I am a new R user. Currently I am working on a dataset wherein I have to transform the multiple binary columns into single factor column
Here is the example:
Melt is certainly a solution. I'd suggest using the reshape2 melt as follows:
library(reshape2)
df=data.frame(Property.RealEstate=c(0,0,1,0,0,0),
Property.Insurance=c(0,1,0,1,0,0),
Property.CarOther=c(0,0,0,0,1,0),
Property.Unknown=c(0,0,0,0,0,1))
#add id column (presumably you have ids more meaningful than row numbers)
df$row=1:nrow(df)
#melt to "long" format
long=melt(df,id="row")
#only keep 1's
long=long[which(long$value==1),]
#merge in ids for NA entries
long=merge(df[,"row",drop=F],long,all.x=T)
#clean up to match example output
long=long[order(long$row),"variable",drop=F]
names(long)="Property"
long$Property=gsub("Property.","",long$Property,fixed=T)
#results
long
Alternately, you can just do it in the naïve way. I think it's more transparent than any of the other suggestions (including my other suggestion).
df=data.frame(Property.RealEstate=c(0,0,1,0,0,0),
Property.Insurance=c(0,1,0,1,0,0),
Property.CarOther=c(0,0,0,0,1,0),
Property.Unknown=c(0,0,0,0,0,1))
propcols=c("Property.RealEstate", "Property.Insurance", "Property.CarOther", "Property.Unknown")
df$Property=NA
for(colname in propcols)({
coldata=df[,colname]
df$Property[which(coldata==1)]=colname
})
df$Property=gsub("Property.","",df$Property,fixed=T)
> mat <- matrix(c(0,1,0,0,0,
+ 1,0,0,0,0,
+ 0,0,0,1,0,
+ 0,0,1,0,0,
+ 0,0,0,0,1), ncol = 5, byrow = TRUE)
> colnames(mat) <- c("Level1","Level2","Level3","Level4","Level5")
> mat
Level1 Level2 Level3 Level4 Level5
[1,] 0 1 0 0 0
[2,] 1 0 0 0 0
[3,] 0 0 0 1 0
[4,] 0 0 1 0 0
[5,] 0 0 0 0 1
Create a new factor based upon the index of each 1 in each row Use the matrix column names as the labels for each level
NewFactor <- factor(apply(mat, 1, function(x) which(x == 1)),
labels = colnames(mat))
> NewFactor
[1] Level2 Level1 Level4 Level3 Level5
Levels: Level1 Level2 Level3 Level4 Level5
also you can try:
factor(mat%*%(1:ncol(mat)), labels = colnames(mat))
also use Tomas
solution - ifounf somewhere in SO
as.factor(colnames(mat)[mat %*% 1:ncol(mat)])
Something different:
Get the data:
dat <- data.frame(Property.RealEstate=c(1,0,1,0,0,0),Property.Insurance=c(0,1,0,1,0,0),Property.CarOther=c(0,0,0,0,1,0),Property.Unknown=c(0,0,0,0,0,1))
Reshape it:
names(dat)[row(t(dat))[t(dat)==1]]
#[1] "Property.RealEstate" "Property.Insurance" "Property.RealEstate"
#[4] "Property.Insurance" "Property.CarOther" "Property.Unknown"
If you want it cleaned up, do:
gsub("Property\\.","",names(dat)[row(t(dat))[t(dat)==1]])
#[1] "RealEstate" "Insurance" "RealEstate" "Insurance" "CarOther" "Unknown"
If you prefer a factor output:
factor(row(t(dat))[t(dat)==1],labels=names(dat))
...and cleaned up:
factor(row(t(dat))[t(dat)==1],labels=gsub("Property\\.","",names(dat)) )