请考虑这个框架：

import pandas as pd
import numpy as np

values = [0, 22, 30, 0, 20, 22, 11, 0, 13]
index = pd.date_range(start = '2023-10-1', periods = len(values))

df = pd.DataFrame({'values':values }, index = index)

df
           values
2023-10-01  0
2023-10-02  22
2023-10-03  30
2023-10-04  0
2023-10-05  20
2023-10-06  22
2023-10-07  11
2023-10-08  0
2023-10-09  13

**目标：**创建一个新列，计算values中从最后一个0开始已经过去了多少天。

我可以使用for循环来实现：

zero_indices = df[df['values'] == 0].index
df['days'] = np.nan

for i in range(len(zero_indices)-1):
    df['days'][zero_indices[i]: zero_indices[i+1]] = range(len(df[zero_indices[i]: zero_indices[i+1]]))
df['days'][zero_indices[-1]: ] = range(len(df[zero_indices[-1]: ]))

           values   days
2023-10-01  0   0.00
2023-10-02  22  1.00
2023-10-03  30  2.00
2023-10-04  0   0.00
2023-10-05  20  1.00
2023-10-06  22  2.00
2023-10-07  11  3.00
2023-10-08  0   0.00
2023-10-09  13  1.00

问题：如何使用矢量化（更快）来实现这一点？