# 这个区别方式适用于没有直接label coding的数据，意思是没有人为都转变为 数字的特征 # 这里不适用，需要人为根据实际含义来区分，意思 是需要自己挑选出那一些 类型特征 # 数字特征 numeric_features = Test_data.select_dtypes(include=[np.number]) print("数字特征：", numeric_features.columns) # 类型特征 categorical_features = Test_data.select_dtypes(include=[np.object]) print("类型特征：", categorical_features.columns)raise AttributeError(__former_attrs__[attr]) AttributeError: module 'numpy' has no attribute 'object'. `np.object` was a deprecated alias for the builtin `object`. To avoid this error in existing code, use `object` by itself. Doing this will not modify any behavior and is safe. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:；Did you mean: 'object_'?

这个错误提示是因为在numpy库中，np.object已经被弃用了，应该使用object来代替。你可以将代码中的np.object替换为object就可以解决这个错误了。具体来说，你可以将代码修改为下面这样：

# 数字特征
numeric_features = Test_data.select_dtypes(include=[np.number])
print("数字特征：", numeric_features.columns)

# 类型特征
categorical_features = Test_data.select_dtypes(include=[object])
print("类型特征：", categorical_features.columns)

这样就不会再出现这个错误了。