Thanks a lot, guys.
Thomas, your method is great, precisely the thing I've been looking forward
to.
Oh dear, how I love R for those list comprehension tricks!
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Hey,
Try the following code:
a=c(1,2,3,4,5)
b=c(10,20,30,40,50)
c=c(100,200,300,400,500)
d=c(1000,8210,9000,8310, 7000)
e=c(,,9190,,)
to.replace=c(8210,8310,9190)
df = data.frame(a,b,c,d,e)
xdf <- apply(df, 2, function(x) x %in% to.replace)
df[xdf] <- "others"
--
View this mess
Hello R-world,
Please, help me to get round my little mess
I have a data.frame in which I'd rather like some values to be NA for the
future imputation process.
I've come up with the following piece of code:
random.del <- function (x, n.keeprows, del.percent){
n.items <- ncol(x)
k <- n.items*(
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