[R] Replace selected columns of a dataframe with NA

[Dimitris Rizopoulos]

I don't know if you have factors in your data frame, but in any case, 
you can try the following approach:

mydata <- data.frame(id = 1:10, x = rnorm(10, 80),
     z = rnorm(10, 80), w = gl(2, 5))
mydata

f <- function (x) {
     if (is.numeric(x))
         x[x > 80] <- NA
     x
}
mydata[-1] <- lapply(mydata[-1], f)
mydata


I hope it helps.

Best,
Dimitris


On 6/20/2011 10:40 AM, Chris Beeley wrote:
> I am using the following command to replace all the missing values and
> assorted typos in a dataframe with NA:
>
> mydata[mydata>80]=NA
>
> The problem is that the first column contains values which should be
> more than 80, so really I want to do it just for
> mydata[,2:length(mydata)]
>
> I can't seem to re-write the code to fit:
>
> mydata[,2:length(mydata)>80]=NA # no error message, but doesn't work-
> doesn't do anything, it would seem
>
> I realise I can just keep the first column somewhere safe and copy it
> back again when I'm done, but I wondered if there was a more elegant
> solution, which would be much more important, if say I just wanted to
> replace the odd columns, or something like that.
>
> I found this code on the internet too:
>
> idx<- which(foo>80, arr.ind=TRUE)
> foo[idx[1], idx[2]]<- NA
>
> But I can't seem to rewrite that either, for the same reason
>
> Many thanks!
>
> Chris Beeley
> Institute of Mental Health
>
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-- 
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus University Medical Center

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