Hello,
The function below fails if any of the followind conditions is met.
1. The first value in the vector is NA
2. There are less than n = 5 (or 500) values before/after the
first/last, respectively, NA.
fun <- function(x, n){
na <- is.na(x)
rna <- rle(na)
sna <- cumsum(rna$lengths)
for(i in which(rna$values)){
prev <- x[(sna[i - 1] - n + 1):sna[i - 1]]
aftr <- x[(sna[i] + 1):(sna[i] + n)]
if(mean(prev) < 0 && mean(aftr) < 0) x[na] <- 0
}
x
}
fun(DF$data, n = 5)
Hope this helps,
Rui Barradas
Em 18-10-2012 14:24, jeff6868 escreveu:
Hi everybody,
I have a little problem about filling some gaps of NAs in my data.
These gaps are between nearly constant data (temperature under snow). Here's
a fake example to illustrate how it looks like approximately:
DF <-
data.frame(data=c(-0.51,-0.51,-0.48,-0.6,-0.54,-0.38,-0.6,-0.42,NA,NA,NA,NA,NA,NA,NA,
-0.25,-0.41,-0.5,-0.5,-0.35,-0.7,-1,-0.87))
I would like to replace my NAs with "0" with this condition:
Fill the gap with "0" if the mean of the 5 previous values before the gap
(NA) is under 0°C, AND if the mean of the 5 following values after the gap
(NA) is also under 0°C (actually it's not the 5 previous and following
values in my real data, it's my 500 previous and following values, but let's
juste take the 5 ones in my example).
I think that the nearest function for doing this is the "na.locf" function
of the package zoo, but it does not really do what I want.
Can somebody help me to resolve this?
Thanks a lot guys!
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