将日期时间间隔分配给日期时间事件
Assigning an DateTime interval to a DateTime Event
我有一个 table >1M 的个人日期时间检测间隔（即在此期间连续检测到一个人）和一个 table 日期时间间隔，表示门何时关闭。个别检测被分类为 "IN" 或 "OUT"
使用 %within% 我已经能够确定检测是否落在任何间隔内。
但是，我想做一些不同的事情。对于每个门关闭间隔，我想知道在外面检测到多少人，在里面检测到多少人。我相信最简单的方法是将每个检测事件分配给一个门控周期，但我无法弄清楚如果没有极其混乱的嵌套 ifelse 语句，该函数将如何编写。
预期输出（非真实数据）：
Tag site species StartDateTime_UTC EndDateTime_UTC interval Location
<fct> <fct> <chr> <dttm> <dttm> <dbl> <chr>
1 5004.24 IC1 Striped Bass 2014-09-29 22:40:40 2014-09-29 22:46:35 1 IN
2 5004.24 IC1 Striped Bass 2014-09-29 22:49:15 2014-09-29 22:50:05 1 IN
3 5004.24 RGD1 Striped Bass 2014-10-01 23:01:12 2014-10-01 23:11:23 2 IN
4 5004.24 RGD1 Striped Bass 2014-10-01 23:16:18 2014-10-02 00:13:17 2 IN
5 5004.24 RGD1 Striped Bass 2014-10-02 00:15:47 2014-10-02 00:30:08 2 IN
6 5004.24 RGD1 Striped Bass 2014-10-02 00:33:12 2014-10-02 01:10:21 2 IN
7 5004.24 RGD1 Striped Bass 2014-10-02 01:13:01 2014-10-02 01:20:12 2 IN
8 5004.24 RGD1 Striped Bass 2014-10-02 04:14:15 2014-10-02 04:21:11 2 IN
9 5004.24 RGD1 Striped Bass 2014-10-02 04:23:31 2014-10-02 04:26:06 NA IN
10 5004.24 RGD1 Striped Bass 2014-10-02 04:28:21 2014-10-02 04:32:16 NA IN
11 5004.24 RGD1 Striped Bass 2014-10-02 22:00:06 2014-10-02 22:44:08 NA IN
12 5004.24 RGD1 Striped Bass 2014-10-02 22:46:58 2014-10-02 23:08:21 5 IN
13 5004.24 RGD1 Striped Bass 2014-10-02 23:10:36 2014-10-03 00:26:00 5 IN
14 5004.24 RGD1 Striped Bass 2014-10-03 00:28:55 2014-10-03 00:51:35 5 IN
15 5004.24 RGD1 Striped Bass 2014-10-03 00:55:06 2014-10-03 01:08:01 5 IN
16 5004.24 RGD1 Striped Bass 2014-10-03 01:10:36 2014-10-03 01:17:21 6 IN
17 5004.24 RGD1 Striped Bass 2014-10-03 01:20:41 2014-10-03 01:21:01 6 IN
18 5004.24 RGD1 Striped Bass 2014-10-03 01:30:41 2014-10-03 01:31:07 6 IN
19 5004.24 RGD1 Striped Bass 2014-10-03 01:35:02 2014-10-03 01:38:12 7 IN
20 5004.24 RGD1 Striped Bass 2014-10-03 01:42:02 2014-10-03 01:58:18 7 IN
当门关闭时，某些检测可能不会发生，因此"NA"有效
有没有更好的选择？
输出：
检测：
structure(list(Tag = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("5004.24",
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"9386.16", "9393.26", "9400.24", "9407.03", "9407.07", "9428.24",
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"9904.24", "9911.07", "9917.06", "9939.03", "9939.07", "9967.07",
"9973.06", "9988.24", "9995.01"), class = "factor"), Start.Time = c("9/29/2014 10:40:40 PM",
"9/29/2014 10:49:15 PM", "10/1/2014 11:01:12 PM", "10/1/2014 11:16:18 PM",
"10/2/2014 12:15:47 AM", "10/2/2014 12:33:12 AM", "10/2/2014 1:13:01 AM",
"10/2/2014 4:14:15 AM", "10/2/2014 4:23:31 AM", "10/2/2014 4:28:21 AM",
"10/2/2014 10:00:06 PM", "10/2/2014 10:46:58 PM", "10/2/2014 11:10:36 PM",
"10/3/2014 12:28:55 AM", "10/3/2014 12:55:06 AM", "10/3/2014 1:10:36 AM",
"10/3/2014 1:20:41 AM", "10/3/2014 1:30:41 AM", "10/3/2014 1:35:02 AM",
"10/3/2014 1:42:02 AM", "10/3/2014 2:05:05 AM", "10/3/2014 2:12:30 AM",
"10/3/2014 2:17:05 AM", "10/3/2014 2:21:36 AM", "10/3/2014 2:28:01 AM",
