fix: normalize null types in QNAM columns after supp merge - #1782
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SFJohnson24 merged 3 commits intoJun 24, 2026
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The supp pivot uses pd.NA for empty cells, but the left join produces NaN for unmatched rows. On pandas 3.0 with nullable dtypes this creates mixed null types in the same column (NaN vs pd.NA), which fails strict equality checks. Normalizing with fillna(pd.NA) after the merge makes null representation consistent.
filippsatverily
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June 23, 2026 19:29
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@SFJohnson24 this should be the last PR before we can bump pandas |
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This PR adds null normalization for merge pivot. Test suite: #1785 and unit tests, pilot study fine
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The supp pivot (
process_supp) initializes QNAM columns withpd.NA, but the subsequent left join inmerge_pivot_supp_datasetfills unmatched rows withNaN. This creates mixed null types (NaNvspd.NA) in the same column. On pandas <3.0 this is invisible since both are treated identically, but on pandas 3.0 with nullable dtypes the inconsistency causes strict equality checks to fail. Addingfillna(pd.NA)after the merge normalizes null representation in the QNAM columns.Tested scenarios: