所以，这是我的问题。我有一个放射性标记蜂鸟位置的数据集，我一直在关注我作为论文的一部分。正如你可能想象的那样，它们飞得很快，所以当我失去对它们的位置的记录时，我会再次找到它们。 现在我试图识别连续跟踪鸟的区段（即“丢失”区间之间的间隔）。
ID Type TimeStart TimeEnd Limiter Starter Ender
1 Observed 6:45:00 6:45:00 NO Start End
2 Lost 6:45:00 5:31:00 YES NO NO
3 Observed 5:31:00 5:31:00 NO Start NO
4 Observed 9:48:00 9:48:00 NO NO NO
5 Observed 10:02:00 10:02:00 NO NO NO
6 Observed 10:18:00 10:18:00 NO NO NO
7 Observed 11:00:00 11:00:00 NO NO NO
8 Observed 13:15:00 13:15:00 NO NO NO
9 Observed 13:34:00 13:34:00 NO NO NO
10 Observed 13:43:00 13:43:00 NO NO NO
11 Observed 13:52:00 13:52:00 NO NO NO
12 Observed 14:25:00 14:25:00 NO NO NO
13 Observed 14:46:00 14:46:00 NO NO End
14 Lost 14:46:00 10:47:00 YES NO NO
15 Observed 10:47:00 10:47:00 NO Start NO
16 Observed 10:57:00 11:00:00 NO NO NO
17 Observed 11:10:00 11:10:00 NO NO NO
18 Observed 11:19:00 11:27:55 NO NO NO
19 Observed 11:28:05 11:32:00 NO NO NO
20 Observed 11:45:00 12:09:00 NO NO NO
21 Observed 11:51:00 11:51:00 NO NO NO
22 Observed 12:11:00 12:11:00 NO NO NO
23 Observed 13:15:00 13:15:00 NO NO End
24 Lost 13:15:00 7:53:00 YES NO NO
25 Observed 7:53:00 7:53:00 NO Start NO
26 Observed 8:48:00 8:48:00 NO NO NO
27 Observed 9:25:00 9:25:00 NO NO NO
28 Observed 9:26:00 9:26:00 NO NO NO
29 Observed 9:32:00 9:33:25 NO NO NO
30 Observed 9:33:35 9:33:35 NO NO NO
31 Observed 9:42:00 9:42:00 NO NO NO
32 Observed 9:44:00 9:44:00 NO NO NO
33 Observed 9:48:00 9:48:00 NO NO NO
34 Observed 9:48:30 9:48:30 NO NO NO
35 Observed 9:51:00 9:51:00 NO NO NO
36 Observed 9:54:00 9:54:00 NO NO NO
37 Observed 9:55:00 9:55:00 NO NO NO
38 Observed 9:57:00 10:01:00 NO NO NO
39 Observed 10:02:00 10:02:00 NO NO NO
40 Observed 10:04:00 10:04:00 NO NO NO
41 Observed 10:06:00 10:06:00 NO NO NO
42 Observed 10:20:00 10:33:00 NO NO NO
43 Observed 10:34:00 10:34:00 NO NO NO
44 Observed 10:39:00 10:39:00 NO NO End
注意：当同一行中有“开始”和“结束”时，因为非丢失时段仅包含该记录。
我能够识别开始或结束这些“非丢失”时段的记录（在“Starter”和“Ender”列下），但现在我希望能够通过为它们提供唯一标识符来识别这些时段（期间A，B，C或1,2,3等）。 理想情况下，标识符的名称将是该期间的起点名称（即ID [Starter ==“Start”]）
我正在寻找类似的东西：
ID Type TimeStart TimeEnd Limiter Starter Ender Period
1 Observed 6:45:00 6:45:00 NO Start End 1
2 Lost 6:45:00 5:31:00 YES NO NO Lost
3 Observed 5:31:00 5:31:00 NO Start NO 3
4 Observed 9:48:00 9:48:00 NO NO NO 3
5 Observed 10:02:00 10:02:00 NO NO NO 3
6 Observed 10:18:00 10:18:00 NO NO NO 3
7 Observed 11:00:00 11:00:00 NO NO NO 3
8 Observed 13:15:00 13:15:00 NO NO NO 3
9 Observed 13:34:00 13:34:00 NO NO NO 3
10 Observed 13:43:00 13:43:00 NO NO NO 3
11 Observed 13:52:00 13:52:00 NO NO NO 3
12 Observed 14:25:00 14:25:00 NO NO NO 3
13 Observed 14:46:00 14:46:00 NO NO End 3
14 Lost 14:46:00 10:47:00 YES NO NO Lost
15 Observed 10:47:00 10:47:00 NO Start NO 15
16 Observed 10:57:00 11:00:00 NO NO NO 15
17 Observed 11:10:00 11:10:00 NO NO NO 15
18 Observed 11:19:00 11:27:55 NO NO NO 15
19 Observed 11:28:05 11:32:00 NO NO NO 15
20 Observed 11:45:00 12:09:00 NO NO NO 15
21 Observed 11:51:00 11:51:00 NO NO NO 15
22 Observed 12:11:00 12:11:00 NO NO NO 15
23 Observed 13:15:00 13:15:00 NO NO End 15
24 Lost 13:15:00 7:53:00 YES NO NO Lost
这在R中难以做到吗？
谢谢！
答案 0 :(得分：0)
> d <- data.frame(Limiter = rep("NO", 44), Starter = rep("NO", 44), Ender = rep("NO", 44), stringsAsFactors = FALSE)
> d$Starter[c(1, 3, 15, 25)] <- "Start"
> d$Ender[c(1, 13, 23, 44)] <- "End"
> d$Limiter[c(2, 14, 24)] <- "Yes"
> d$Period <- ifelse(d$Limiter == "Yes", "Lost", which(d$Starter == "Start")[cumsum(d$Starter == "Start")])
> d
Limiter Starter Ender Period
1 NO Start End 1
2 Yes NO NO Lost
3 NO Start NO 3
4 NO NO NO 3
5 NO NO NO 3
6 NO NO NO 3
7 NO NO NO 3
8 NO NO NO 3
9 NO NO NO 3
10 NO NO NO 3
11 NO NO NO 3
12 NO NO NO 3
13 NO NO End 3
14 Yes NO NO Lost
15 NO Start NO 15
16 NO NO NO 15
17 NO NO NO 15
18 NO NO NO 15
19 NO NO NO 15
20 NO NO NO 15
21 NO NO NO 15
22 NO NO NO 15
23 NO NO End 15
24 Yes NO NO Lost
25 NO Start NO 25
26 NO NO NO 25
27 NO NO NO 25
28 NO NO NO 25
29 NO NO NO 25
30 NO NO NO 25
31 NO NO NO 25
32 NO NO NO 25
33 NO NO NO 25
34 NO NO NO 25
35 NO NO NO 25
36 NO NO NO 25
37 NO NO NO 25
38 NO NO NO 25
39 NO NO NO 25
40 NO NO NO 25
41 NO NO NO 25
42 NO NO NO 25
43 NO NO NO 25
44 NO NO End 25