REGR: Series.__array_ufunc__ doesn't handle `.outer`
0.24.2

```python
In [4]: s = pd.Series([1, 2, 3])

In [5]: o = np.array([0, 1 ,2])

In [6]: np.subtract.outer(s, o)
Out[6]:
array([[ 1,  0, -1],
       [ 2,  1,  0],
       [ 3,  2,  1]])


```


master

```pytb
In [7]: np.subtract.outer(s, o)
---------------------------------------------------------------------------
Exception                                 Traceback (most recent call last)
<ipython-input-7-a64bc670e48a> in <module>
----> 1 np.subtract.outer(s, o)

~/sandbox/pandas/pandas/core/series.py in __array_ufunc__(self, ufunc, method, *inputs, **kwargs)
    793             return None
    794         else:
--> 795             return construct_return(result)
    796
    797     def __array__(self, dtype=None):

~/sandbox/pandas/pandas/core/series.py in construct_return(result)
    784                                      index=index,
    785                                      name=name,
--> 786                                      copy=False)
    787
    788         if type(result) is tuple:

~/sandbox/pandas/pandas/core/series.py in __init__(self, data, index, dtype, name, copy, fastpath)
    255             else:
    256                 data = sanitize_array(data, index, dtype, copy,
--> 257                                       raise_cast_failure=True)
    258
    259                 data = SingleBlockManager(data, index, fastpath=True)

~/sandbox/pandas/pandas/core/internals/construction.py in sanitize_array(data, index, dtype, copy, raise_cast_failure)
    654     elif subarr.ndim > 1:
    655         if isinstance(data, np.ndarray):
--> 656             raise Exception('Data must be 1-dimensional')
    657         else:
    658             subarr = com.asarray_tuplesafe(data, dtype=dtype)

Exception: Data must be 1-dimensional
```

Probably not an RC blocker, but I may try to get a fix in quick.

Do we want to return an ndarray here? We don't want a DataFrame where the index & columns match?

cc @jorisvandenbossche @shoyer if you have thoughts on the ideal return type.