How to flatten MultiIndex Columns and Rows in Pandas

6 Tricks to effectively flatten MultiIndex columns and rows in a Pandas DataFrame

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A MultiIndex (also known as a hierarchical index) DataFrame allows you to have multiple columns acting as a row identifier and multiple rows acting as a header identifier.

Pandas MultiIndex DataFrame Example (Image by author)

MultIndex is very useful for doing sophisticated data analysis, especially for working with higher dimensional data. Pandas has various methods that can output a MultIndex DataFrame, for instance, groupby(), melt(), pivot_table(), stack() etc. However, sometimes it’s just easier to work with a single-level index in a DataFrame.

In this article, you’ll learn how to flatten MultiIndex columns and rows. This article is organized as follows:

1. Flatten columns: use get_level_values()
2. Flatten columns: use to_flat_index()
3. Flatten columns: join column labels
4. Flatten rows: flatten all levels
5. Flatten rows: flatten a specific level
6. Flatten rows: join row labels