"10/3/2014 2:34:52 AM", "10/3/2014 4:01:03 AM", "10/3/2014 4:05:58 AM",
"10/3/2014 4:18:34 AM", "10/3/2014 4:28:29 AM", "10/3/2014 4:31:50 AM",
"10/3/2014 4:35:55 AM", "10/3/2014 6:00:15 AM", "10/3/2014 6:29:57 AM",
"10/3/2014 6:33:37 AM", "10/3/2014 6:46:58 AM", "10/3/2014 7:02:00 AM",
"10/3/2014 7:11:36 AM", "10/3/2014 7:18:32 AM", "10/3/2014 7:36:38 AM",
"10/3/2014 8:04:27 AM", "10/3/2014 9:30:15 AM", "10/3/2014 10:16:38 AM",
"10/3/2014 11:28:14 AM", "10/3/2014 12:13:46 PM", "10/3/2014 1:08:55 PM",
"10/3/2014 1:12:10 PM", "10/3/2014 2:28:59 PM", "10/3/2014 2:51:51 PM",
"10/3/2014 3:13:46 PM", "10/3/2014 3:43:47 PM", "10/3/2014 4:05:47 PM",
"10/3/2014 5:12:46 PM", "10/3/2014 6:02:10 PM", "10/3/2014 6:25:01 PM",
"10/3/2014 11:19:32 PM", "10/4/2014 9:16:18 AM", "10/4/2014 11:07:55 AM",
"10/4/2014 11:59:58 AM", "10/4/2014 12:42:29 PM", "10/4/2014 2:00:54 PM",
"10/4/2014 2:05:44 PM", "10/4/2014 2:09:39 PM", "10/4/2014 2:31:20 PM",
"10/4/2014 5:20:04 PM", "10/4/2014 6:23:53 PM", "10/4/2014 6:31:39 PM",
"10/4/2014 6:35:19 PM", "10/4/2014 6:38:40 PM", "10/4/2014 7:04:09 PM",
"10/4/2014 7:16:35 PM", "10/5/2014 2:51:50 AM", "10/5/2014 3:08:26 AM",
"10/5/2014 3:15:06 AM", "10/5/2014 3:46:12 AM", "10/5/2014 3:52:58 AM",
"10/5/2014 4:00:58 AM", "10/5/2014 4:05:54 AM", "10/5/2014 4:27:50 AM",
"10/5/2014 5:03:22 AM", "10/5/2014 5:09:42 AM", "10/5/2014 5:24:23 AM",
"10/5/2014 5:35:29 AM", "10/5/2014 5:39:44 AM", "10/5/2014 6:00:40 AM",
"10/5/2014 6:10:31 AM", "10/5/2014 6:18:22 AM", "10/5/2014 6:26:11 AM",
"10/5/2014 6:33:52 AM", "10/5/2014 6:54:43 AM", "10/5/2014 7:11:13 AM",
"10/5/2014 7:15:43 AM", "10/5/2014 8:08:37 AM", "10/5/2014 9:10:24 AM",
"10/5/2014 9:13:14 AM", "10/5/2014 9:27:19 AM", "10/5/2014 9:40:26 AM",
"10/5/2014 10:17:48 AM", "10/5/2014 10:51:59 AM", "10/5/2014 10:55:04 AM"
), total.duration = c(355L, 50L, 611L, 3419L, 861L, 2229L, 431L,
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201L, 41L, 80L, 461L, 752L, 45L, 670L, 85L, 426L, 286L, 935L,
1256L, 4882L, 2644L, 4111L, 2212L, 256L, 50L, 720L, 1192L, 1085L,
1515L, 931L, 3759L, 1851L, 1201L, 840L, 2397L, 6528L, 2993L,
2421L, 3597L, 35L, 35L, 6L, 1327L, 246L, 221L, 65L, 25L, 830L,
596L, 831L, 310L, 245L, 1696L, 100L, 336L, 85L, 1181L, 1847L,
170L, 586L, 355L, 45L, 866L, 371L, 310L, 294L, 271L, 245L, 190L,
26L, 3004L, 3517L, 35L, 706L, 641L, 2112L, 1892L, 6L, 71L), site = structure(c(4L,
4L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L), .Label = c("CLRS", "CVP1",
"GL1", "IC1", "IC2", "IC3", "ORN1", "ORN2", "ORS1", "ORS3", "RGD1",
"RGU1", "WC1", "WC2", "WC3"), class = "factor"), number.Of.Pings = c(15L,
4L, 25L, 513L, 163L, 368L, 27L, 16L, 10L, 14L, 214L, 167L, 566L,
175L, 146L, 13L, 5L, 7L, 13L, 82L, 17L, 10L, 7L, 8L, 3L, 15L,
10L, 32L, 10L, 4L, 8L, 47L, 44L, 8L, 75L, 10L, 20L, 31L, 47L,
266L, 623L, 398L, 480L, 305L, 19L, 10L, 23L, 71L, 90L, 110L,
108L, 797L, 167L, 105L, 118L, 211L, 773L, 368L, 455L, 729L, 8L,
