import pandas as pd
from sklearn.tree import DecisionTreeClassifier

df = pd.read_csv('/datasets/train_data.csv')

df.loc[df['last_price'] > 5650000, 'price_class'] = 1
df.loc[df['last_price'] <= 5650000, 'price_class'] = 0

features = df.drop(['last_price', 'price_class'], axis=1)
target = df['price_class']

model = DecisionTreeClassifier(random_state=12345)

model.fit(features, target)

test_df = pd.read_csv('/datasets/test_data.csv')[:3]

test_df.loc[test_df['last_price'] > 5650000, 'price_class'] = 1
test_df.loc[test_df['last_price'] <= 5650000, 'price_class'] = 0

test_features = test_df.drop(['last_price', 'price_class'], axis=1)
test_target = test_df['price_class']
test_predictions = model.predict(test_features)

print("Предсказания:", test_predictions)
print("Правильные ответы:", test_target.values)