Fix pandas chained indexing to restore NumPy 2.x compatibility #854
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adilraza99
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…ility Replace chained .iloc[rows][column] with single-step .loc[rows, column] in plot_haplotype_network() to resolve NumPy 2.x compatibility issue. NumPy 2.0 removed the 'order' parameter from astype(), which pandas may call internally when processing chained indexing operations on string columns. The single-step .loc access avoids creating intermediate DataFrame objects and maintains identical behavior with both NumPy 1.26.x and 2.x. Fixes haplotype network plotting tests with NumPy 2.x.
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Hi @jonbrenas, This PR fixes the pandas chained indexing issue causing NumPy 2.x compatibility errors in the haplotype plotting path by switching to a single-step CI checks are pending due to fork restrictions. The fix has been verified locally and is scoped only to this issue. Happy to rerun checks or make adjustments if needed. Thanks! |
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Summary
This PR fixes a NumPy 2.x compatibility issue caused by pandas chained indexing in the
plot_haplotype_network()code path.The change replaces chained
.iloc[rows][column]access with a single-step.loc[rows, column]selection, avoiding intermediate object creation that can trigger NumPy 2.xastype(order=...)failures on string-backed arrays.Root Cause
The issue was triggered by the following chained indexing pattern: