set summarized like this:
>
> File name= Height
>
> Group Ind Age Trait
> 1     1 1       20
> 1       1       2       21
> 1       2       1       22
> 1       2       2       21
> 1       3       1       24
> 1       3       2       45
> 1       4       1       23
> 1       4       2       26
> 2       1       1       45
> 2       1       2       12
> 2       2       1       25
> 2       2       2       26
> 2       3       1       45
> 2       3       2       43
> 2       4       1       23
> 2       4       2       47
> .
> .
> .
>
>
> I would like to plot Trait ~ Age but a different plot for each Group.
> I tried:
> > plot(Height$Trait ~ Height$Age | Group)
>
> But does not work. Any suggestion?
>
> Thanks
> Rosario
>
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