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onehotencoder = OneHotEncoder(categorical_features = [1]) X = onehotencoder.fit_transform(X).toarray() X = X[:, 1:]

lanzani answered on April 23, 2020 Popularity 9/10 Helpfulness 2/10

answer onehotencoder = OneHotEncoder(categorical_features = [1]) X = onehotencoder.fit_transform(X).toarray() X = X[:, 1:]

onehotencoder = OneHotEncoder(categorical_features = [1]) X = onehotencoder.fit_transform(X).toarray() X = X[:, 1:]

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from sklearn.compose import ColumnTransformer

ct = ColumnTransformer([('encoder', OneHotEncoder(), [1])], remainder='passthrough')
X = np.array(ct.fit_transform(X), dtype=np.float)

Popularity 9/10 Helpfulness 2/10 Language python

Source: Grepper

Tags: python

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Contributed on Apr 23 2020

lanzani

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onehotencoder = OneHotEncoder(categorical_features = [1]) X = onehotencoder.fit_transform(X).toarray() X = X[:, 1:]

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onehotencoder = OneHotEncoder(categorical_features = [1]) X = onehotencoder.fit_transform(X).toarray() X = X[:, 1:]

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