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Understanding "ValueError: cannot reindex from a duplicate axis"
In Pandas, reindexing refers to the operation of changing the row or column labels of a DataFrame. When a reindex operation is attempted and a duplicate axis is encountered, the "ValueError: cannot reindex from a duplicate axis" error is raised.
Explanation
This error typically occurs when you assign a new row or column to a DataFrame whose index (row labels) or columns (column labels) contain duplicate values.
In the context of your question, you are assigning a new row named 'sums' to the affinity_matrix DataFrame. However, the error suggests that affinity_matrix may have duplicate values in its columns. This is likely the cause of the issue.
Example
Consider the following DataFrame with string-label rows and integer-label columns:
import pandas as pd df = pd.DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 9]], index=["a", "b", "c"], columns=[1, 2, 2])
In this DataFrame, column 2 appears twice. If we try to assign a new row named 'sum' by summing the values in each column, we will encounter the same error:
df.loc['sum'] = df.sum(axis=0)
ValueError: cannot reindex from a duplicate axis
This error occurs because the DataFrame already has a column labeled '2,' and attempting to reindex from it would create an ambiguous assignment.
Solving the Issue
To resolve this issue, you need to verify that the indices or column labels of your DataFrame do not contain duplicate values. If they do, you can either remove the duplicate values or re-label them uniquely.
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