11L, 3L, 59L, 20L, 8L, 2L, 5L, 33L, 24L, 68L, 20L, 14L, 118L,
2L, 19L, 12L, 85L, 117L, 8L, 33L, 13L, 9L, 85L, 42L, 19L, 11L,
20L, 25L, 10L, 4L, 500L, 703L, 2L, 124L, 101L, 449L, 401L, 4L,
9L), species = c("Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass", "Striped Bass", "Striped Bass", "Striped Bass",
"Striped Bass"), StartDateTime_UTC = structure(c(1412030440,
1412030955, 1412204472, 1412205378, 1412208947, 1412209992, 1412212381,
1412223255, 1412223811, 1412224101, 1412287206, 1412290018, 1412291436,
1412296135, 1412297706, 1412298636, 1412299241, 1412299841, 1412300102,
1412300522, 1412301905, 1412302350, 1412302625, 1412302896, 1412303281,
1412303692, 1412308863, 1412309158, 1412309914, 1412310509, 1412310710,
1412310955, 1412316015, 1412317797, 1412318017, 1412318818, 1412319720,
1412320296, 1412320712, 1412321798, 1412323467, 1412328615, 1412331398,
1412335694, 1412338426, 1412341735, 1412341930, 1412346539, 1412347911,
1412349226, 1412351027, 1412352347, 1412356366, 1412359330, 1412360701,
1412378372, 1412414178, 1412420875, 1412423998, 1412426549, 1412431254,
1412431544, 1412431779, 1412433080, 1412443204, 1412447033, 1412447499,
1412447719, 1412447920, 1412449449, 1412450195, 1412477510, 1412478506,
1412478906, 1412480772, 1412481178, 1412481658, 1412481954, 1412483270,
1412485402, 1412485782, 1412486663, 1412487329, 1412487584, 1412488840,
1412489431, 1412489902, 1412490371, 1412490832, 1412492083, 1412493073,
1412493343, 1412496517, 1412500224, 1412500394, 1412501239, 1412502026,
1412504268, 1412506319, 1412506504), class = c("POSIXct", "POSIXt"
), tzone = "UTC"), Duration_sec = new("Period", .Data = c(355,
50, 611, 3419, 861, 2229, 431, 416, 155, 235, 2642, 1283, 4524,
1360, 775, 405, 20, 26, 190, 976, 166, 136, 60, 145, 41, 80,
146, 380, 201, 41, 80, 461, 752, 45, 670, 85, 426, 286, 935,
1256, 4882, 2644, 4111, 2212, 256, 50, 720, 1192, 1085, 1515,
931, 3759, 1851, 1201, 840, 2397, 6528, 2993, 2421, 3597, 35,
35, 6, 1327, 246, 221, 65, 25, 830, 596, 831, 310, 245, 1696,
100, 336, 85, 1181, 1847, 170, 586, 355, 45, 866, 371, 310, 294,
271, 245, 190, 26, 3004, 3517, 35, 706, 641, 2112, 1892, 6, 71
), year = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
month = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0), day = c(0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), hour = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0), minute = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)), EndDateTime_UTC = structure(c(1412030795,
1412031005, 1412205083, 1412208797, 1412209808, 1412212221, 1412212812,
1412223671, 1412223966, 1412224336, 1412289848, 1412291301, 1412295960,
1412297495, 1412298481, 1412299041, 1412299261, 1412299867, 1412300292,
1412301498, 1412302071, 1412302486, 1412302685, 1412303041, 1412303322,
1412303772, 1412309009, 1412309538, 1412310115, 1412310550, 1412310790,
1412311416, 1412316767, 1412317842, 1412318687, 1412318903, 1412320146,
1412320582, 1412321647, 1412323054, 1412328349, 1412331259, 1412335509,
1412337906, 1412338682, 1412341785, 1412342650, 1412347731, 1412348996,
1412350741, 1412351958, 1412356106, 1412358217, 1412360531, 1412361541,
1412380769, 1412420706, 1412423868, 1412426419, 1412430146, 1412431289,
1412431579, 1412431785, 1412434407, 1412443450, 1412447254, 1412447564,
1412447744, 1412448750, 1412450045, 1412451026, 1412477820, 1412478751,
1412480602, 1412480872, 1412481514, 1412481743, 1412483135, 1412485117,
1412485572, 1412486368, 1412487018, 1412487374, 1412488450, 1412489211,
1412489741, 1412490196, 1412490642, 1412491077, 1412492273, 1412493099,
1412496347, 1412500034, 1412500259, 1412501100, 1412501880, 1412504138,
1412506160, 1412506325, 1412506575), class = c("POSIXct", "POSIXt"
), tzone = "UTC"), StartOpen = c(FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE), EndOpen = c(FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE
), location = c("IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN")), row.names = c(NA, -100L), class = c("tbl_df",
"tbl", "data.frame"))
门关闭间隔
new("Interval", .Data = c(-81060, -117060, -59400, -16200, -76680,
-51000, -81120), start = structure(c(1412238660, 1412362800,
1412434800, 1412454600, 1412542980, 1412602200, 1412690400), class = c("POSIXct",
"POSIXt"), tzone = "UTC"), tzone = "UTC")
因此，您的示例数据存在一些问题，导致难以回答您的问题。
- 您的示例检测数据包含许多不需要解决或理解您的问题的额外信息。
- 您的示例间隔是倒退的。 （他们在开始之前就结束了）
- 您的示例数据未以易于使用的格式设置（您未包含读取它所需的包）。
也就是说，让我们简化并纠正这些问题：
library(tidyverse) # needed because your data is in tibble format
library(lubridate) # needed for time interval class used in your example
# I called your example data "Detections" and "Intervals", not importing them here
set.seed(914)
row.sample <- c(1,5,2, sample(1:100, 10)) # to include the samples not in the given intervals mixed with good values
use.cols <- c(1,4,6,7,9)
Detections.use <- Detections[row.sample, use.cols]
Detections.use
# A tibble: 13 x 5
Tag site species StartDateTime_UTC EndDateTime_UTC
<fct> <fct> <chr> <dttm> <dttm>
1 5004.24 IC1 Striped Bass 2014-09-29 22:40:40 2014-09-29 22:46:35
2 5004.24 RGD1 Striped Bass 2014-10-02 00:15:47 2014-10-02 00:30:08
3 5004.24 IC1 Striped Bass 2014-09-29 22:49:15 2014-09-29 22:50:05
4 5004.24 RGD1 Striped Bass 2014-10-04 18:38:40 2014-10-04 18:52:30
5 5004.24 RGD1 Striped Bass 2014-10-05 07:15:43 2014-10-05 08:05:47
6 5004.24 RGD1 Striped Bass 2014-10-03 02:21:36 2014-10-03 02:24:01
7 5004.24 RGD1 Striped Bass 2014-10-03 12:13:46 2014-10-03 12:18:02
8 5004.24 RGD1 Striped Bass 2014-10-03 09:30:15 2014-10-03 10:14:19
9 5004.24 RGD1 Striped Bass 2014-10-04 14:09:39 2014-10-04 14:09:45
10 5004.24 RGD1 Striped Bass 2014-10-03 02:17:05 2014-10-03 02:18:05
11 5004.24 RGD1 Striped Bass 2014-10-05 03:08:26 2014-10-05 03:12:31
12 5004.24 RGD1 Striped Bass 2014-10-03 01:42:02 2014-10-03 01:58:18
13 5004.24 RGD1 Striped Bass 2014-10-02 00:33:12 2014-10-02 01:10:21
# Convert your intervals to a table, then correct them to make them positive time intevals
Interval.table <- tibble(Intervals, "ID" = seq(from = 1, to = length(Intervals))) %>%
mutate(end_time = Intervals$start,
start_time = end_time+Intervals$.Data,
new_Interval = start_time %--% end_time) %>%
select(ID, new_Interval)
Interval.table
# A tibble: 7 x 2
ID new_Interval
<int> <Interval>
1 1 2014-10-01 10:00:00 UTC--2014-10-02 08:31:00 UTC
2 2 2014-10-02 10:29:00 UTC--2014-10-03 19:00:00 UTC
3 3 2014-10-03 22:30:00 UTC--2014-10-04 15:00:00 UTC
4 4 2014-10-04 16:00:00 UTC--2014-10-04 20:30:00 UTC
5 5 2014-10-04 23:45:00 UTC--2014-10-05 21:03:00 UTC
6 6 2014-10-05 23:20:00 UTC--2014-10-06 13:30:00 UTC
7 7 2014-10-06 15:28:00 UTC--2014-10-07 14:00:00 UTC
现在回答你的问题
lubridate 包包含一个函数 %within%，用于测试时间是否在时间间隔内，但对于 tidyverse 函数来说奇怪的是，它似乎不能很好地向量化。我无法弄清楚如何使它在典型的 dplyr/tidyr 语法中工作，但是使用 for 循环，我们可以创建一个向量，其中包含每次适合的间隔的 ID 和 NA 的间隔不在任何给定的内部。
y <- c()
for (i in 1:length(Detections.use$StartDateTime_UTC)){
z<- which(Detections.use$StartDateTime_UTC[i] %within% Interval.table$new_Interval)
y[i] <- ifelse(isTRUE(z>0), z, NA)
}
Detections.use$Interval <- y
Detections.use
# A tibble: 13 x 6
Tag site species StartDateTime_UTC EndDateTime_UTC Interval
<fct> <fct> <chr> <dttm> <dttm> <int>
1 5004.24 IC1 Striped Bass 2014-09-29 22:40:40 2014-09-29 22:46:35 NA
2 5004.24 RGD1 Striped Bass 2014-10-02 00:15:47 2014-10-02 00:30:08 1
3 5004.24 IC1 Striped Bass 2014-09-29 22:49:15 2014-09-29 22:50:05 NA
4 5004.24 RGD1 Striped Bass 2014-10-04 18:38:40 2014-10-04 18:52:30 4
5 5004.24 RGD1 Striped Bass 2014-10-05 07:15:43 2014-10-05 08:05:47 5
6 5004.24 RGD1 Striped Bass 2014-10-03 02:21:36 2014-10-03 02:24:01 2
7 5004.24 RGD1 Striped Bass 2014-10-03 12:13:46 2014-10-03 12:18:02 2
8 5004.24 RGD1 Striped Bass 2014-10-03 09:30:15 2014-10-03 10:14:19 2
9 5004.24 RGD1 Striped Bass 2014-10-04 14:09:39 2014-10-04 14:09:45 3
10 5004.24 RGD1 Striped Bass 2014-10-03 02:17:05 2014-10-03 02:18:05 2
11 5004.24 RGD1 Striped Bass 2014-10-05 03:08:26 2014-10-05 03:12:31 5
12 5004.24 RGD1 Striped Bass 2014-10-03 01:42:02 2014-10-03 01:58:18 2
13 5004.24 RGD1 Striped Bass 2014-10-02 00:33:12 2014-10-02 01:10:21 1
编辑添加sapply解决方案---
这也可以 sapply 更平滑一些，并且不会留下工件：
which.join <- function(x, y) {
z <- which(x %within% y)
z <- ifelse(isTRUE(z > 0), z, NA)
z
}
Detections.use$Interval <- sapply(Detections.use$StartDateTime_UTC,
function(x) which.join(x,Interval.table$new_Interval)
另一种方法可能是使用 fuzzyjoin 包，如图所示 here
我有一个 table >1M 的个人日期时间检测间隔（即在此期间连续检测到一个人）和一个 table 日期时间间隔，表示门何时关闭。个别检测被分类为 "IN" 或 "OUT"
使用 %within% 我已经能够确定检测是否落在任何间隔内。
但是，我想做一些不同的事情。对于每个门关闭间隔，我想知道在外面检测到多少人，在里面检测到多少人。我相信最简单的方法是将每个检测事件分配给一个门控周期，但我无法弄清楚如果没有极其混乱的嵌套 ifelse 语句，该函数将如何编写。
预期输出（非真实数据）：
Tag site species StartDateTime_UTC EndDateTime_UTC interval Location
<fct> <fct> <chr> <dttm> <dttm> <dbl> <chr>
1 5004.24 IC1 Striped Bass 2014-09-29 22:40:40 2014-09-29 22:46:35 1 IN
2 5004.24 IC1 Striped Bass 2014-09-29 22:49:15 2014-09-29 22:50:05 1 IN
