Hi,
Try:
dat1 <- structure(list(Site = c("Downstream", "Downstream", "Downstream",
"Downstream", "Downstream", "Downstream", "Downstream", "Downstream",
"Downstream", "Midstream", "Midstream", "Midstream", "Midstream",
"Midstream", "Upstream", "Upstream", "Upstream", "Upstream",
"Upstream", "Upstream", "Upstream", "Upstream", "Upstream", "Upstream",
"Upstream", "Upstream", "Upstream", "Upstream"), Intersex = c("no",
"no", "no", "no", "yes", "no", "yes", "no", "no", "yes", "no",
"no", "no", "no", "yes", "yes", "yes", "yes", "yes", "no", "no",
"yes", "yes", "no", "yes", "no", "yes", "yes")), .Names = c("Site",
"Intersex"), class = "data.frame", row.names = c("1", "2", "3",
"4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15",
"16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26",
"27", "28"))
res1 <- aggregate(Intersex~Site,data=dat1,function(x) (table(x)/length(x))*100)
res1New <- do.call(`data.frame`,res1)
#or
library(plyr)
res2 <- ddply(dat1,.(Site),summarize,
Percent=(table(Intersex)/length(Intersex))*100)
plot(Intersex.yes~as.numeric(Site),data=res1New,xaxt="n",xlab="Site",ylim=c(0,100),type="b")
axis(1,at=as.numeric(res1New$Site),levels(res1New$Site))
A.K.
Hi I have the following dataset:
Site Intersex
1 Downstream no
2 Downstream no
3 Downstream no
4 Downstream no
5 Downstream yes
6 Downstream no
7 Downstream yes
8 Downstream no
9 Downstream no
10 Midstream yes
11 Midstream no
12 Midstream no
13 Midstream no
14 Midstream no
15 Upstream yes
16 Upstream yes
17 Upstream yes
18 Upstream yes
19 Upstream yes
20 Upstream no
21 Upstream no
22 Upstream yes
23 Upstream yes
24 Upstream no
25 Upstream yes
26 Upstream no
27 Upstream yes
28 Upstream yes
I want to group the sites and calculate the percent of "yes"
"no" for Intersex. Then I want to plot the prevalence of intersex
(basically plot the percent of "yes" for each site. I'm stumped!
Thanks
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