> 
> Perhaps something like this will work.
> 
> df[!(rowSums(is.na(df))==NCOL(df)),]


Or

df[complete.cases(df),]

Regards
Petr


> 
> Michael
> 
> On Fri, Nov 4, 2011 at 9:27 AM, Jose Iparraguirre
> <jose.iparragui...@ageuk.org.uk> wrote:
> > Hi,
> >
> > Imagine I have the following data frame:
> >
> >> a <- c(1,NA,3)
> >> b <- c(2,NA,NA)
> >> c <- data.frame(cbind(a,b))
> >> c
> >   a  b
> > 1  1  2
> > 2 NA NA
> > 3  3 NA
> >
> > I want to delete the second row. If I use na.omit, that would also 
> affect the third row. I tried to use a loop and an ifelse clause with 
> is.na to get R identify that row in which all records are missing, as 
> opposed to the first row in which no records are missing or the third 
one,
> in which only one record is missing. How can I get R identify the row in 

> which all records are missing? Or, how can I get R delete/omit only this 
row?
> > Thanks in advance,
> >
> > José
> >
> >
> > José Iparraguirre
> > Chief Economist
> > Age UK
> >
> > T 020 303 31482
> > E jose.iparragui...@ageuk.org.uk<mailto:jose.iparragui...@ageuk.org.uk
>
> >
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