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

[TomAugspurger]

0.24.2

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

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.

[jorisvandenbossche]

if you have thoughts on the ideal return type.

It could indeed be a DataFrame.

(I first wanted to say: that's only possible if both inputs are a Series, otherwise you don't have labels for the columns, but: inputs first get aligned, so you always get the same labels for index / columns.
And that is actually a change in behavior compared to the current one (which is also the case for the plain ufuncs -> should this be mentioned more explicitly in the whatsnew? I don't think we currently have anything about that)

BTW, for outer ufuncs, in numpy you can have different lengths for both inputs, and end up with a non-square array. But since we do alignment in normal ufuncs in pandas, we should do alignment here as well I suppose. Although I would also see usefulness in a non-aligning behaviour, where the resulting index/column labels can be different.

[TomAugspurger]

Hmm, apparently the inputs can be n-dimensional. So returning a DataFrame doesn't scale well. Really, outer[Series, Series] and outer[Series, Index] are the only two that could return a DataFrame. outer[Series, DataFrame] is already 3-dimensional, so we would need to return an ndarray.

So I guess we should always return an ndarray...

which is also the case for the plain ufuncs -> should this be mentioned more explicitly in the whatsnew?

Yes... I missed that. I'll make a PR.

[TomAugspurger]

For reference, xarray raises

In [22]: a = xr.DataArray([1, 2, 3])

In [23]: np.subtract.outer(a, a)
---------------------------------------------------------------------------
NotImplementedError                       Traceback (most recent call last)
<ipython-input-23-83caec80c9b6> in <module>
----> 1 np.subtract.outer(a, a)

~/Envs/pandas-dev/lib/python3.7/site-packages/xarray/core/arithmetic.py in __array_ufunc__(self, ufunc, method, *inputs, **kwargs)
     47                 'alternative, consider explicitly converting xarray objects '
     48                 'to NumPy arrays (e.g., with `.values`).'
---> 49                 .format(method, ufunc))
     50
     51         if any(isinstance(o, SupportsArithmetic) for o in out):

NotImplementedError: outer method for ufunc <ufunc 'subtract'> is not implemented on xarray objects, which currently only support the __call__ method. As an alternative, consider explicitly converting xarray objects to NumPy arrays (e.g., with `.values`).

Given the ambiguity about whether .outer(Series, Series) should return a DataFrame or an ndarray, that seems sensible. I'll restore the previous behavior, but with a deprecation.

[jorisvandenbossche]

Yes, that seems like the safest option (we can later still always enable it again if there is a clear use case)