Transpose Columns in Python/Pandas

Introduction

In this article, we will explore how to transpose columns in a pandas DataFrame in Python. We will cover the various methods available and provide examples to illustrate each approach.

Setting Up Our Environment

For this example, we’ll be using the latest version of Python (3.x) and the pandas library.

!pip install -U pandas

We’ll create a sample DataFrame with 7 columns:

import pandas as pd

data = {
    'Name': ['foo', 'bar', 'nil'],
    'Value1': [0.994369885, 0.92930566, 0.997754262],
    'Value2': [0.780942307, 0.274566936, 0.488064461],
    'Value3': [0.510782105, 0.390724018, 0.642086396],
    'Value4': [0.842522334, 0.613705323, 0.028703768],
    'Value5': [0.383279727, 0.287280101, 0.764773601]
}

df = pd.DataFrame(data)
print(df)

This will output:

Reshaping the DataFrame

The goal is to have ‘Period’ as the index and the other columns as rows. We can achieve this by using the set_index method followed by the T attribute.

Using set_index

# Set 'Period' as the index
df_set_index = df.set_index('Period')

print(df_set_index)

This will output:

Using T

# Transpose the DataFrame using the 'T' attribute
df_transposed = df.set_index('Period').T

print(df_transposed)

This will output:

Conclusion

Transposing columns in a pandas DataFrame is a common requirement when working with tabular data. By using the set_index method and then applying the T attribute, you can achieve this in a single step.

We have covered the different methods available for reshaping the DataFrame, including setting ‘Period’ as the index followed by transposing the resulting table.

By following these steps, you should be able to easily transpose columns in your pandas DataFrames.

Last modified on 2025-01-27