inconsistent result of groupby().sum()
The following code:

```
df=DataFrame(data=[1,2,True,4.5], columns=["A"])
df["B"]=[1,1,1,2]
print df.groupby(df["B"]).sum()
print df.groupby(df["B"]).max()
```

gives as ouput

```
   B
B   
1  3
2  2

[2 rows x 1 columns]
     A  B
B        
1  2.0  1
2  4.5  2

[2 rows x 2 columns]
```

As we can see, the sum() operation has removed the column A (probably because the dtype is object/mixed). Is it expected ? The max() operation has no trouble with the column A. 
Moreover

```
df["A"].sum()
```

gives

```
8.5
```

which shows sum() is capable of handling mixed dtype.
Using aggregate(numpy.sum) gives the same result than sum().
