try this:
dat <- data.frame(x = rnorm(10), y = rnorm(10),
z = rnorm(10), g = gl(5,2))
dat$x[sample(10, 3)] <- NaN
dat$y[sample(10, 3)] <- NaN
dat$z[sample(10, 3)] <- NaN
dat[] <- lapply(dat, function(x){
x[is.nan(x)] <- NA
x
})
I hope it helps.
Best,
Dimitris
Peck, Jon wrote:
I am looking for the most efficient way to replace all occurrences of NaN in a
data frame with NA. I can do this with a double loop, but it seems that there
should be a higher level and more efficient way. With is.na, I could use
ifelse, but if.nan seems not to have similar capabilities.
TIA,
Jon Peck
Jon K. Peck
[EMAIL PROTECTED]
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--
Dimitris Rizopoulos
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
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