I think upcasting to float should occur here.
For example:
In [1]: df = pd.DataFrame([[0, 0]])
In [2]: df.loc[0] = np.nan
In [3]: df
Out[3]:
0 1
0 -9223372036854775808 -9223372036854775808
Sometimes this is caught:
In [11]: df = pd.DataFrame([[0]])
In [12]: df.loc[0] = np.nan
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-12-92653b6a9ef8> in <module>()
----> 1 df.loc[0] = np.nan
/Users/234BroadWalk/pandas/core/indexing.pyc in __setitem__(self, key, value)
86
87 self._setitem_with_indexer(indexer, value)
---> 88
89 def _has_valid_tuple(self, key):
90 pass
/Users/234BroadWalk/pandas/core/indexing.pyc in _setitem_with_indexer(self, indexer, value)
183 if np.prod(values.shape):
184 values[indexer] = value
--> 185
186 def _align_series(self, indexer, ser):
187 # indexer to assign Series can be tuple or scalar
ValueError: cannot convert float NaN to integer
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