QST:Different results of pd.merge if using on='key' vs  left_on/right_on!
Hello,
I see a mysterious behaviour of merge function in pandas and i don't know if its a bug or because i missed something.
If i use the parameters left_on and right on an how='outer'  then a key is missing and relpaced with a NA. If i use the same name for both key columns and use on='key' all the keys will be available. Is this a normal behaviour? Is there any difference between on and left_on/right_on? 
Please see the examples below:
```python
# Example 1: NA for key=2
a = pd.DataFrame({'aa': [1,3,4,5], 'bb':[1,2,3,4]})
b = pd.DataFrame({'ab': [1,2,3,4,5], 'cc':[1,2,3,4,5]})
pd.merge(a, b, left_on='aa', right_on='ab', how='outer')

# Example 2: no NA
a = pd.DataFrame({'aa': [1,3,4,5], 'bb':[1,2,3,4]})
b = pd.DataFrame({'aa': [1,2,3,4,5], 'cc':[1,2,3,4,5]})
pd.merge(a, b, on='aa', how='outer')
```
