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Reset a column multiindex levels

Given a pandas multiindex dataframe, we have to reset a column multiindex levels. By Pranit Sharma Last updated : September 30, 2023

Pandas is a special tool that allows us to perform complex manipulations of data effectively and efficiently. Inside pandas, we mostly deal with a dataset in the form of DataFrame. DataFrames are 2-dimensional data structures in pandas. DataFrames consist of rows, columns, and data.

Multilevel indexing is a type of indexing that include different levels of indexes or simply multiple indexes. The DataFrame is classified under multiple indexes and the topmost index layer is presented as level 0 of the multilevel index followed by level 1, level 2, and so on.

Resetting a column multiindex levels

For this purpose, we will use DataFrame.columns.droplevel() method (this method returns Series/DataFrame with requested index / column level(s) removed) inside which we will pass the level number.

Let us understand with the help of an example,

Python program to reset a column multiindex levels

# Importing pandas package
import pandas as pd

# Creating multiindex DataFrame
# Creating multilevel index
index = pd.MultiIndex.from_tuples([
    ('Vitamin A','Sources'),
    ('Vitamin C', 'Sources'),
    ('Vitamin D','Sources')])

# Creating a multilevel index DataFrame 
# with columns = multilevel indexes
df = pd.DataFrame([
    ['Papaya','Orange','Oily Fish'],
    ['Watermelon','Blackcurrent','Red meat'],
    ['Mango','Kale','egg yolks']
    ], columns=index)

# Display Original DataFrames
print("Created DataFrame:\n",df,"\n")

# Dropping column levels
df.columns = df.columns.droplevel(0)

# Display result
print("Modified DataFrame:\n",df)

Output

The output of the above program is:

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