python - 使用 Pandas DataFrame 逐行查找过去 6 个月内发生的事件

Question

假设我有这样一个数据集:

  id_police id_sinistre    datesurv
0      p123        s120  01/01/2018
1      p123        s121  03/01/2018
2      p123        s122  05/05/2018
3      p222        s123  04/05/2018
4      p222        s124  02/12/2018
5      p433        s125  07/08/2018
6      p433        s126  08/09/2018
7      p433        s127  10/10/2018

我的目标是在过去 6 个月中为每一行找到最后一次出现的 id_police，如下所示:

  id_police id_sinistre    datesurv  occ
0      p123        s120  01/01/2018    0
1      p123        s121  03/01/2018    1
2      p123        s122  05/05/2018    2
3      p222        s123  04/05/2018    0
4      p222        s124  02/12/2018    0
5      p433        s125  07/08/2018    0
6      p433        s126  08/09/2018    1
7      p433        s127  10/10/2018    2

我想我需要 .duplicated 或 .groupby 但我不确定如何使用它们...在此先感谢您的帮助!

Answer 1

如果 6 个月应该简化为 6 * 30 天，请使用带有 diff 的自定义 lambda 函数，按值和最后的累积总和进行比较:

df['datesurv'] = pd.to_datetime(df['datesurv'], dayfirst=True)

df = df.sort_values(['id_police','datesurv'])

f = lambda x: (x.diff().dt.days < 30 * 6).cumsum()
df['occ'] = df.groupby('id_police')['datesurv'].apply(f)

print (df)
  id_police id_sinistre   datesurv  occ
0      p123        s120 2018-01-01    0
1      p123        s121 2018-01-03    1
2      p123        s122 2018-05-05    2
3      p222        s123 2018-05-04    0
4      p222        s124 2018-12-02    0
5      p433        s125 2018-08-07    0
6      p433        s126 2018-09-08    1
7      p433        s127 2018-10-10    2