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Commit 80f923e

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ENH num_features for a 1d collection of dicts is undefined (#19740)
Co-authored-by: Christian Lorentzen <lorentzen.ch@gmail.com>
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‎sklearn/utils/tests/test_validation.py

Copy file name to clipboardExpand all lines: sklearn/utils/tests/test_validation.py
+5-2Lines changed: 5 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1345,9 +1345,10 @@ def test_num_features(constructor_name):
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[1, 2, 3],
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["a", "b", "c"],
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[False, True, False],
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[1.0, 3.4, 4.0]
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[1.0, 3.4, 4.0],
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[{"a": 1}, {"b": 2}, {"c": 3}],
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],
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ids=["int", "str", "bool", "float"]
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ids=["int", "str", "bool", "float", "dict"]
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)
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@pytest.mark.parametrize("constructor_name", [
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"list", "tuple", "array", "series"
@@ -1368,6 +1369,8 @@ def test_num_features_errors_1d_containers(X, constructor_name):
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message += " with shape (3,)"
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elif isinstance(X[0], str):
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message += " where the samples are of type str"
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elif isinstance(X[0], dict):
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message += " where the samples are of type dict"
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with pytest.raises(TypeError, match=re.escape(message)):
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_num_features(X)
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‎sklearn/utils/validation.py

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+2-2Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -226,8 +226,8 @@ def _num_features(X):
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first_sample = X[0]
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# Do not consider an array-like of strings to be a 2D array
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if isinstance(first_sample, (str, bytes)):
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# Do not consider an array-like of strings or dicts to be a 2D array
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if isinstance(first_sample, (str, bytes, dict)):
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message += (f" where the samples are of type "
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f"{type(first_sample).__qualname__}")
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raise TypeError(message)

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