Extend ignored columns test to cover np.nan and pd.NA cases - #472
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manishaagangadevi wants to merge 1 commit into
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Extend ignored columns test to cover np.nan and pd.NA cases#472manishaagangadevi wants to merge 1 commit into
manishaagangadevi wants to merge 1 commit into
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| enc = getattr(encoders, encoder_name)(cols=['col1']) | ||
| out = enc.fit_transform(X, y) | ||
| self.assertTrue(out.col2[2] is None) | ||
| self.assertTrue(pd.isna(out.col2.iloc[2])) |
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why do you want to relax the check from is None to pd.isna? the precise point of this test is checking that it is still a python None
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Thanks for the clarification.
You’re right, the original test is meant to check that the value stays strictly None. I was trying to extend the test to also cover cases with np.nan and pd.NA, but I realise now that replacing the original assertion changes the intent of the test.
I’ll revert the strict None check and instead add separate tests for np.nan and pd.NA while keeping the original behaviour unchanged.
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Description
This pull request extends the existing test
test_ignored_columns_are_untouchedto additionally verify that ignored columns remain unchanged when containing
np.nanandpd.NAvalues.The existing test already checks behaviour for
Nonevalues. This change ensuresconsistent handling of other common missing value representations in pandas.
Changes Made
np.nanvalues in ignored columnspd.NAvalues in ignored columns