I have a dataframe in R that I would like to convert all columns (outside the ids) from negative to zero
id1 id2 var1 var2 var3
-1 -1 0 -33 5
You could use pmax
:
dat <- data.frame(id1=c(-1,-1), id2=c(-1,-2), var1=c(0,9), var2=c(-33,10), var3=c(5,-1))
dat[,-c(1,2)] <- matrix(pmax(unlist(dat[,-c(1,2)]),0), nrow=nrow(dat))
There might be fancier or more compact ways, but here's a vectorised replacement you can apply
to the var
columns:
mytable <- read.table(textConnection("
id1 id2 var1 var2 var3
-1 -1 0 -33 5
-1 -2 9 -10 -1"), header = TRUE)
mytable[, grep("^var", names(mytable))] <-
apply(mytable[, grep("^var", names(mytable))], 2, function(x) ifelse(x < 0, 0, x))
mytable
## id1 id2 var1 var2 var3
## 1 -1 -1 0 0 5
## 2 -1 -2 9 0 0
We can use data.table
setDT(d1)
for(j in grep('^var', names(d1))){
set(d1, i= which(d1[[j]]<0), j= j, value=0)
}
d1
# id1 id2 var1 var2 var3
# 1: -1 -1 0 0 5
# 2: -1 -2 9 0 0
Edit a bit your variant
temp[,-c(1,2)][temp[, -c(1,2)] < 0] <- 0
You can try using replace
:
> mydf[-c(1, 2)] <- replace(mydf[-c(1, 2)], mydf[-c(1, 2)] < 0, 0)
> mydf
id1 id2 var1 var2 var3
1 -1 -1 0 0 5
2 -1 -2 9 0 0