How to do add/merge/concat two or more multiindex pandas dataframe in python to get below output?-CodePudding

This is my first Multiindex DataFrame df0

Attributes  Adj Close        Close          High
Symbols     AARON  AART      AARON  AART    AARON  AART
Date                                                
2021-12-01  111.3  512.2     111.3  512.2   114.0 519.5
2021-12-02  116.6  512.5     116.6  512.5   116.8 519.9
2021-12-03  117.2  522.3     117.2  522.3   122.5 526.0

Next DataFrame df1

Attributes  Adj Close     Close        High
Symbols     FINP   FLEX   FINP  FLEX   FINP  FLEX
Date                                                
2021-12-01  204.4  18.0  204.4  18.0   213.6 18.0
2021-12-02  204.5  18.7  204.5  18.7   206.3 18.9
2021-12-03  200.8  19.5  200.8  19.5   205.8 19.6

Now I want to get final dataFrame df as

Attributes  Adj Close                  Close                      High
Symbols     AARON  AART  FINP   FLEX   AARON AART  FINP   FLEX    AARON  AART   FINP   FLEX
Date                                                
2021-12-01  111.3  512.2 204.4  18.0   111.3 512.2 204.4  18.0    114.0  519.5  213.6  18.0
2021-12-02  116.6  512.5 204.5  18.7   116.6 512.5 204.5  18.7    116.8  519.9  206.3  18.9
2021-12-03  117.2  522.3 200.8  19.5   117.2 522.3 200.8  19.5    122.5  526.0  205.8  19.6

Which function/method should I use to get desired output

Note: Here added columns information for both dataFrames

df0.columns

MultiIndex([('Adj Close',      'AARON'),
            ('Adj Close',      'AART'),
            (    'Close',      'AARON'),
            (    'Close',      'AART'),
            (     'High',      'AARON'),
            (     'High',      'AART')],
           names=['Attributes', 'Symbols'])

df1.columns

MultiIndex([('Adj Close',      'AARON'),
            ('Adj Close',      'AART'),
            (    'Close',      'AARON'),
            (    'Close',      'AART'),
            (     'High',      'AARON'),
            (     'High',      'AART')],
           names=['Attributes', 'Symbols'])

CodePudding user response：

You can simply pd.concat them, and use groupby with level=0 (to group by the 0th (1st) level of the index) first:

df = pd.concat([df0, df1]).groupby(level=0).first()

Output:

>>> df
           Adj Close                      Close                       High                    
               AARON   AART   FINP  FLEX  AARON   AART   FINP  FLEX  AARON   AART   FINP  FLEX
Symbols                                                                                       
2021-12-01     111.3  512.2  204.4  18.0  111.3  512.2  204.4  18.0  114.0  519.5  213.6  18.0
2021-12-02     116.6  512.5  204.5  18.7  116.6  512.5  204.5  18.7  116.8  519.9  206.3  18.9
2021-12-03     117.2  522.3  200.8  19.5  117.2  522.3  200.8  19.5  122.5  526.0  205.8  19.6