Removing Multilevel Index Using Pivot Table

There are several methods to remove the multilevel index from a DataFrame in Pandas. Let’s explore each method in detail. Removing Multilevel Index:

• Using reset_index()
• Using droplevel()
• Using rename_axis()

1. Using reset_index()

The reset_index() method is the most straightforward way to remove the multilevel index. It resets the index of the DataFrame, converting the index levels into columns.

Output:

Subcategory        Date Category     X     Y
0            2023-01-01        A  10.0   NaN
1            2023-01-01        B   NaN  20.0
2            2023-01-02        A  30.0   NaN
3            2023-01-02        B   NaN  40.0
4            2023-01-03        A  50.0   NaN
5            2023-01-03        B   NaN  60.0

2. Using droplevel()

The droplevel() method can be used to remove specific levels from the index. This method is useful if you want to drop only certain levels of the multilevel index.

Output:

Subcategory         X   Y
Date                  
2023-01-01      10 NaN
2023-01-01     NaN  20
2023-01-02      30 NaN
2023-01-02     NaN  40
2023-01-03      50 NaN
2023-01-03     NaN  60

In this example, we dropped the ‘Category’ level from the index

3. Using rename_axis()

The rename_axis() method can be used to rename the index or column labels. By setting the index or column labels to None, you can effectively remove the multilevel index.

Output:

         Date Category     X     Y
0  2023-01-01        A  10.0   NaN
1  2023-01-01        B   NaN  20.0
2  2023-01-02        A  30.0   NaN
3  2023-01-02        B   NaN  40.0
4  2023-01-03        A  50.0   NaN
5  2023-01-03        B   NaN  60.0

Pandas is a powerful and versatile library in Python for data manipulation and analysis. One of its most useful features is the pivot table, which allows you to reshape and summarize data. However, using pivot tables often results in a multilevel (hierarchical) index, which can be cumbersome to work with. In this article, we will explore how to get rid of the multilevel index after using a pivot table in Pandas, making your data easier to handle and analyze.