Hi everybody,
I'm a new R french user. Sorry if my english is not perfect. Hope you'll
understand my problem ;)
I have to work on temperature data (35000 lines in one file) containing some
missing data (N/A). Sometimes I have only 2 or 3 N/A following each other,
but I have also sometimes 100 or 200 N/A following each other. Here's an
example of my data, when I have only small gaps of missing data (2 or 3
N/A):
09/01/2008 12:00 2 1.93 2.93 4.56 5.43
09/01/2008 12:15 2 *3.93* 3.25 4.93 5.56
09/01/2008 12:30 2 NA 3.5 5.06 5.56
09/01/2008 12:45 2 NA 3.68 5.25 5.68
09/01/2008 13:00 2 *4.93 * 3.87 5.56 5.93
09/01/2008 13:15 2 5.93 4.25 5.75 6.06
09/01/2008 13:30 2 3.93 4.56 5.93 6.18
My question is: how can I replace these small gaps of N/A by numeric values?
I would like a fonction which only replace the small gaps (2 or 3 N/A) in my
data, but not the big gaps (more than 5 N/A following each other).
For the moment, i'm trying to do it by working with the time gap between the
2 numeric values surrounding the N/A as following:
imputation <- function(x){
met = NULL
temp <- met[1] <- x[1]
ind_temp <- 1
tps <- time(x)
for (i in 2:(length(x)) ){
if((tps[i]-tps[ind_temp] > 1)&(tps[i]-tps[ind_temp] <=
4)&(is.na(x[i]))){
met[i] <- na.approx(x)
}
else {
temp <- met[i] <- x[i]
ind_temp <- i
}
}
return(met)
}
In this example, I would like to apply the function: na.approx(x) on my N/A,
but only when I have maximum 4 N/A following each other.
There's no error, but it doesn't work (it was working in the other way, when
I had to detect aberrant data and replace it by N/A, but not now). It is
maybe not the good way to solve this problem. I don't have a lot of
experience in R. Maybe there is an easier way to do it...
Does somebody have an idea about it for helping me?
Thanks a lot!
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