Thank you very much for this. Yes the ggplot does look prettier. Just a few
additional questions though.

The data in the sample data frame are already the means of the 5 samples
measured for each time T. Does this mean that I need to

1) calculate the means and standard deviations separately per variable per
time,
2) compile those results in a new data frame, then
3) use the ggplot code you provided?


On Wed, Oct 24, 2012 at 11:22 PM, S Ellison <S.Ellison@lgcgroup.com> wrote:

>
> > I'd greatly appreciate your help in making a bar graph with multiple
> > variables plotted on it. All the help sites I've seen so far only plot 1
> > variable on the y-axis
> > ...
> >
> > I've spent several hours looking for code to do this but didn't find
> > anything. I'd use the Excel graph except that it doesn't have the sd or
> se
> > bars.
> >
> Perhaps something like lattice or ggplot would serve better?
>
> Here's something using ggplot (which has prettier colours than lattice)
>
>
> #Something like your data - with considerable licence on unreadable names!
> abst <-structure(list(Count = c(17.03, 22.94, 28.38, 29.72, 28.37, 14.45,
> 1.51, 0.54, 0.62, 1.52, 62.3, 70.6, 68.82, 64.75, 63.77, 3.17,
> 2.78, 2.22, 2.03, 1.94, 0.61, 0.33, 0.74, 0.74, 0.58, 0.44, 0.12,
> 0.37, 0.08, 0.41, 0.04, 0, 0.08, 0, 0.08, 1.96, 1.68, 2.84, 2.06,
> 3.32, 0, 0, 0, 0, 0), Benthic = structure(c(2L, 2L, 2L, 2L, 2L,
> 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 9L, 9L, 9L, 9L, 9L, 4L,
> 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 8L, 8L,
> 8L, 8L, 8L, 7L, 7L, 7L, 7L, 7L), .Label = c("Algae", "Coral",
> "Deadcoral", "Ind", "other", "softcoral", "something", "sponges",
> "xBiotic"), class = "factor"), Time = structure(c(1L, 2L, 3L,
> 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L,
> 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L,
> 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L), .Label = c("T 1", "T 2",
> "T 3", "T 4", "T 5"), class = "factor")), .Names = c("Count",
> "Benthic", "Time"), row.names = c(NA, -45L), class = "data.frame")
>
> head(abst)
>
> #Add an arbitrary 'std error'
>
> abst$stderr <- 0.05*abst$Count
>
>  library(ggplot2)
>  b <- ggplot(subset(abst, Benthic!="something"), aes(x = Time, y = Count,
> fill=Time))
>  bptot<-b + geom_bar(stat = "identity", position = "dodge")
>  bptot + facet_grid(. ~ Benthic , scales="free_y", margins=T)
>
> #or, for unequal scale heights - much easier to see individual trends
> bwrap <- bptot + facet_wrap( ~ Benthic , scales="free", nrow=2)
> bwrap
>
> #Now add error bars
> bwrap+geom_errorbar(aes(ymin=Count-stderr, ymax=Count+stderr), width=.3)
>
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