熊猫：在时间窗口上移动总和条件

Question

我有一个数据框，其中包含特定计算机的布尔故障（带有时间戳）。我想添加一个列，该列为特定机器执行相对于时间戳的特定时间范围内所有故障的移动总和。例如，计算线路故障前8天到1天之间每台机器发生的故障数。

这会创建一个初始数据帧的示例：

import pandas as pd
df1=pd.DataFrame({"Machine":["M0","M2","M3","M0","M2","M3"],"Failure":[0,0,1,1,1,1],"Date-time":["2014-02-20 11:00:19.0","2014-02-21 12:29:55.0","2014-02-20 11:00:21.0","2014-02-19 09:10:19.0","2014-02-18 12:19:47.0","2014-02-20 1:33:00.0"]})

这将创建一个示例输出数据框：

df1=pd.DataFrame({"Machine":["M0","M2","M3","M0","M2","M3"],"Number of failures, d-8 to d-1":[1,1,0,0,0,0],"Failure":[0,0,1,1,1,1],"Date-time":["2014-02-20 11:00:19.0","2014-02-21 12:29:55.0","2014-02-20 11:00:21.0","2014-02-19 09:10:19.0","2014-02-18 12:19:47.0","2014-02-20 1:33:00.0"]})

Answer 1

我发现了一个类似的问题，在这里回答。

Pandas temporal cumulative sum by group

它可能值得保留两个线程，因为它们的措辞非常不同。这可能有助于搜索。