python - Pandas 事件研究

Question

假设我有一个时间序列:

pd.Series(np.random.rand(20), index=pd.date_range("1990-01-01",periods=20))

这给出了，

1990-01-01    0.018363
1990-01-02    0.288625
1990-01-03    0.460708
1990-01-04    0.663063
1990-01-05    0.434250
1990-01-06    0.504893
1990-01-07    0.587743
1990-01-08    0.412223
1990-01-09    0.604656
1990-01-10    0.960338
1990-01-11    0.606765
1990-01-12    0.110480
1990-01-13    0.671683
1990-01-14    0.178488
1990-01-15    0.458074
1990-01-16    0.219303
1990-01-17    0.172665
1990-01-18    0.429534
1990-01-19    0.505891
1990-01-20    0.242567
Freq: D, dtype: float64

假设事件日期为 1990-01-05 和 1990-01-15。我想将数据子集化为围绕事件的长度为 (-2,+2) 的窗口，如下所示:

1990-01-03    0.460708
1990-01-04    0.663063
1990-01-05    0.434250
1990-01-06    0.504893
1990-01-07    0.587743
1990-01-13    0.671683
1990-01-14    0.178488
1990-01-15    0.458074
1990-01-16    0.219303
1990-01-17    0.172665
Freq: D, dtype: float64

我应该怎样做呢？

Answer 1

我认为你可以使用concat由列表理解使用 loc 创建的所有系列 :

date1 = pd.to_datetime('1990-01-05')
date2 = pd.to_datetime('1990-01-15')
window = 2

dates = [date1, date2]

s1 = pd.concat([s.loc[date - pd.Timedelta(window, unit='d'): 
                      date + pd.Timedelta(window, unit='d')] for date in dates])
print (s1)
1990-01-03    0.284356
1990-01-04    0.997019
1990-01-05    0.293225
1990-01-06    0.451379
1990-01-07    0.743209
1990-01-13    0.254926
1990-01-14    0.339728
1990-01-15    0.793124
1990-01-16    0.121002
1990-01-17    0.930924
dtype: float64