Understanding the Error: "ValueError: cannot reindex from a duplicate axis"

In pandas, the "ValueError: cannot reindex from a duplicate axis" is encountered when attempting to reindex or assign data along an axis that contains duplicate values. This issue arises when joining or assigning data to a column/row that has duplicate index values.

Applying the Concept to the Example

In the provided example, the user is attempting to set the index value 'sums' to the sum of all columns in the affinity_matrix DataFrame. However, the error is thrown because there is a duplicate value in the affinity_matrix.columns, which is not displayed in the given code snippet.

This duplicate value creates a conflict when trying to reindex or assign data along the columns axis. To resolve this issue, one needs to ensure that the index values in the DataFrame are unique before performing such operations.

Testing with a Simplified Example

Let's use a simplified example to further illustrate the error:

import pandas as pd
import numpy as np

a = np.arange(35).reshape(5, 7)
df = pd.DataFrame(a, ['x', 'y', 'u', 'z', 'w'], range(10, 17))
df.loc['sums'] = df.sum(axis=0)  # Assume that 'sums' is already an index value

# This would result in the ValueError, as 'sums' is a duplicate index value

The error occurs because the DataFrame 'df' already has an index value 'sums' in the rows, and attempting to create a new index value with the same name results in a duplicate axis.

Conclusion

The "ValueError: cannot reindex from a duplicate axis" error serves as a reminder to ensure uniqueness of index values in a DataFrame. Failing to do so can lead to issues when performing operations along specific axes, such as reindexing or assigning data.