如何在python数据框中动态添加列，以便为数据框中的每个变量包含高阶项？

import pandas as pd
import numpy as np

data = {'A': [1, 2, 3],
        'B': [4, 5, 6]}
df = pd.DataFrame(data)

def generate_higher_order_terms(x, degree):
    terms = [x]
    for i in range(2, degree+1):
        terms.append(np.power(x, i))
    return terms

degree = 3  # 设置高阶项的最高次数
for column in df.columns:
    terms = generate_higher_order_terms(df[column], degree)
    for i, term in enumerate(terms):
        df[f'{column}_degree_{i+1}'] = term

import pandas as pd
import numpy as np

# 创建示例数据框
data = {'A': [1, 2, 3],
        'B': [4, 5, 6]}
df = pd.DataFrame(data)

# 定义生成高阶项的函数
def generate_higher_order_terms(x, degree):
    terms = [x]
    for i in range(2, degree+1):
        terms.append(np.power(x, i))
    return terms

# 添加高阶项列
degree = 3
for column in df.columns:
    terms = generate_higher_order_terms(df[column], degree)
    for i, term in enumerate(terms):
        df[f'{column}_degree_{i+1}'] = term

# 打印结果
print(df)

   A  B  A_degree_2  A_degree_3  B_degree_2  B_degree_3
0  1  4           1           1           4           4
1  2  5           4           8          25          125
2  3  6           9          27          36          216