python - 在下一次应用迭代 python 中使用应用 fnc 的输出

Question

下面是 1. 开始 df(称为“关闭”)，和 2. 应用代码行及其生成的 df:

1.

Date    
2006-01-27  100.0
2006-01-30  100.0
2006-01-31  100.0
2006-02-01  100.0
2006-02-02  NaN
2006-02-03  NaN

2.

close.apply(lambda x: x.shift(1) + (x.shift(4))

Date    
2006-01-27  NaN
2006-01-30  NaN
2006-01-31  NaN
2006-02-01  NaN
2006-02-02  100.706786
2006-02-03  NaN

我的预期输出是使用 #2 (100.706786) 的输出和现有的 df“关闭”来计算序列中的下一个值，即 2/03 。该日期需要最后一个值(第 1 类)和从那时起的 4 个值(第 4 类或 100)。

如何只使用矢量化来做到这一点？我想避免 for 循环，因为它非常慢。这是我的:

closedf = pd.DataFrame()
for num,date in enumerate(close.index[4:]):
    widget = close.apply(lambda x: x.shift(1) + (x.shift(4)).iloc[num+4]
    closedf[date] = close.iloc[num+4] = widget

Answer 1

考虑一系列 close

close = pd.Series(
    [100] * 3 + [100.706786] + [np.nan] * 10,
    pd.date_range('2006-01-27', periods=14, name='Date')
)

close

Date
2006-01-27    100.000000
2006-01-28    100.000000
2006-01-29    100.000000
2006-01-30    100.706786
2006-01-31           NaN
2006-02-01           NaN
2006-02-02           NaN
2006-02-03           NaN
2006-02-04           NaN
2006-02-05           NaN
2006-02-06           NaN
2006-02-07           NaN
2006-02-08           NaN
2006-02-09           NaN
Freq: D, dtype: float64

---

解决方案
这是斐波那契数列的导数。据我所知，我们不能“向量化”...(w/e“向量化”意味着)

但是我们可以创建一个执行任务的生成器

def shib(x1, x2, x3, x4):
    while True:
        x1, x2, x3, x4 = x2, x3, x4, x1 + x4
        yield x4

然后用它来分配新的变量

from itertools import islice

close.iloc[4:] = list(islice(shib(*close[:4]), 0, len(close) - 4))

close

Date
2006-01-27     100.000000
2006-01-28     100.000000
2006-01-29     100.000000
2006-01-30     100.706786
2006-01-31     200.706786
2006-02-01     300.706786
2006-02-02     400.706786
2006-02-03     501.413572
2006-02-04     702.120358
2006-02-05    1002.827144
2006-02-06    1403.533930
2006-02-07    1904.947502
2006-02-08    2607.067860
2006-02-09    3609.895004
Freq: D, dtype: float64