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Python Pandas | Create a DataFrame with the levels of the MultiIndex as columns and substitute index level names

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mahmoud2506
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2022-05-23
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Create a DataFrame with the levels of the MultiIndex as columns and substitute index level names

The pandas.MultiIndex.to_frame() method is used for this purpose i.e., to create a DataFrame with the levels of the MultiIndex as columns.

Syntax:

MultiIndex.to_frame(index=True, name=NoDefault.no_default)

The method accepts two parameters, index which is a bool type having default value True, it sets the index of returned DataFrame constructor with data as a dict. The second parameter is the name (optional) which is a list or sequence of str, the passed names should substitute index level names. The method returns a DataFrame containing the original MultiIndex data.

To work with MultiIndex in Python Pandas, we need to import the pandas library. Below is the syntax,

import pandas as pd
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mahmoud2506
2022-05-23
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Python code to create a DataFrame with the levels of the MultiIndex as columns

# Import the pandas package
import pandas as pd

# Create arrays
employees = [
        ['E101', 'E102', 'E102', 'E103'],
        ['Alex', 'Alvin', 'Deniel', 'Jenny'],
    ]

# create a Multiindex using  from_arrays() 
mi = pd.MultiIndex.from_arrays(employees, names=('emp_id', 'name'))

# display the Multiindex
print("The MultiIndex...\n",mi)
print()

# Get the levels in MultiIndex
print("The levels in MultiIndex...\n",mi.levels)
print()

# Create a DataFrame
df = mi.to_frame(name=['Emp. ID', 'Emp. Name'])

# Print the DataFrame
print("The DataFrame is...\n", df)

Output:

The MultiIndex...
 MultiIndex([('E101',   'Alex'),
            ('E102',  'Alvin'),
            ('E102', 'Deniel'),
            ('E103',  'Jenny')],
           names=['emp_id', 'name'])

The levels in MultiIndex...
 [['E101', 'E102', 'E103'], ['Alex', 'Alvin', 'Deniel', 'Jenny']]

The DataFrame is...
               Emp. ID Emp. Name
emp_id name                    
E101   Alex      E101      Alex
E102   Alvin     E102     Alvin
       Deniel    E102    Deniel
E103   Jenny     E103     Jenny

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