## How to add weights to prcomp() to do PCA analysis and subsequently crossvalidate the model? - r

I have a dataset, df, with one column where weights are present as below as a .csv file:
Outcome,Heat,Mobility,Time,weights
Good,125,0.2,9,2
Neutral,250,0.5,10,2
Bad,12,1.6,1,3
Good,162,0.1,9,1
Good,150,0.3,9,1
Bad,8,5.2,2,4
Neutral,330,0.2,12,3
Neutral,200,0.6,8,1
Bad,50,12,4,3
Good,130,0.9,10,4
I usually begin PCA analysis by using prcomp(df[,2:4]). But there doesn't seem to be any option to add the weights.
I tried doing prcomp(df[,2:4],scale. =as.numeric(unlist(df[5]))) option, but that gave errors stating that the number of columns provided was not suitable. Is there a way to add the associated to each row here, somehow?
Also, how I go about cross validating the model I generate here using the "leave-one-out" approach?

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