`from sklearn import preprocessing
le = preprocessing.LabelEncoder()
for unique_hash in train.columns:
        if train[unique_hash].dtype == object:
            train[unique_hash] = le.fit_transform(train[unique_hash])
        else:
            pass`

`sent_classifier = DecisionTreeClassifier(max_leaf_nodes=10, random_state=0)
sent_classifier.fit(X_train, y_train)`