CODEWITHSUNDEEP
pythonpandasmulti-index
rpb
rpb

Reputation: 3299

How to set multiindex column from existing multiindex column df

The objective is to add another multiindex on top of existing multiindex column in Pandas.

I have the impression this can be achieve as below

 # Assuming we have an existing multilevel index as below
df.columns = pd.MultiIndex.from_product([['level1'],['level2'],df.columns ])

# Along the pipeline, we would like to append another multiindex on top of it
    df.columns = pd.MultiIndex.from_product([['Top'],df.columns ])

However, the compiler return an error

NotImplementedError: isna is not defined for MultiIndex

May I know how to fix this issue?

Code to reproduce the above error

import pandas as pd
df = pd.DataFrame({'A': [11, 21, 31],
               'B': [12, 22, 32],
               'C': [13, 23, 33]},
              index=['ONE', 'TWO', 'THREE'])


df.columns = pd.MultiIndex.from_product([['level1'],['level2'],df.columns ])
df.columns = pd.MultiIndex.from_product([['Top'],df.columns ])

Expected output

      Top
      level1        
      level2        
           A   B   C
ONE       11  12  13
TWO       21  22  23
THREE     31  32  33

Upvotes: 0

Views: 631

Answers (2)

mozway
mozway

Reputation: 260300

You can also use a dictionary with concat:

pd.concat({'Top': df}, axis=1)

Upvotes: 1

Corralien
Corralien

Reputation: 120391

Use pd.concat:

>>> pd.concat([df], keys=['Top'], axis='columns')
         Top
      level1
      level2
           A   B   C
ONE       11  12  13
TWO       21  22  23
THREE     31  32  33

Upvotes: 2

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