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I am using linearsvc for prediction. I want to use two columns to predict the class of an item. I have written code by using only one column how to inlcude two columns for that.

labels_T = df_T['Asso_Sub']
text_T=df_T['Title']
count_vect = CountVectorizer()
model= LinearSVC()


#######Title#######
X_train_T, X_test_T, y_train_T, y_test_T = train_test_split(text_T, labels_T, random_state = 0, test_size =0.3)

X_train_counts_T = count_vect.fit_transform(X_train_T)
tf_transformer_T = TfidfTransformer().fit(X_train_counts_T)
X_train_tfidf_T = tf_transformer_T.transform(X_train_counts_T)

X_test_counts_T = count_vect.transform(X_test_T)
X_test_tfidf_T = tf_transformer_T.transform(X_test_counts_T)

y_test_counts_T = count_vect.transform(y_test_T)
y_test_tfidf_T = tf_transformer_T.transform(y_test_counts_T)

labels_T=LabelEncoder()
y_train_labels_fit_T=labels_T.fit(y_train_T)
y_train_labels_trf_T=labels_T.transform(y_train_T)


clf_T=model.fit(X_train_tfidf_T,y_train_labels_trf_T)
##################################################################################
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