Sort dataframe multiindex level and by column

Question

#Updated: pandas version 0.23.0 solves this problem with

Sorting by a combination of columns and index levels

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I have struggled with this and I suspect there is a better way. How do I sort the following dataframe by index level name 'idx_0', level=0 and by column, 'value_1' descending such that the column 'MyName' reads vertical 'SCOTTBOSTON'.

import pandas as pd
import numpy as np
df = pd.DataFrame({'idx_0':[2]*6+[1]*5,
                   'idx_1':[6,4,2,10,18,5,11,1,7,9,3],
                   'value_1':np.arange(11,0,-1),
                   'MyName':list('BOSTONSCOTT')})

df = df.set_index(['idx_0','idx_1'])
df

Output:

            MyName  value_1
idx_0 idx_1                
2     6          B       11
      4          O       10
      2          S        9
      10         T        8
      18         O        7
      5          N        6
1     11         S        5
      1          C        4
      7          O        3
      9          T        2
      3          T        1

#Excepted output using:

df.sort_values(['value_1'], ascending=False)\
  .reindex(sorted(df.index.get_level_values(0).unique()), level=0)

I suspect there is an easier way without resetting indexes

            MyName  value_1
idx_0 idx_1                
1     11         S        5
      1          C        4
      7          O        3
      9          T        2
      3          T        1
2     6          B       11
      4          O       10
      2          S        9
      10         T        8
      18         O        7
      5          N        6

Failure #1:

df.sort_values('value_1', ascending=False).sort_index(level=0)

Sort by values first then sort index level=0, but level=1 get sorted also.

            MyName  value_1
idx_0 idx_1                
1     1          C        4
      3          T        1
      7          O        3
      9          T        2
      11         S        5
2     2          S        9
      4          O       10
      5          N        6
      6          B       11
      10         T        8
      18         O        7

Failure #2

df.sort_index(level=0).sort_values('value_1', ascending=False)

Sort by index level=0 then sort by values, but index=0 gets jumbled again.

            MyName  value_1
idx_0 idx_1                
2     6          B       11
      4          O       10
      2          S        9
      10         T        8
      18         O        7
      5          N        6
1     11         S        5
      1          C        4
      7          O        3
      9          T        2
      3          T        1

Answer 1

Here are some potential solutions for your needs:

Method-1:

 (df.sort_values('value_1', ascending=False)
    .sort_index(level=[0], ascending=[True]))

Method-2:

 (df.set_index('value_1', append=True)
    .sort_index(level=[0,2], ascending=[True,False])
    .reset_index('value_1'))

Tested on pandas 0.22.0, Python 3.6.4