Reputation: 2481
I have to find out the cumulative frequency, converted to percentage, of a continuous variable by factor. For example:
data <- data.frame(n = sample(1:12),
d = seq(10, 120, by = 10),
Site = rep(c("FirstSite", "SecondSite"), 6),
Plot = rep(c("Plot1", "Plot1", "Plot2", "Plot2"), 3)
)
data <- with(data, data[order(Site,Plot),])
data <- transform(data, G = ((pi * (d/2)^2) * n) / 10000)
data
n d Site Plot G
1 7 10 FirstSite Plot1 0.05497787
5 9 50 FirstSite Plot1 1.76714587
9 12 90 FirstSite Plot1 7.63407015
3 10 30 FirstSite Plot2 0.70685835
7 5 70 FirstSite Plot2 1.92422550
11 1 110 FirstSite Plot2 0.95033178
2 3 20 SecondSite Plot1 0.09424778
6 8 60 SecondSite Plot1 2.26194671
10 6 100 SecondSite Plot1 4.71238898
4 4 40 SecondSite Plot2 0.50265482
8 2 80 SecondSite Plot2 1.00530965
12 11 120 SecondSite Plot2 12.44070691
I need the cumulaive frequency of column G
by factors Plot~Site
in order to plot a geom_step ggplot of G
against d
for each plot and site.
I have achieved to compute cumulative sum of G
by factor by:
data.ss <- by(data[, "G"], data[,c("Plot", "Site")], function(x) cumsum(x))
# Gtot
(data.ss.tot <- sapply(ss, max))
[1] 9.456194 3.581416 7.068583 13.948671
Now I need to express each Plot
G
in the range [0..1] where 1 is G
tot for each Plot
. I imagine I should divide G
by its Plot
Gtot
, then apply a new cumsum
to it. How to do it?
Please note that I have to plot this cumulative frequency against d
not G
itself, so it is not a proper ecdf.
Thank you.
Upvotes: 6
Views: 1826
Reputation: 22588
I usually use ddply
and transform
to do this type of thing:
> data = ddply(data, c('Site', 'Plot'), transform, Gsum=cumsum(G), Gtot=sum(G))
> qplot(x=d, y=Gsum/Gtot, facets=Plot~Site, geom='step', data=data)
Upvotes: 8