Inconsistent behaviour when assigning to series?
I noticed that `.loc` and `__setitem__` behave very differently when assigning one series to a sub-range of another series:

```python
>>> s = pd.Series(0.0, index=list('abcd'))
>>> s1 = pd.Series(1.0, index=list('ab'))
>>> s2 = pd.Series(2.0, index=list('xy'))
>>> s[['a', 'b']] = s2
>>> s  # names of s2 are ignored as expected
a    2.0
b    2.0
c    0.0
d    0.0
dtype: float64
>>> s.loc[['a', 'b']] = s2
>>> s  # not expected!!
a    NaN
b    NaN
c    0.0
d    0.0
dtype: float64
>>> s.loc[['a', 'b']] = s1
>>> s  # everything's fine if the indices match
a    1.0
b    1.0
c    0.0
d    0.0
dtype: float64
```

I'm not sure if this is intended behaviour but it seems odd.

I'm on pandas v. 0.24.1
