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- from numpy import asarray
- from sklearn.preprocessing import OrdinalEncoder
- data = asarray([['red'],['green'],['blue']])
- print(data)
- encoder = OrdinalEncoder()
- result = encoder.fit_transform(data)
- print(result)
- from numpy import asarray
- from sklearn.preprocessing import OneHotEncoder
- data = asarray([['red'],['green'],['blue']])
- print(data)
- encoder = OneHotEncoder()
- result = encoder.fit_transform(data)
- print(result)
- from numpy import asarray
- from sklearn.preprocessing import OneHotEncoder
- data = asarray([['red'],['green'],['blue']])
- print(data)
- encoder = OneHotEncoder(drop='first', sparse_output=False)
- result = encoder.fit_transform(data)
- print(result)
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