Not the most straightforward way, but I think it gets the job done:

x <- read.table(textConnection("Ageclass Scale     Mean    Sex
1     21-40    BP 40.26667 female
2     41-60    BP 34.10714 female
3     61-79    BP 37.30000 female
4     21-40    GH 30.25000 female
5     41-60    GH 39.00926 female
6     61-79    GH 49.30000 female
7     21-40    MH 56.53333 female
8     41-60    MH 62.42857 female
9     61-79    MH 72.72727 female
10    21-40    PF 25.86111 female
11    41-60    PF 42.42063 female
12    61-79    PF 52.17172 female
13    21-40    RE 38.09524 female
14    41-60    RE 42.85714 female
15    61-79    RE 42.42424 female
16    21-40    RP 20.00000 female
17    41-60    RP 25.89286 female
18    61-79    RP 15.90909 female
19    21-40    SF 51.66667 female
20    41-60    SF 63.88889 female
21    61-79    SF 57.95455 female
22    21-40    VT 32.11111 female
23    41-60    VT 36.96429 female
24    61-79    VT 33.18182 female
25    21-40    BP 35.00000   male
26    41-60    BP 37.75000   male
27    61-79    BP 36.00000   male
28    21-40    GH 42.16667   male
29    41-60    GH 41.89062   male
30    61-79    GH 41.40000   male
31    21-40    MH 72.00000   male
32    41-60    MH 66.60417   male
33    61-79    MH 75.20000   male
34    21-40    PF 41.85185   male
35    41-60    PF 55.31250   male
36    61-79    PF 47.00000   male
37    21-40    RE 37.03704   male
38    41-60    RE 54.16667   male
39    61-79    RE 46.66667   male
40    21-40    RP 27.77778   male
41    41-60    RP 28.12500   male
42    61-79    RP 20.00000   male
43    21-40    SF 61.11111   male
44    41-60    SF 66.40625   male
45    61-79    SF 60.00000   male
46    21-40    VT 38.88889   male
47    41-60    VT 30.93750   male
48    61-79    VT 42.00000   male"), header=TRUE)
# setup the plot for the max range
plot(0, type='n', ylim=range(x$Mean), xlim=range(as.integer(x$Scale)),
xaxt='n',
    ylab="Mean", xlab="Scale")
# plot the axis
axis(1, at=seq_along(levels(x$Scale)), labels=levels(x$Scale))
# split the data
x.s <- split(x, list(x$Ageclass, x$Sex))
# plot the data
invisible(lapply(seq_along(x.s), function(.grp){
    lines(as.integer(x.s[[.grp]]$Scale), x.s[[.grp]]$Mean, col=.grp,
type='o')
}))
legend('topleft', legend=names(x.s), lwd=3, col=seq_along(x.s))




On Feb 12, 2008 12:21 PM, Tom Cohen <[EMAIL PROTECTED]> wrote:

>  Dear list,
>
>  I have following data set, which I want to plot the "Scale" variable on
> the
>  x-axis and "Mean"´on the y-axis for each Ageclass and for each sex. The
> Mean
>  value of each Ageclass for each sex would be connected by a line.
> Totally,
>  there should be 6 lines, from which three present the Mean values of each
>  Ageclass for respective sex. Are there any easy ways to do this in R?
>
>
>  Ageclass Scale     Mean    Sex
> 1     21-40    BP 40.26667 female
> 2     41-60    BP 34.10714 female
> 3     61-79    BP 37.30000 female
> 4     21-40    GH 30.25000 female
> 5     41-60    GH 39.00926 female
> 6     61-79    GH 49.30000 female
> 7     21-40    MH 56.53333 female
> 8     41-60    MH 62.42857 female
> 9     61-79    MH 72.72727 female
> 10    21-40    PF 25.86111 female
> 11    41-60    PF 42.42063 female
> 12    61-79    PF 52.17172 female
> 13    21-40    RE 38.09524 female
> 14    41-60    RE 42.85714 female
> 15    61-79    RE 42.42424 female
> 16    21-40    RP 20.00000 female
> 17    41-60    RP 25.89286 female
> 18    61-79    RP 15.90909 female
> 19    21-40    SF 51.66667 female
> 20    41-60    SF 63.88889 female
> 21    61-79    SF 57.95455 female
> 22    21-40    VT 32.11111 female
> 23    41-60    VT 36.96429 female
> 24    61-79    VT 33.18182 female
> 25    21-40    BP 35.00000   male
> 26    41-60    BP 37.75000   male
> 27    61-79    BP 36.00000   male
> 28    21-40    GH 42.16667   male
> 29    41-60    GH 41.89062   male
> 30    61-79    GH 41.40000   male
> 31    21-40    MH 72.00000   male
> 32    41-60    MH 66.60417   male
> 33    61-79    MH 75.20000   male
> 34    21-40    PF 41.85185   male
> 35    41-60    PF 55.31250   male
> 36    61-79    PF 47.00000   male
> 37    21-40    RE 37.03704   male
> 38    41-60    RE 54.16667   male
> 39    61-79    RE 46.66667   male
> 40    21-40    RP 27.77778   male
> 41    41-60    RP 28.12500   male
> 42    61-79    RP 20.00000   male
> 43    21-40    SF 61.11111   male
> 44    41-60    SF 66.40625   male
> 45    61-79    SF 60.00000   male
> 46    21-40    VT 38.88889   male
> 47    41-60    VT 30.93750   male
> 48    61-79    VT 42.00000   male
>  Thanks for any help,
> Tom
>
>
> ---------------------------------
> Går det långsamt? Skaffa dig en snabbare bredbandsuppkoppling.
>
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>
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html>
> and provide commented, minimal, self-contained, reproducible code.
>
>


-- 
Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem you are trying to solve?

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