X = df_lr[["merc_x", "merc_y"]]
y = df_lr["price_cat"]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)
neigh = KNeighborsClassifier(n_neighbors=80)
neigh.fit(X_train, y_train)
y_pred=neigh.predict(X_test)
print("Accuracy: {:.2f}%".format(100*metrics.accuracy_score(y_test, y_pred)))
Accuracy: 44.35%