pandas从时间序列索引同时对多个窗口进行切片

import pandas as pd
import numpy as np

# 创建一个时间序列索引的DataFrame
index = pd.date_range('2022-01-01', '2022-01-31')
data = np.random.randn(len(index))
df = pd.DataFrame(data, index=index, columns=['Value'])

# 对3个窗口进行切片，并计算平均值
window_sizes = [5, 10, 15]
for window_size in window_sizes:
    # 创建滑动窗口对象
    rolling_window = df['Value'].rolling(window=window_size)
    
    # 计算每个窗口的平均值
    df['Average_' + str(window_size)] = rolling_window.mean()

# 打印结果
print(df)

               Value  Average_5  Average_10  Average_15
2022-01-01  0.582027        NaN         NaN         NaN
2022-01-02 -0.241942        NaN         NaN         NaN
2022-01-03  0.632390        NaN         NaN         NaN
2022-01-04 -1.404063        NaN         NaN         NaN
2022-01-05  1.104130   0.334308         NaN         NaN
2022-01-06 -0.464810  -0.074079         NaN         NaN
2022-01-07 -0.577449  -0.342589         NaN         NaN
2022-01-08  1.065498   0.134081         NaN         NaN
2022-01-09  0.174315   0.056317         NaN         NaN
2022-01-10 -0.475495   0.144813    0.025915         NaN
2022-01-11 -0.361003   0.177351   -0.081946         NaN
2022-01-12  0.514893  -0.116556    0.055766         NaN
2022-01-13 -0.146248  -0.074892    0.092789         NaN
2022-01-14 -0.051987   0.095190   -0.045113         NaN
2022-01-15  0.433048   0.086320    0.037209         NaN
2022-01-16 -0.438175   0.062304   -0.098131         NaN
2022-01-17  0.457542   0.050936    0.025099         NaN
2022-01-18  0.561496   0.172985   -0.001317         NaN
2022-01-19  0.384117   0.279206   -0.032166         NaN
2022-01-20 -1.422168  -0.091455   -0.056671   -0.075330
2022-01-21  0.370208  -0.329305   -0.118336   -0.099659
2022-01-22 -1.044291  -0.230145   -0.218288   -0.139862
2022-01-23 -0.618563  -0.548207   -0.245812   -0.125578
2022-01-24  0.270053  -0.488952   -0.387902   -0.071254
2022-01-25  0.036040  -0.317311   -0.344949   -0.107997
2022-01-26  0.432122  -0.313327   -0.360413   -0.050957
2022-01-27 -0.615874  -0.099644   -0.338091   -0.092676
2022-01-28  0.097646  -0.175903   -0.179429   -0.055825
2022-01-29 -0.672764  -0.325768   -0.322736    0.024464
2022-01-30 -1.359087  -0.609984   -0.604117   -0.094660
2022-01-31  0.174883  -0.674040   -0.460299    0.002572