Perhaps you want this?
data <- NULL
data$state <- c(rep("Illinois", 10), rep("Wisconsin", 10))
data$county <- c("Adams", "Brown", "Bureau", "Cass", "Champaign",
"Christian", "Coles", "De Witt", "Douglas", "Edgar",
"Adams", "Ashland", "Barron", "Bayfield", "Buffalo",
"Burnett", "Chippewa", "Clark", "Columbia", "Crawford")
data$percentOld <- c(17.554849, 16.826594, 18.196593, 17.139242, 8.743823,
17.862746, 13.747967, 16.626302, 15.258940, 18.984435,
19.347022, 17.814436, 16.903067, 17.632781, 16.659305,
20.337817, 14.293354, 17.252820, 15.647179, 16.825596)
data<-data.frame(data,stringsAsFactors=FALSE)
rankWithinState<-unlist(tapply(-data$percentOld,data$state,rank))
names(rankWithinState)<-NULL
data<-data.frame(data,rankWithinState)
highCounties<-data[data$rankWithinState<=5,]
highCountiesSorted<-highCounties[order(highCounties$state,-highCounties$percentOld),]
Cory Nissen wrote:
> I am working with census data. My columns of interest are...
>
> PercentOld - the percentage of people in each county that are over 65
> County - the county in each state
> State - the state in the US
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