DEPR: deprecate relableling dicts in groupby.agg
pre-curser to #14668 

This is basically in the whatsnew, but:

```
In [1]:     df = pd.DataFrame({'A': [1, 1, 1, 2, 2],
   ...:                        'B': range(5),
   ...:                        'C':range(5)})
   ...:     df
   ...: 
Out[1]: 
   A  B  C
0  1  0  0
1  1  1  1
2  1  2  2
3  2  3  3
4  2  4  4
```

This is good; multiple aggregations on a dataframe with a dict-of-lists
```
In [2]:    df.groupby('A').agg({'B': ['sum', 'max'],
   ...:                         'C': ['count', 'min']})
   ...: 
Out[2]: 
    B         C    
  sum max count min
A                  
1   3   2     3   0
2   7   4     2   3
```

This is a dict on a grouped Series -> deprecated
```
In [3]: df.groupby('A').B.agg({'foo': 'count'})
FutureWarning: using a dictionary on a Series for aggregation
is deprecated and will be removed in a future version
Out[3]: 
   foo
A     
1    3
2    2
```

Further this has to go as well, a nested dict that does renaming.
Note once we fix https://github.com/pandas-dev/pandas/issues/4160 (renaming with a level); the following becomes almost trivial to rename in-line.
```
In [4]: df.groupby('A').agg({'B': {'foo': ['sum', 'max']}, 
                             'C': {'bar': ['count', 'min']}})
FutureWarning: using a dictionary on a Series for aggregation
is deprecated and will be removed in a future version
Out[4]: 
  foo       bar    
  sum max count min
A                  
1   3   2     3   0
2   7   4     2   3
```
Note: I will fix this message (as it doesn't actually apply here)
