On Nov 1, 2010, at 3:34 PM, blurg wrote:
I have a data set similar to the set below where 1 and 2 indicate test
results and 0 indicates time points in between where there are no test
results. I would like to allocate the time points leading up to a
test
result with the value of the test result.
What I have: What I want:
1 1
0 1
0 1
0 1
1 1
0 2
0 2
2 2
0 1
0 1
1 1
0 2
2 2
I have attempted methods creating a data.frame of the the breaks/
changes in
of values to from 0 to 1 or to 2.
x<-c(0,2,0,1,0,0,0,0,1,0,1,0,0,0,2,1,0,0,0,2,0,0,0,1)
x1 <- which(diff(x) == 1)
x2 <- which(diff(x) == 2)
Not sure how long you longest run of zeros is but repeate applications
of htis method n-such times will fill in in the backward direction:
> xna <- x
> xna[xna==0] <- NA
> xna[which(is.na(xna))] <- xna[which(is.na(xna))+1]
> xna
[1] 2 2 1 1 NA NA NA 1 1 1 1 NA NA 2 2 1 NA NA 2 2 NA
NA 1 1
> xna[which(is.na(xna))] <- xna[which(is.na(xna))+1]
> xna
[1] 2 2 1 1 NA NA 1 1 1 1 1 NA 2 2 2 1 NA 2 2 2 NA
1 1 1
> xna[which(is.na(xna))] <- xna[which(is.na(xna))+1]
> xna[which(is.na(xna))] <- xna[which(is.na(xna))+1]
> xna[which(is.na(xna))] <- xna[which(is.na(xna))+1]
> xna
[1] 2 2 1 1 1 1 1 1 1 1 1 2 2 2 2 1 2 2 2 2 1 1 1 1
I'm not sure that conversion to NA is needed. The indexing with
which(x==0) and which(x==0+1 might work as well. Yep... that work's too:
> x
[1] 0 2 0 1 0 0 0 0 1 0 1 0 0 0 2 1 0 0 0 2 0 0 0 1
> x[which(x==0)] <- x[which(x==0)+1]
> x
[1] 2 2 1 1 0 0 0 1 1 1 1 0 0 2 2 1 0 0 2 2 0 0 1 1
> x[which(x==0)] <- x[which(x==0)+1]
> x[which(x==0)] <- x[which(x==0)+1]
> x[which(x==0)] <- x[which(x==0)+1]
> x
[1] 2 2 1 1 1 1 1 1 1 1 1 2 2 2 2 1 2 2 2 2 1 1 1 1
--
David
What ever the solution, I can't be entered by hand due to the size
of the
dataset (>10 million and change). Any ideas? This is my first time
posting
to this forum and I am relatively new to R, so please don't flame me
to
hard. Desperate times call for desperate measures. Thanks.
--
David Winsemius, MD
West Hartford, CT
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