On Apr 19, 2011, at 10:57 , dereksloan wrote:
> This is probably very simple but I'm new to R so apologies for being stupid.
>
> I have some data with No coded as 0 and yes coded as 1.
>
> e.g.
>
> id sex alcohol smoker
> 1 M 0 1
> 2 F 1 0
> 3 M 0 0
>
> I realise I can covert the numerical variable back to a factor by
>
> falcohol<-factor(alcohol,levels=0:1)
> levels<-c("No","Yes")
> fsmoker<-factor(smoker,levels=0:1)
> levels<-c("No","Yes")
>
> but can I do this for all factors using the same levels in a single command
> to make it easier (i.e. switch all 0/1, no/yes variables without having to
> recode the same factor levels for them all)?
Yes, if they are in the same data frame. The idiom goes roughly like this
ix <- c("alcohol", "smoker")
new <- paste("f", ix, sep="")
dd[new] <- lapply(dd[ix], factor, levels=0:1, labels=c("No","Yes"))
(You might store the transformed variables back where they came from, just make
sure to do it exactly once! That would avoid creating new variable names and
give you a bit more flexibility in the choice of index type. There are also
various possibilities to actually compute the indices, e.g.
isBin <- function(x) all(na.omit(x) %in% 0:1)
ixl <- sapply(dd, isBin)
ix <- names(dd)[ixl]
...
)
>
> Derek
>
> --
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>
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--
Peter Dalgaard
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd....@cbs.dk Priv: pda...@gmail.com
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