Scaling test dataset without dependent var

I’m trying to scale my test dataset using the mapper from the training and validation data set, however because the mapper knows about my dependent variable it keeps throwing an error saying that it can’t find it (because it doesn’t exist in my test data).

I am trying to scale using the proc_df function and not passing in a y_fld which should set y = None, however inside the proc_df function I can see that it passes the df through to scale_vars, along with the mapper. I think scale_vars is looking up the fields in the mapper and complaining that the y_fld doesn’t exist.

There doesn’t appear to be any way to tell proc_df to ignore the dependent variable. Is there another way that I’m missing. Most of the examples seem to process the test data alongside the training data, but this isn’t practical after you have already trained the model and just want to make predictions on new data.

After posting I realized my mistake, but I don’t see any way of removing the post. proc_df does appear to be working as expected. If there’s an admin that reads this please feel free to remove this post.