1017 ddf00102 #1469
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1017 ddf00102 #1469
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…ed distinct operations
gerrycampion
requested changes
Dec 5, 2025
Comment on lines
158
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167
| non_null_values = [] | ||
| for val in column: | ||
| if val is None: | ||
| continue | ||
| try: | ||
| if pd.isna(val): | ||
| continue | ||
| except (ValueError, TypeError): | ||
| pass | ||
| non_null_values.append(val) |
Collaborator
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i believe you can replace this block with:
non_null_values = column[column.notnull()]
it will be useful to take a tutorial to learn some pandas fundamentals
gerrycampion
requested changes
Dec 5, 2025
Comment on lines
516
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570
| @pytest.mark.parametrize( | ||
| "column_data,expected", | ||
| [ | ||
| ([["A", "B"], ["C", "D"], ["E", "F"]], True), | ||
| ([{"A", "B"}, {"C", "D"}], True), | ||
| ([None, ["A", "B"], ["C", "D"]], True), | ||
| ([["A", "B"], None, ["C", "D"]], True), | ||
| ([["A", "B"], ["C", "D"], None], True), | ||
| ([None, None, ["A", "B"]], True), | ||
| ([None, {"A", "B"}, {"C", "D"}], True), | ||
| ([[]], True), | ||
| ([set()], True), | ||
| ([None, []], True), | ||
| ([None, set()], True), | ||
| ([["A"], []], True), | ||
| ([["A"], set()], True), | ||
| ([{"A"}, []], True), | ||
| ([["A"]], True), | ||
| ([{"A"}], True), | ||
| ([None, ["A"]], True), | ||
| ([["A"], {"B"}], True), | ||
| ([None, ["A"], {"B"}], True), | ||
| ([float("nan")], False), | ||
| ([None, float("nan")], False), | ||
| ([None, float("nan"), ["A"]], True), | ||
| ([float("nan"), ["A"]], True), | ||
| # Negative cases - not iterables | ||
| (["A", "B", "C"], False), | ||
| ([None, "A", "B"], False), | ||
| ([["A", "B"], "C", ["D", "E"]], False), | ||
| ([None, None, None], False), | ||
| ([], False), | ||
| ([("A", "B")], False), | ||
| ([None, ("A", "B")], False), | ||
| ([["A"], ("B", "C")], False), | ||
| ], | ||
| ) | ||
| def test_is_column_of_iterables(column_data, expected): | ||
| df = PandasDataset.from_dict({"col": column_data}) | ||
| dataframe_operator = DataframeType({"value": df}) | ||
| result = dataframe_operator.is_column_of_iterables(df["col"]) | ||
| assert result == expected | ||
|
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| def test_is_column_of_iterables_with_pd_na(): | ||
| """Test pd.NA handling (pandas NA value)""" | ||
| import pandas as pd | ||
|
|
||
| test_cases = [ | ||
| ([pd.NA], False), | ||
| ([None, pd.NA], False), | ||
| ([None, pd.NA, ["A"]], True), | ||
| ([pd.NA, ["A"]], True), | ||
| ([None, pd.NA, ["A"], ["B"]], True), | ||
| ] |
Collaborator
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Sorry, one more thing. I think these test cases should be combined to a single function
ASL-rmarshall
approved these changes
Dec 5, 2025
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ASL-rmarshall
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ASL-rmarshall
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General code review looks good. Validation produced expected results.
…test cases to a single function
gerrycampion
approved these changes
Dec 5, 2025
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Fixes Issue #1017 (CORERULES-9645): Updated
is_column_of_iterablesto check all non-null values instead of only the first row. When the first row isNone(common after grouped distinct operations with LEFT joins), the method now correctly identifies columns containing iterables by examining all non-null values. Also fixed boolean column reading in Excel files by using nullable boolean dtype ("boolean") and addingtrue_values/false_valuesparameters to handleNaNvalues. This fix ensures containment operators work correctly with columns containingNonevalues and affects USDM rules using grouped distinct operations with containment operators.