pandas 怎么对比当前行的前面 7 天的所有某列的数字？

我目前自己写的代码（第 2 个要求还没搞）
```
for i in range(1, end_num):

df['prev_row'] = df['total'].shift(i)

df['range_compare_result'] = df['total'].lt(df['prev_row'])

del df['prev_row']
# end for
```

In [2]: ret = []

In [2]: for i in range(7, a.shape[0]+1):
...: m = np.argmin(a[i-7:i]) +i -7
...: ret.append((m, a[m], m==i-1))
...:

In [3]: ret
Out[3]:
[(4, 0.1070058697941636, False), # (绝对索引，值，当日是否为当周（前 7 日）最低）
(4, 0.1070058697941636, False),
(4, 0.1070058697941636, False),
(4, 0.1070058697941636, False),
(4, 0.1070058697941636, False),
(7, 0.38082268305528855, False),
(7, 0.38082268305528855, False),
(13, 0.3198102115371413, True),
(13, 0.3198102115371413, False),
(15, 0.26007158139013975, True),
(15, 0.26007158139013975, False),
(15, 0.26007158139013975, False),
(18, 0.1774755070886418, True),
(18, 0.1774755070886418, False)]

In [4]: a
Out[4]:
array([0.59171944, 0.95287085, 0.56036765, 0.91771266, 0.10700587,
0.67920182, 0.40034268, 0.38082268, 0.81140219, 0.78271362,
0.43178875, 0.7328393 , 0.93324926, 0.31981021, 0.74938937,
0.26007158, 0.33768583, 0.78881252, 0.17747551, 0.27862649])

用 query

pandas 先 rolling 后 聚合，比如以每一天与过去 7 天做比较：
1. dataframe.rolling("7d").min() == dataframe
2. dataframe.rolling("7d").min()

```
df = pd.DataFrame(np.random.randint(10,50,30),index=pd.date_range(start='2021-01-01',periods=30),columns=["sales"])
df['pass_min'] = df.rolling(window=7, min_periods=1)['sales'].min()
df['is_min'] = df.sales==df.pass_min
```

这样吗？

滑动窗口 rolling().min()
和 query 判等应该可以解决

4 ，6 说得对

学习了，还有 rooling 这个方法