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ENH num_features for a 1d collection of dicts is undefined #19740

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Mar 29, 2021
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7 changes: 5 additions & 2 deletions 7 sklearn/utils/tests/test_validation.py
Original file line number Diff line number Diff line change
Expand Up @@ -1345,9 +1345,10 @@ def test_num_features(constructor_name):
[1, 2, 3],
["a", "b", "c"],
[False, True, False],
[1.0, 3.4, 4.0]
[1.0, 3.4, 4.0],
[{"a": 1}, {"b": 2}, {"c": 3}],
],
ids=["int", "str", "bool", "float"]
ids=["int", "str", "bool", "float", "dict"]
)
@pytest.mark.parametrize("constructor_name", [
"list", "tuple", "array", "series"
Expand All @@ -1368,6 +1369,8 @@ def test_num_features_errors_1d_containers(X, constructor_name):
message += " with shape (3,)"
elif isinstance(X[0], str):
message += " where the samples are of type str"
elif isinstance(X[0], dict):
message += " where the samples are of type dict"
with pytest.raises(TypeError, match=re.escape(message)):
_num_features(X)

Expand Down
4 changes: 2 additions & 2 deletions 4 sklearn/utils/validation.py
Original file line number Diff line number Diff line change
Expand Up @@ -226,8 +226,8 @@ def _num_features(X):

first_sample = X[0]

# Do not consider an array-like of strings to be a 2D array
if isinstance(first_sample, (str, bytes)):
# Do not consider an array-like of strings or dicts to be a 2D array
if isinstance(first_sample, (str, bytes, dict)):
message += (f" where the samples are of type "
f"{type(first_sample).__qualname__}")
raise TypeError(message)
Expand Down
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