[R] filling small gaps of N/A

[jeff6868]

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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