BXC (Bendix Carstensen <bxc <at> steno.dk> writes:
:
: > From: r-help-bounces <at> stat.math.ethz.ch
: > [mailto:r-help-bounces <at> stat.math.ethz.ch] On Behalf Of Robert
: >
: > I have a data set of about 10000 records which was compiled
: > from several smaller data sets using SPSS. During compilation
: > 88 false records were accidentally introduced which comprise
: > all NA values. I want to delete these records but not other
: > missing data. The functions na.exclude and na.omit seem to
: > remove all values of NA? How can I delete just the relevant
: > NA's? . i.e. I want to delete all records in the data frame
: > DATA where the field age contains NA values
:
: How about:
:
: all.nas <- apply( old, 1, function(x) sum( is.na( x ) ) )
: new <- old[all.nas < dim( old )[2], ]
A minor simplification of this might be:
x[rowSums(is.na(x)) < ncol(x),]