Wrong behavior due to Pandas : dict with the same key based on tuple extracted from DataFrame
Can you explain the behavior of the following :

<!-- language: lang-python -->

```
rows = pd.DataFrame([
    (0, np.nan, np.nan, 'toto'),
    (1, np.nan, np.nan, 'tata')
])

dico = {}

for row in rows.itertuples():
    k = (row[2], row[3])
    v = row[4]
    print('hash(k) : {0}'.format(hash(k)))
    v_prev = dico.setdefault(k, None)
    if v_prev is None:
        dico[k] = v

print('dico : {0}'.format(dico))
```

Result :

```
hash(k) : 3713080549408328131
hash(k) : 3713080549408328131
dico : {(nan, nan): 'toto', (nan, nan): 'tata'}
```

I manage to create a dict with the same key `(np.nan, np.nan)`. I have got this behavior only with `np.nan`. With `None` or whatever else, I get the usual result with only one key.

You can find some hints in my SO question : http://stackoverflow.com/questions/34163497/wrong-behavior-dict-with-the-same-key-based-on-tuple

It seems to be linked to `RichCompare`. The comparison operator `is` is not used in this case 
