Merging two datasets with different dtypes

I’m referering to the tutorial dataset “ratings” for tensorflow recommenders
This has different dtypes (see below).
How is this created? I cannot concatenate two datasets with different dtypes.

{‘bucketized_user_age’: <tf.Tensor: shape=(), dtype=float32, numpy=45.0>, ‘movie_genres’: <tf.Tensor: shape=(1,), dtype=int64, numpy=array([7])>, ‘movie_id’: <tf.Tensor: shape=(), dtype=string, numpy=b’357’>, ‘movie_title’: <tf.Tensor: shape=(), dtype=string, numpy=b"One Flew Over the Cuckoo’s Nest (1975)">, ‘raw_user_age’: <tf.Tensor: shape=(), dtype=float32, numpy=46.0>, ‘timestamp’: <tf.Tensor: shape=(), dtype=int64, numpy=879024327>, ‘user_gender’: <tf.Tensor: shape=(), dtype=bool, numpy=True>, ‘user_id’: <tf.Tensor: shape=(), dtype=string, numpy=b’138’>, ‘user_occupation_label’: <tf.Tensor: shape=(), dtype=int64, numpy=4>, ‘user_occupation_text’: <tf.Tensor: shape=(), dtype=string, numpy=b’doctor’>, ‘user_rating’: <tf.Tensor: shape=(), dtype=float32, numpy=4.0>, ‘user_zip_code’: <tf.Tensor: shape=(), dtype=string, numpy=b’53211’>}

Got it, seems not to work for allready created datasets, but
tf.data.Dataset.from_tensor_slices(dict(dataframe))
does it.