我正在尝试将 category_encoders 的 OrdinalEncoder fit_transform 到我的 data 的列之一.
我尝试看到的documentation是:
import category_encoders as ce
# here i'm defining mapping for OrdinalEncoder
property_ordinal_mapping_1 = [{"col":"property_type", "mapping": [('Apartment', 1),('House', 2),('Condominium', 3),
('Townhouse', 4),('Loft', 5),('Other', 6),
('Guesthouse', 7),('Bed & Breakfast', 8),
('Bungalow', 9),('Villa', 10),('Dorm', 11),
('Guest suite', 12),('Camper/RV', 13),
('Timeshare', 14),('Cabin', 15),('In-law', 16),
('Hostel', 17),('Boutique hotel', 18),('Boat', 19),
('Serviced apartment', 20),('Tent', 21),('Castle', 22),
('Vacation home', 23),('Yurt', 24),('Hut', 25),
('Treehouse', 26),('Chalet', 27),('Earth House', 28),
('Tipi', 29),('Train', 30),('Cave', 31),
('Casa particular', 32),('Parking Space', 33),
('Lighthouse', 34),('Island', 35)
]
},
]
# preparing the OrdinalEncoder for fitting and transforming
property_encoder_1 = ce.OrdinalEncoder(mapping = property_ordinal_mapping_1, return_df = True, cols=["property_type"])
当我尝试fit_transfom时出现的问题是:
df_train = property_encoder_1.fit_transform(air_cat_2)
错误:
TypeError Traceback (most recent call last)
<ipython-input-96-9cea1713182c> in <module>()
----> 1 df_train = property_encoder_1.fit_transform(air_cat_2)
/usr/local/lib/python3.6/dist-packages/sklearn/base.py in fit_transform(self, X, y, **fit_params)
551 if y is None:
552 # fit method of arity 1 (unsupervised transformation)
--> 553 return self.fit(X, **fit_params).transform(X)
554 else:
555 # fit method of arity 2 (supervised transformation)
/usr/local/lib/python3.6/dist-packages/category_encoders/ordinal.py in fit(self, X, y, **kwargs)
139 cols=self.cols,
140 handle_unknown=self.handle_unknown,
--> 141 handle_missing=self.handle_missing
142 )
143 self.mapping = categories
/usr/local/lib/python3.6/dist-packages/category_encoders/ordinal.py in ordinal_encoding(X_in, mapping, cols, handle_unknown, handle_missing)
288 for switch in mapping:
289 column = switch.get('col')
--> 290 X[column] = X[column].map(switch['mapping'])
291
292 try:
/usr/local/lib/python3.6/dist-packages/pandas/core/series.py in map(self, arg, na_action)
3380 """
3381 new_values = super(Series, self)._map_values(
-> 3382 arg, na_action=na_action)
3383 return self._constructor(new_values,
3384 index=self.index).__finalize__(self)
/usr/local/lib/python3.6/dist-packages/pandas/core/base.py in _map_values(self, mapper, na_action)
1216
1217 # mapper is a function
-> 1218 new_values = map_f(values, mapper)
1219
1220 return new_values
pandas/_libs/lib.pyx in pandas._libs.lib.map_infer()
TypeError: 'list' object is not callable
sklearn.preprocessing.OrdinalEncoder 也有类似的错误。
我做错了什么以及如何解决这个问题。我已经仔细检查了我的专栏的类名并重写了整个代码，但似乎没有任何帮助；或者有什么替代方法可以做到这一点。
请不要将我的问题标记为重复。
最佳答案
文档不正确。 映射 的语法现在有所不同。参见这里:https://github.com/scikit-learn-contrib/categorical-encoding/issues/193
关于python - 无法使用category_encoders的fit_transform对我的数据进行序数编码，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/56655197/