您可以使用concat
+ shift
使用先前的值创建一个宽的 DataFrame,这使得复杂的滚动计算变得更容易。
样本数据
np.random.seed(42)
df = pd.DataFrame(np.random.randint(0, 100, size=(100, 2)), columns=list('AB'))
Code
N = 4
# End slice ensures same default min_periods behavior to `.rolling`
df1 = pd.concat([df['A'].shift(i).rename(i) for i in range(N)], axis=1).iloc[N-1:]
# Remove values larger than B, then find the max of remaining.
df['C'] = df1.where(df1.lt(df.B, axis=0)).max(1)
print(df.head(15))
A B C
0 51 92 NaN # Missing b/c min_periods
1 14 71 NaN # Missing b/c min_periods
2 60 20 NaN # Missing b/c min_periods
3 82 86 82.0
4 74 74 60.0
5 87 99 87.0
6 23 2 NaN # Missing b/c 82, 74, 87, 23 all > 2
7 21 52 23.0 # Max of 21, 23, 87, 74 which is < 52
8 1 87 23.0
9 29 37 29.0
10 1 63 29.0
11 59 20 1.0
12 32 75 59.0
13 57 21 1.0
14 88 48 32.0