我具有不规则采样时间序列距离到多个不规则采样的事件熊猫
event
Time
2013-01-01 01:40:53.072 n
2013-01-01 01:41:25.563 e
2013-01-01 01:51:23.293 e
2013-01-01 01:57:14.168 e
2013-01-01 01:58:07.273 e
2013-01-01 02:05:36.250 e
2013-01-01 02:35:08.501 e
2013-01-01 02:37:36.498 e
2013-01-01 03:22:15.091 e
2013-01-01 03:35:58.140 e
2013-01-01 03:39:47.682 e
2013-01-01 04:22:18.756 e
2013-01-01 04:33:08.892 e
2013-01-01 04:43:17.985 n
2013-01-01 04:49:49.281 e
2013-01-01 05:10:26.957 e
2013-01-01 05:17:15.411 e
2013-01-01 06:11:15.033 e
2013-01-01 06:46:36.406 e
2013-01-01 07:26:00.488 e
,我想计算每个事件n
之间的累积经过的时间。 还有一个类似的问题(Pandas time series time between events),但由于不规则的timeindex,我无法使解决方案适应我的问题。我尝试使用df1['diff']=df1.groupby('event_bool')['event_time'].diff()
获得这样的事情:
event event_bool diff
Time
2013-01-01 01:40:53.072 n True NaT
2013-01-01 01:41:25.563 e False NaT
2013-01-01 01:51:23.293 e False 00:09:57.730000
2013-01-01 01:57:14.168 e False 00:05:50.875000
2013-01-01 01:58:07.273 e False 00:00:53.105000
2013-01-01 02:05:36.250 e False 00:07:28.977000
2013-01-01 02:35:08.501 e False 00:29:32.251000
2013-01-01 02:37:36.498 e False 00:02:27.997000
2013-01-01 03:22:15.091 e False 00:44:38.593000
2013-01-01 03:35:58.140 e False 00:13:43.049000
2013-01-01 03:39:47.682 e False 00:03:49.542000
2013-01-01 04:22:18.756 e False 00:42:31.074000
2013-01-01 04:33:08.892 e False 00:10:50.136000
2013-01-01 04:43:17.985 n True NaT
2013-01-01 04:49:49.281 e False 00:16:40.389000
2013-01-01 05:10:26.957 e False 00:20:37.676000
2013-01-01 05:17:15.411 e False 00:06:48.454000
2013-01-01 06:11:15.033 e False 00:53:59.622000
2013-01-01 06:46:36.406 e False 00:35:21.373000
2013-01-01 07:26:00.488 e False 00:39:24.082000
但是我有以下的未解决问题:
- 没有为
n
后的第一个事件e
在NAT。结果应该是'00:00:32.491000`` - Ho会累计累计
n
事件之间的经过时间?
不错!但是,我无法解决'diff'列的转变。第一个'e'应该是'00:00:32.491000'的差异,而不是NaT。第二个'n'之后的第一个'e'应该显示'2013-01-01 04:49:49.281 - 2013-01-01 04:43:17.985 = 00:06:31.296' – lorenzo
@lorenzo Oh ...我在问题中匹配你的输出。这看起来更好吗? –
工程就像一个魅力!谢谢@Scott – lorenzo