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Handle with type problem for OneHotEncoder.get_feature_names #16593 #21754

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Handle with type problem for OneHotEncoder.get_feature_names #16593 #21754

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ff3f5fd
Handle with type problem for get_feature_names
jfreneau Nov 23, 2021
77eb6ff
Update sklearn/preprocessing/_encoders.py
jfreneau Nov 26, 2021
b458a71
Merge branch 'scikit-learn:main' into main
jfreneau Nov 26, 2021
94fca3e
Update _encoders.py
jfreneau Nov 26, 2021
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8 changes: 6 additions & 2 deletions sklearn/preprocessing/_encoders.py
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Original file line number Diff line number Diff line change
Expand Up @@ -692,7 +692,9 @@ def get_feature_names(self, input_features=None):

feature_names = []
for i in range(len(cats)):
names = [input_features[i] + "_" + str(t) for t in cats[i]]
if not isinstance(input_features[i], str):
warnings.warn("Features names aren't strings, errors could occur")
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Please provide always the observed invalid value in error message, for instance:

    warnings.warn(
        "Unexpected type of feature name feature_names[{i}]={feature_names[i]!r}. "
        "Converting to str now. To silence this warning, please make sure encode "
        "feature names as `str` from the start."
    )

names = [str(input_features[i]) + "_" + str(t) for t in cats[i]]
if self.drop_idx_ is not None and self.drop_idx_[i] is not None:
names.pop(self.drop_idx_[i])
feature_names.extend(names)
Expand Down Expand Up @@ -724,7 +726,9 @@ def get_feature_names_out(self, input_features=None):

feature_names = []
for i in range(len(cats)):
names = [input_features[i] + "_" + str(t) for t in cats[i]]
if not isinstance(input_features[i], str):
warnings.warn("Features names aren't strings, errors could occur")
names = [str(input_features[i]) + "_" + str(t) for t in cats[i]]
if self.drop_idx_ is not None and self.drop_idx_[i] is not None:
names.pop(self.drop_idx_[i])
feature_names.extend(names)
Expand Down