如何根据特定列对 MultiIndex Pandas 数据透视表进行排序

Question

I am new to Python and am trying to play around with the Pandas Pivot Tables. I have searched and searched but none of the answers have been what I am looking for. Basically, I am trying to sort the below pandas pivot table

import numpy as np
import pandas as pd

df = pd.DataFrame({

"TIME":["FQ1","FQ2","FQ2","FQ2"],
"NAME":["Robert",'Miranda',"Robert","Robert"],
"TOTAL":[900,42,360,2000],
"TYPE":["Air","Ground","Air","Ground"],
"GROUP":["A","A","A","A"]})

pt = pd.pivot_table(data=df,
               values =["TOTAL"], aggfunc = (np.sum),
               index = ["GROUP","TYPE","NAME"],
               columns = "TIME",
               fill_value=0,
               margins = True)

Basically I am hoping to sort the "Type" and the "Name" column based on the sum of each row.

The end goal in this case would be "Ground" type appearing first before "Air", and within the "Ground" type, I'm hoping to have Robert appear before Miranda, since his sum is higher.

Here is how it appears now:

                     TOTAL            
TIME                   FQ1   FQ2   All
GROUP TYPE   NAME                     
A     Air    Robert    900   360  1260
      Ground Miranda     0    42    42
             Robert      0  2000  2000
All                    900  2402  3302

Thanks to anyone who is able to help!!

Answer 1

Try this, because your column header is multiindex, you need to use a tuple to access the colums:

pt.sort_values(['GROUP','TYPE',('TOTAL','All')], 
               ascending=[True, True, False])

Output:

                     TOTAL            
TIME                   FQ1   FQ2   All
GROUP TYPE   NAME                     
A     Air    Robert    900   360  1260
      Ground Robert      0  2000  2000
             Miranda     0    42    42
All                    900  2402  3302