Using numpy median with groupby aggregrate
Migrated from http://stackoverflow.com/questions/12651618/inconsisitency-in-results-of-aggregating-pandas-groupby-object-using-numpy-media

```
test = pd.DataFrame({'A' : [10,11,12,13,15,25,43,70],  
                     'B' : [1,2,3,4,5,6,7,8],  
                     'C' : [1,1,1,1,2,2,2,2]})
    A  B  C
0  10  1  1
1  11  2  1
2  12  3  1
3  13  4  1
4  15  5  2
5  25  6  2
6  43  7  2
7  70  8  2
test_g = test.groupby('C')
```

Aggregating using `np.median` (unexpectedly) produces DataFrame-wise aggregation within groups:

```
test_g.aggregate(np.median) 
      A     B
C            
1   7.0   7.0
2  11.5  11.5
```

It works perfectly when `axis=0` is passed in:

```
test_g.aggregate(np.median, axis=0)
      A    B
C           
1  11.5  2.5
2  34.0  6.5
```

For `np.mean` (also `sum`, `min`, `max`) this doesn't average over entire array:

```
test_g.aggregate(np.mean) 
       A    B
C            
1  11.50  2.5
2  38.25  6.5
```

Perhaps worth noting that when passing in as a list this behaviour is not seen:

```
test_g.agg([np.median])
       A             B        
    median    median
C                             
1  11.5         2.5
2   34.0        6.5
```
