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

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

January 29, 2022

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'])

>Solution :

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