[R] plotting multiple variables in 1 bar graph

[S Ellison]

Macy 

> 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?

That seems to be the easiest thing to do.

You said you already used aggregate() to get the means; you can extend that a little to get the sd's or (assuming a simple stderr) the standard errors in the same data frame; for example

aggregate(count~site+time+benthic.component, data=yourdataframe, FUN=function(x) c(mean=mean(x), sd=sd(x), stderr=sqrt(var(x)/length(x))))
	#assuming i) that you have a column-format data frame with one row for each individual count identified by site, time and component
                #ii) that's how you want the stderr calculated!

Then you'll have the means, standard deviations and standard errors in the right form for ggplot to work with stat="identity".

Do check the variable names in the resulting aggregated data frame; aggregate would give them names like count.mean, count.sd etc so you will need to use those names in ggplot.

Steve E

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