sklearn vectorizing PoS & numeric data?

If I want to train on text, PoS, and numeric vectors how should this be done?

The only thing that made sense so far was to hstack coo_matrix objects. I use CountVectorizer on the PoS tagged text in dicts and simply normalize the numeric float vectors... convert to coo and stack.

is this correct?

thanks all