ENH: Question: pivot_table() column order and hierarchy of index
I am trying to use the pivot_table() method.  Here is the sample code:

```
In [15]: import pandas as pd
In [16]: import numpy as np

In [17]: df = pd.DataFrame({'A' : ['one', 'one', 'two', 'three'] * 6,
'B' : ['A', 'B', 'C'] * 8,
'C' : ['foo', 'foo', 'foo', 'bar', 'bar', 'bar'] * 4,
'D' : np.random.randn(24),
'E' : np.random.randn(24)})

In [18]: df
Out[18]:
    A  B    C         D         E
0     one  A  foo -1.087882 -1.148548
1     one  B  foo  0.198324 -1.124947
2     two  C  foo -0.685986 -0.070714
3   three  A  bar  1.443773 -1.453439
4     one  B  bar -0.156894  0.223677
5     one  C  bar  0.571895  2.437650
6     two  A  foo  0.594358  1.010818
7   three  B  foo  0.897380  0.901461
8     one  C  foo  1.216059 -0.204750
9     one  A  bar -0.982300 -0.413738
10    two  B  bar  1.415841 -0.624734
11  three  C  bar -2.409420  2.532603
12    one  A  foo -2.215678 -1.329448
13    one  B  foo  0.157040  0.674976
14    two  C  foo  0.260635  0.741918
15  three  A  bar  0.369208 -0.133038
16    one  B  bar -0.334977  0.982732
17    one  C  bar  0.262204 -0.534082
18    two  A  foo  0.761802  0.221214
19  three  B  foo  0.229975 -1.616976
20    one  C  foo -0.288168 -0.465998
21    one  A  bar -0.510864 -0.734697
22    two  B  bar  0.165877 -0.412671
23  three  C  bar  0.714225  0.664559

In [19]: pd.pivot_table(df, values=['E','D'], rows=['A'], cols=['C','B'],aggfunc='sum')
Out[19]:
          D                                                           E  \
C           bar                           foo                           bar
B             A         B         C         A         B         C         A
A
one   -1.493164 -0.491871  0.834099 -3.303559  0.355364  0.927891 -1.148435
three  1.812980       NaN -1.695195       NaN  1.127355       NaN -1.586477
two         NaN  1.581718       NaN  1.356160       NaN -0.425351       NaN


C                               foo
B             B         C         A         B         C
A
one    1.206409  1.903568 -2.477996 -0.449970 -0.670747
three       NaN  3.197161       NaN -0.715515       NaN
two   -1.037405       NaN  1.232031       NaN  0.671204

In [20]:

The output I would like to see instead is (pivoted using Excel)

    bar                 
    A                     B                     C   
    Sum of E    Sum of D    Sum of E    Sum of D    Sum of E    Sum of D \
one -1.148435   -1.493164   1.206409    -0.491871   1.903568    0.834099
three   -1.586477   1.812981            3.197162    -1.695195
two         -1.037405   1.581718        


foo                 
A                       B                       C   
Sum of E    Sum of D    Sum of E    Sum of D    Sum of E    Sum of D
-2.477996   -3.30356    -0.449971   0.355364    -0.670748   0.927891
        -0.715515   1.127355        
1.232032    1.35616         0.671204    -0.425351
```
1. The summation column are under the column index under Excel, while in pivot_table() they are above the column indexes.  So on the columns are group by column indexes while under pandas they are grouped by the values.
2. Under Excel the values order is maintained.  E and then D while in pivot_table, it is alpha sorted, first D and then E (specification has it set as E and D).

How can I mimic Excel pivoting?

Thanks
