排序数据透视表（多索引）

Question

I'm trying to sort a pivot table's values in descending order after putting two "row labels" (Excel term) on the pivot.

sample data:

x = pd.DataFrame({'col1':['a','a','b','c','c', 'a','b','c', 'a','b','c'],
                  'col2':[  1,  1,  1,  1,  1,   2,  2,  2,   3,  3,  3],
                  'col3':[  1,.67,0.5,  2,.65, .75,2.25,2.5, .5,  2,2.75]})
print(x)
   col1  col2  col3
0     a     1  1.00
1     a     1  0.67
2     b     1  0.50
3     c     1  2.00
4     c     1  0.65
5     a     2  0.75
6     b     2  2.25
7     c     2  2.50
8     a     3  0.50
9     b     3  2.00
10    c     3  2.75

To create the pivot, I'm using the following function:

pt = pd.pivot_table(x, index = ['col1', 'col2'], values = 'col3', aggfunc = np.sum)
print(pt)
           col3
col1 col2      
a    1     1.67
     2     0.75
     3     0.50
b    1     0.50
     2     2.25
     3     2.00
c    1     2.65
     2     2.50
     3     2.75

In words, this variable pt is first sorted by col1 , then by values of col2 within col1 then by col3 within all of those. This is great, but I would like to sort by col3 (the values) while keeping the groups that were broken out in col2 (this column can be any order and shuffled around).

The target output would look something like this ( col3 in descending order with any order in col2 with that group of col1 ):

                   col3
    col1   col2    
     a       1     1.67
             2     0.75
             3     0.50

     b       2     2.25
             3     2.00 
             1     0.50

     c       3     2.75
             1     2.65
             2     2.50 

I have tried the code below, but this just sorts the entire pivot table values and loses the grouping (I'm looking for sorting within the group).

    pt.sort_values(by = 'col3', ascending = False)

For guidance, a similar question was asked (and answered) here, but I was unable to get a successful output with the provided output:

Pandas: Sort pivot table

The error I get from that answer is ValueError: all keys need to be the same shape

Answer 1

You need reset_index for DataFrame , then sort_values by col1 and col3 and last set_index for MultiIndex :

df = df.reset_index()
       .sort_values(['col1','col3'], ascending=[True, False])
       .set_index(['col1','col2'])

print (df)
           col3
col1 col2      
a    1     1.67
     2     0.75
     3     0.50
b    2     2.25
     3     2.00
     1     0.50
c    3     2.75
     1     2.65
     2     2.50