ColumnTransformer input feature name and count validation #14544
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now you only need to adjust the tests ;) |
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The failing test is @NicolasHug do you agree with this version? |
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My general thought is that we should have gone for a stricter version of #14237 and just error for any discrepancy match, as a bug fix. But OK for doing a deprecation. I'm OK with this but we still need to error when |
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I agree with all of that @NicolasHug. I lean a little more towards a deprecation. |
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I added a test for the case where the indexing is negative, I'd appreciate a close review on that part. |
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@amueller you fine with the changes? |
| X_array_fewer = np.array([[0, 1, 2], ]).T | ||
| err_msg = 'Number of features' | ||
| with pytest.raises(ValueError, match=err_msg): | ||
| ct.transform(X_array_fewer) | ||
| with pytest.warns(DeprecationWarning, match=msg): |
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Why warn when passing less features? I thought the only scenario we still accept is passing more features, not less?
This will be confusing for users since the message says it should not error until 0.24
| with pytest.raises(ValueError, match=err_msg): | ||
| tf.transform(X_trans_df) | ||
| with pytest.warns(DeprecationWarning, match=warn_msg): |
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same here, why warn here since we error as well?
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| tf = ColumnTransformer([('bycol', Trans(), [0, -1])]) | ||
| tf.fit(df_extra) | ||
| msg = "At least one negative column was used to" |
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can you also check that no warning is raised when n_features matches with negative indexing? Just in case.
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@NicolasHug done :) |
Fixes #14251.
This raises a deprecation warning if the
Xat the time of fit and transform don't match in terms of feature names or count. It implements option (1) of #14251 (comment)