We have a PR candidate here: #11639

@thomasjpfan This is maybe a user-case that you were searching for.
The inverse_transform is also useful in this context: #22574

This issue is thus a duplicate from #11463

@glemaitre Sorry I didn't notice that other issue. However this is not a duplicate because I am requesting one additional feature -- the ability to pass in a subset of the data

I have now edited the issue above to focus just on the unique part of this request. Perhaps the Triage label could be re-added?

Hi @rebeccaherman1 : what do you mean by "subset of the data"? How is it defined?

@GaelVaroquaux I mean columns associated with one or more of the transforms within the ColumnTransformer

For example, let's say my data is Mx10, and I define the ColumnTransformer using

transformers = [('X', StandardScaler(total_variance=True), [0,1,2]),
                ('Y', StandardScaler(total_variance=True), [3,4,5,6,7]),
                ('Z', StandardScaler(total_variance=True), [8,9])]

Then, maybe later, I'd like to pass in data corresponding to just 'X' (original columns [0,1,2]) and 'Z' (original columns [8,9]), without 'Y'. I would then hope to pass in an M'x5 matrix, and identify the original columns the new data columns correspond to ([0,1,2,8,9]), or the transforms they correspond to (['X', 'Z')].

If we want to support this feature, I'll go with "slicing a column transformer":

transformers = [('X', StandardScaler(total_variance=True), [0,1,2]),
                ('Y', StandardScaler(total_variance=True), [3,4,5,6,7]),
                ('Z', StandardScaler(total_variance=True), [8,9])]
ct = ColumnTransform(transformers)
ct.fit(X)
ct_sliced = ct[["X", "Z"]]

ct_sliced.transform(X_subset)

We already have some precedence for this with Pipeline slicing.

@thomasjpfan This would be wonderful.

I tried to look through the code for ColumnTransformer, but it is a little too complicated for me to really understand everything that's going on in order to modify it in a reasonable amount of time.

Would someone else who is more familiar with the code be willing to implement this? Or discuss in more detail how it would be best implemented?