Label Encoding for machine learning and data science in python using sklearn

from sklearn import preprocessing

label_encoder = preprocessing.LabelEncoder()
input_classes = ['suzuki', 'ford', 'suzuki', 'toyota', 'ford', 'bmw']
label_encoder.fit(input_classes)
print("\nClass mapping:")
for i, item in enumerate(label_encoder.classes_):
    print(item, '-->', i)

labels = ['toyota', 'ford', 'suzuki']
encoded_labels = label_encoder.transform(labels)
print "\nLabels =", labels
print "Encoded labels =", list(encoded_labels)

######decoding

encoded_labels = [3, 2, 0, 2, 1]
decoded_labels = label_encoder.inverse_transform(encoded_labels)
print "\nEncoded labels =", encoded_labels
print "Decoded labels =", list(decoded_labels)