I have split the data into training and testing and the confusion matrix give these results, not sure if is it the right thing
from sklearn.tree import DecisionTreeClassifier
dt=DecisionTreeClassifier()
dt.fit(X_train,y_train)
pred_dt_tr=dt.predict(X_train)
pred_dt=dt.predict(X_test)
from sklearn.metrics import confusion_matrix,classification_report,f1_score
print(confusion_matrix(y_test,pred_dt))
print(classification_report(y_test,pred_dt))