BUG: Aggregating over an integer on an empty DataFrame removes the index name
Suppose I have this simple DataFrame:

``` python
In [91]: df = pd.DataFrame({'ref':[1, 2, 3], 'symbol':['GOOGL', 'IBM', 'MSFT'], 'price':[585.93, 180.72, 42.03]}, columns=['ref', 'symbol', 'price'])

In [92]: df
Out[92]:
   ref symbol   price
0    1  GOOGL  585.93
1    2    IBM  180.72
2    3   MSFT   42.03

In [93]: df.dtypes
Out[93]:
ref         int64
symbol     object
price     float64
dtype: object
```

If I aggregate over an object and then reset the index, everything comes back as expected:

``` python
In [95]: df.groupby('symbol').first().reset_index()
Out[95]:
  symbol  ref   price
0  GOOGL    1  585.93
1    IBM    2  180.72
2   MSFT    3   42.03
```

Similarly with aggregating over an integer:

``` python
In [96]: df.groupby('ref').first().reset_index()
Out[96]:
   ref symbol   price
0    1  GOOGL  585.93
1    2    IBM  180.72
2    3   MSFT   42.03
```

Now let's say I have an empty DataFrame. Aggregating over an object produces what I expect:

``` python
In [97]: df.query('price > 1000').groupby('symbol').first().reset_index()
Out[97]:
Empty DataFrame
Columns: [symbol, ref, price]
Index: []
```

But aggregating over an integer gives me `index` as the column name instead of the expected `ref`!

``` python
In [98]: df.query('price > 1000').groupby('ref').first().reset_index()
Out[98]:
Empty DataFrame
Columns: [index, symbol, price]
Index: []
          ^^^^^
```

Interestingly, setting the index in a non-aggregating function does the right thing:

``` python
In [100]: df.query('price > 1000').set_index('ref').reset_index()
Out[100]:
Empty DataFrame
Columns: [ref, symbol, price]
Index: []
```

So aggregating over an integer in an empty DataFrame removes the index name. This was discovered in pandas 0.14.0.
