onehotencoder = OneHotEncoder(categorical_features = [3]) code example

Example 1: OneHotEncoder(categorical_features=

#Encoding the categorical data
from sklearn.preprocessing import LabelEncoder

labelencoder_X = LabelEncoder()
X[:,0] = labelencoder_X.fit_transform(X[:,0])

#we are dummy encoding as the machine learning algorithms will be
#confused with the values like Spain > Germany > France
from sklearn.preprocessing import OneHotEncoder

onehotencoder = OneHotEncoder(categorical_features=[0])
X = onehotencoder.fit_transform(X).toarray()

Example 2: onehotencoder = OneHotEncoder(categorical_features = [1]) X = onehotencoder.fit_transform(X).toarray() X = X[:, 1:]

from sklearn.compose import ColumnTransformer

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