Comments (3)
I agree that string and arrow string should be recognized as categorical.
Even the categorical type itself it currently not recognized as such.
That's the function that need to be adjusted (and renamed)
from category_encoders.
alright, I'll make a pr
from category_encoders.
thanks
from category_encoders.
Related Issues (20)
- Equivalent method to sklearn's partial_fit? HOT 1
- CountEncoder incorrectly counts Timestamp columns HOT 3
- Target encoding categories with a single training example HOT 1
- DOC: one of the source links is dead HOT 1
- Missing text in documentation HOT 2
- Support Pandas 2.1 HOT 1
- Feature Request: Count-Based Target Encoder (Dracula)? HOT 1
- Pandas copy-on-write doesn't work properly HOT 2
- pd.NA should behave as np.nan HOT 5
- Multidimensional/composite target encoding HOT 4
- FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. HOT 2
- Support for Spark HOT 1
- EOF Error Raised while Calling HashingEncoders function HOT 6
- why we combine this library with main sklearn ? HOT 1
- catboost encoder get different result with catboost HOT 8
- Combining with set_output can produce errors HOT 1
- AttributeError: 'DataFrame' object has no attribute 'unique' HOT 1
- [Question; need help; support request] Possible to join multiple CountEncoders after parallel (multiprocessing) fitting? HOT 1
- FutureWarning in ordinal encoder when downcasting objects HOT 2
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from category_encoders.