On Jun 27, 2011, at 12:56 PM, Christopher Desjardins wrote:
Hi,
I have the following data management issue. I am trying to combine
multiple
years of ethnicity data into one variable called ethnic. The data
looks
similar to the following
id ethnic07 ethnic08 ethnic09 ethnic10
1 1 1 1 1
2 1 1 2 2
3 3 4 4 NA
4 2 3 NA NA
So, what I'd like to do is create a variable called 'ethnic' and I'd
like to
have this variable be filled with the most recent data available. So
ethnic10 would have the highest priority, then ethnic09, followed by
ethnic08, and finally ethnic07. So the ethnic variable based on the
data
above would look like the following:
ethnic
1
2
4
3
rd.txt <- function(txt, header=TRUE, ...) {
rd <- read.table(textConnection(txt), header=header, ...)
closeAllConnections()
rd }
> tail_noNA <- function(x,n) tail(x[!is.na(x)], n)
> tail_noNA(c(1,2,3,NA),1)
[1] 3
> dat <-rd.txt("id ethnic07 ethnic08 ethnic09 ethnic10
+ 1 1 1 1 1
+ 2 1 1 2 2
+ 3 3 4 4 NA
+ 4 2 3 NA NA")
> apply(dat, 1, tail_noNA, 1)
[1] 1 2 4 3
> as.matrix(apply(dat, 1, tail_noNA, 1))
[,1]
[1,] 1
[2,] 2
[3,] 4
[4,] 3
I thought an ifelse() statement might work but I seem to be writing
over my
data every time I do this.
Thanks,
Chris
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and provide commented, minimal, self-contained, reproducible code.
