API/BUG: Series.argmin/max with all-NaN data returns -1 ?
Ran into this while looking at https://github.com/pandas-dev/pandas/pull/27801. 

Both numpy and pandas raise an error for empty arrays/Series in `argmin` and `argmax`:

```python
>>> pd.Series([], dtype=float).argmin()   
...
ValueError: attempt to get argmin of an empty sequence

>>> np.array([], dtype=float).argmin()  
...
ValueError: attempt to get argmin of an empty sequence
```

However, when having all NaN data, we see a different behaviour:

```python
>>> pd.Series([np.nan, np.nan], dtype=float).argmin() 
-1

>>> np.array([np.nan, np.nan], dtype=float).argmin() 
0
```

Does somebody have an explanation of *why* this would return -1 ?

In principle, in pandas, `argmin` has a `skipna=True` keyword, so for pandas I would expect that an all-NaN Series behaves the same as an empty Series.