'ValueError: Cannot assign nan to integer series" when calling `where` on Series with non-unique index.
Create a Series with non-unique index:

``` python
>>> import pandas as pd
>>> pd.__version__
'0.12.0'
>>> s1 = pd.Series(range(3))
>>> s2 = pd.Series(range(3))
>>> comb = pd.concat([s1,s2])
>>> comb
0    0
1    1
2    2
0    0
1    1
2    2
dtype: int64
```

As of https://github.com/pydata/pandas/issues/4548 I cannot use `comb[comb<2] =+ 10`, so I tried working with `where` (according to http://pandas.pydata.org/pandas-docs/stable/indexing.html#where-and-masking, stating "To guarantee that selection output has the same shape as the original data, you can use the where method in Series and DataFrame"). But already calling `where` on `comb` is problematic:

``` python
>>> comb.where(comb < 2)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/projects/bioinfp_apps/Python-2.7.3/lib/python2.7/site-packages/pandas/core/series.py", line 745, in where
    ser._set_with(~cond, other)
  File "/projects/bioinfp_apps/Python-2.7.3/lib/python2.7/site-packages/pandas/core/series.py", line 886, in _set_with
    self._set_values(key, value)
  File "/projects/bioinfp_apps/Python-2.7.3/lib/python2.7/site-packages/pandas/core/series.py", line 904, in _set_values
    values[key] = _index.convert_scalar(values, value)
  File "index.pyx", line 547, in pandas.index.convert_scalar (pandas/index.c:9752)
  File "index.pyx", line 560, in pandas.index.convert_scalar (pandas/index.c:9639)
ValueError: Cannot assign nan to integer series
>>> 
```

Is this expected?
