Pandas获取连续至少5行值为0.0的首次出现索引位置

假设我有如下结构的pandas DataFrame：

import pandas as pd

lst = [45.45454545454545, 45.45454545454545, 45.45454545454545, 45.45454545454545, 45.45454545454545, 36.36363636363637, 36.36363636363637, 36.36363636363637, 27.27272727272727, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 27.27272727272727, 0.0, 0.0, 27.27272727272727, 0.0, 0.0, 0.0, 0.0, 27.27272727272727, 0.0, 0.0, 0.0, 36.36363636363637, 0.0, 27.27272727272727, 0.0, 27.27272727272727, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 27.27272727272727, 27.27272727272727, 54.54545454545454, 27.27272727272727, 36.36363636363637, 36.36363636363637, 54.54545454545454, 36.36363636363637, 45.45454545454545, 45.45454545454545, 36.36363636363637, 36.36363636363637, 45.45454545454545, 45.45454545454545, 36.36363636363637, 45.45454545454545, 36.36363636363637, 45.45454545454545, 36.36363636363637, 45.45454545454545, 36.36363636363637, 36.36363636363637, 36.36363636363637, 0.0, 36.36363636363637, 27.27272727272727, 0.0, 36.36363636363637, 0.0, 36.36363636363637, 36.36363636363637, 0.0, 0.0, 27.27272727272727, 0.0, 36.36363636363637, 0.0, 0.0, 0.0, 0.0, 36.36363636363637, 36.36363636363637, 0.0, 36.36363636363637, 36.36363636363637, 27.27272727272727, 27.27272727272727, 36.36363636363637, 36.36363636363637, 36.36363636363637, 36.36363636363637, 0.0, 27.27272727272727, 0.0, 0.0, 0.0, 27.27272727272727, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 27.27272727272727, 36.36363636363637, 0.0, 0.0, 0.0, 0.0, 0.0]
df = pd.DataFrame(lst,columns =['%'])
df.index.name='Time/ps'
df

需求：查询首次出现“%”列下降至0.0时对应的Time/ps索引值，筛选条件为该起始位置之后至少有连续5行的“%”列值均为0.0。

之前尝试的代码只能打印所有连续0值分组，需要手动查找结果，无法自动返回符合要求的位置：

for k, v in df[df['%'] == 0.000000].groupby((df['%'] != 0.000000).cumsum()):
    print(f'[group {k}]')
    print(v)
    print('\n')

期望输出格式为：Time/ps: 9

直接基于连续段分组逻辑做过滤，不需要手动遍历打印：

# 给连续相同值的段分配唯一组ID：遇到非0值时ID累加，同一段连续0值共享同一ID
df['seg_id'] = (df['%'] != 0.0).cumsum()

# 筛选出所有值为0的行，按组过滤出连续长度≥5的0值段
valid_seg = df[df['%'] == 0.0].groupby('seg_id').filter(lambda x: len(x) >= 5)

# 取第一个符合要求的段的起始索引
first_idx = valid_seg.index[0]
print(f'Time/ps: {first_idx}')

运行后直接输出：Time/ps: 9

注意：如果数据存在浮点数计算精度问题（比如计算得到的1e-16这类近似0的值），可以导入numpy后用np.isclose(df['%'], 0.0)代替df['%'] == 0.0做判断，结果更稳妥。

内容的提问来源于stack exchange，提问作者HungryMolecule