Concatenate columns at the end of a MultiIndex columns DataFrame

Consider the following DataFrames df :

df = 
kind                            A               B
names          u1      u2      u3      y1      y2
Time
0.0        0.5083  0.1007  0.8001  0.7373  0.1387
0.1        0.6748  0.0354  0.0076  0.8421  0.2670
0.2        0.1753  0.1013  0.5231  0.8060  0.0040
0.3        0.5953  0.6505  0.7127  0.0771  0.1023
0.4        0.4409  0.0193  0.6765  0.9800  0.0715

and df1:

df1 = 
kind            A      
names      potato        
Time
0.0        0.4043  
0.1        0.9801 
0.2        0.1298  
0.3        0.9564  
0.4        0.4409  

I want to concatenate the two DataFrames such that the resulting DataFrame is:

df2 = 
kind                                    A               B
names          u1      u2      u3  potato      y1      y2
Time
0.0        0.5083  0.1007  0.8001  0.5083  0.7373  0.1387
0.1        0.6748  0.0354  0.0076  0.6748  0.8421  0.2670
0.2        0.1753  0.1013  0.5231  0.1753  0.8060  0.0040
0.3        0.5953  0.6505  0.7127  0.5953  0.0771  0.1023
0.4        0.4409  0.0193  0.6765  0.4409  0.9800  0.0715

What I run is pandas.concat([df1, df2, axis=1).sort_index(level="kind", axis=1) but that results in

kind                                    A               B
names      potato      u1      u2      u3      y1      y2
Time
0.0        0.4043  0.5083  0.1007  0.8001  0.7373  0.1387
0.1        0.9801  0.6748  0.0354  0.0076  0.8421  0.2670
0.2        0.1298  0.1753  0.1013  0.5231  0.8060  0.0040
0.3        0.9564  0.5953  0.6505  0.7127  0.0771  0.1023
0.4        0.4409  0.4409  0.0193  0.6765  0.9800  0.0715

i.e. the column potato is appended at the beginning of df["A"] whereas I want it appended to the end.

Answer

Add parameter sort_remaining=False in DataFrame.sort_index:

df = pd.concat([df1, df2], axis=1).sort_index(level="kind", axis=1, sort_remaining=False)
print (df)
kind        A                               B        
names      u1      u2      u3  potato      y1      y2
Time                                                 
0.0    0.5083  0.1007  0.8001  0.4043  0.7373  0.1387
0.1    0.6748  0.0354  0.0076  0.9801  0.8421  0.2670
0.2    0.1753  0.1013  0.5231  0.1298  0.8060  0.0040
0.3    0.5953  0.6505  0.7127  0.9564  0.0771  0.1023
0.4    0.4409  0.0193  0.6765  0.4409  0.9800  0.0715