Join on Column Name not Working
I assume I am doing something wrong here:

```
s1 = pd.DataFrame({
      'Month':[pd.Timestamp('2010-05-01')], 
      'Baz':[100]}, 
   index=[pd.Timestamp('2010-05-01')])

s2 = pd.DataFrame({
      'Month':[pd.Timestamp('2010-05-01')], 
      'Foo':[100]})
```

and then I join:

```
In [58]: s1.join(s2, on="Month", rsuffix="_r")
Out[58]: 
            Baz               Month  Foo Month_r
2010-05-01  100 2010-05-01 00:00:00  NaN     NaT
```

Why is the `join` not matching correctly (I get `NaT` for `Month_r` and `NaN` for `foo`)?

Even if I do not add an index to `s1`, the join still fails:

```
s3 = pd.DataFrame({'Month':[pd.Timestamp('2010-05-01')], 'Baz':[100]})
In [68]: s3.join(s2, on="Month", rsuffix="_r")
Out[68]: 
   Baz               Month  Foo Month_r
0  100 2010-05-01 00:00:00  NaN     NaT
```

In fact, even a self join fails:

```
In [77]: s3.join(s3, on="Month", rsuffix="_r")
Out[77]: 
   Baz               Month  Baz_r Month_r
0  100 2010-05-01 00:00:00    NaN     NaT
```

`Merge`, however, works fine:

```
In [79]: s3.merge(s3, on="Month")
Out[79]: 
   Baz_x               Month  Baz_y
0    100 2010-05-01 00:00:00    100
```
