sklearn FeatureUnion vs ColumnTransformer
I've tried this with an sklearn builtin dataset rather than yours, but the only difference appears to be the order of the columns.  Switching the order of the elements in the transformer lists produces the same results.  (In both cases, the numeric columns and categorical one-hot encoded columns are separated from each other, but are placed in the order that they appear in the transformer list.)