Question

I have a problem where a vector has a bunch of NAs at the beginning, and data thereafter. However the peculiarity of my data is that the first n values that are non NA, are probably unreliable, so I would like to remove them and replace them with NA.

For example, if I have a vector of length 20, and non-NAs start at index position 4:

> z
 [1]          NA          NA          NA -1.64801942 -0.57209233  0.65137286  0.13324344 -2.28339326
 [9]  1.29968050  0.10420776  0.54140323  0.64418164 -1.00949072 -1.16504423  1.33588892  1.63253646
[17]  2.41181291  0.38499825 -0.04869589  0.04798073

I would like to remove the first 3 non-NA values, which I believe to be unreliable, to give this:

> z
 [1]          NA          NA          NA          NA          NA          NA  0.13324344 -2.28339326
 [9]  1.29968050  0.10420776  0.54140323  0.64418164 -1.00949072 -1.16504423  1.33588892  1.63253646
[17]  2.41181291  0.38499825 -0.04869589  0.04798073

Of course I need a general solution and I never know when the first non-NA value starts. How would I go about doing this? IE how do I find out the index position of the first non-NA value?

For completeness, my data is actually arranged in a data frame with lots of these vectors in columns, and each vector can have a different non-NA starting position. Also once the data starts, there may be sporadic NAs further down, which prevents me from simply counting their number, as a solution.

Answer 1

Use a combination of is.na and which to find the non-NA index locations.

NonNAindex <- which(!is.na(z))
firstNonNA <- min(NonNAindex)

# set the next 3 observations to NA
is.na(z) <- seq(firstNonNA, length.out=3)