Hi,
I've got a rather large matrix of about 800 rows and 600000 columns.
Each column is a time-series 800 long.
Out of these 600000 time series, some have missing values (NA).
I want to strip out all columns that have one or more NA values, i.e.,
only want full time series.
This should do the trick:
data_no_NA <- data[,!apply(is.na(data), 2, any)]
I now use data_no_NA as input to a function, which returns output as a
matrix of the same size as data_no_NA
The trick is that i now need to put these columns back into a new 800 by
600000 empty matrix, at their original locations.
Any suggestions on how to do that? hopefully without having to use loops.
I'm using R/3.0.3
Cheers,
Jatin.
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