3 5004.24 RGD1 Striped Bass 2014-10-01 23:01:12 2014-10-01 23:11:23 2 IN
4 5004.24 RGD1 Striped Bass 2014-10-01 23:16:18 2014-10-02 00:13:17 2 IN
5 5004.24 RGD1 Striped Bass 2014-10-02 00:15:47 2014-10-02 00:30:08 2 IN
6 5004.24 RGD1 Striped Bass 2014-10-02 00:33:12 2014-10-02 01:10:21 2 IN
7 5004.24 RGD1 Striped Bass 2014-10-02 01:13:01 2014-10-02 01:20:12 2 IN
8 5004.24 RGD1 Striped Bass 2014-10-02 04:14:15 2014-10-02 04:21:11 2 IN
9 5004.24 RGD1 Striped Bass 2014-10-02 04:23:31 2014-10-02 04:26:06 NA IN
10 5004.24 RGD1 Striped Bass 2014-10-02 04:28:21 2014-10-02 04:32:16 NA IN
11 5004.24 RGD1 Striped Bass 2014-10-02 22:00:06 2014-10-02 22:44:08 NA IN
12 5004.24 RGD1 Striped Bass 2014-10-02 22:46:58 2014-10-02 23:08:21 5 IN
13 5004.24 RGD1 Striped Bass 2014-10-02 23:10:36 2014-10-03 00:26:00 5 IN
14 5004.24 RGD1 Striped Bass 2014-10-03 00:28:55 2014-10-03 00:51:35 5 IN
15 5004.24 RGD1 Striped Bass 2014-10-03 00:55:06 2014-10-03 01:08:01 5 IN
16 5004.24 RGD1 Striped Bass 2014-10-03 01:10:36 2014-10-03 01:17:21 6 IN
17 5004.24 RGD1 Striped Bass 2014-10-03 01:20:41 2014-10-03 01:21:01 6 IN
18 5004.24 RGD1 Striped Bass 2014-10-03 01:30:41 2014-10-03 01:31:07 6 IN
19 5004.24 RGD1 Striped Bass 2014-10-03 01:35:02 2014-10-03 01:38:12 7 IN
20 5004.24 RGD1 Striped Bass 2014-10-03 01:42:02 2014-10-03 01:58:18 7 IN
当门关闭时，某些检测可能不会发生，因此"NA"有效
有没有更好的选择？
输出：
检测：
structure(list(Tag = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("5004.24",
"5010.04", "5011.03", "5011.07", "5017.06", "5025.22", "5025.26",
"5032.24", "5038.04", "5039.03", "5039.07", "5045", "5053.26",
"5067.07", "5073.06", "5074.16", "5088.11", "5094.04", "5101.06",
"5116.24", "5123.03", "5123.07", "5150.04", "5157.06", "5165.22",
"5172.24", "5179.03", "5179.07", "5186.16", "5200.11", "5206.31",
"5214.16", "5228.24", "5235", "5242.16", "5249", "5256.24", "5263.07",
"5270.16", "5284.11", "5290.31", "5298.16", "5312.11", "5318.04",
"5326.16", "5340.11", "5347.07", "5361.26", "5368.24", "5374.04",
"5375.03", "5375.07", "5381.06", "5402.31", "5403.07", "5431.07",
"5438.16", "5445.26", "5465.06", "5480.24", "5487.03", "5487.07",
"5493.06", "5501.22", "5514.31", "5536.11", "5542.31", "5550.16",
"5557.22", "5564.24", "5570.04", "5571.03", "5571.07", "5577",
"5585.26", "5592.11", "5599.15", "5605.06", "5620.11", "5626.31",
"5627.15", "5641.22", "5641.26", "5648.11", "5654.31", "5662.16",
"5676.24", "5682.04", "5683.03", "5683.07", "5690.16", "5697.22",
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0), day = c(0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), hour = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0), minute = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)), EndDateTime_UTC = structure(c(1412030795,
1412031005, 1412205083, 1412208797, 1412209808, 1412212221, 1412212812,
1412223671, 1412223966, 1412224336, 1412289848, 1412291301, 1412295960,
1412297495, 1412298481, 1412299041, 1412299261, 1412299867, 1412300292,
1412301498, 1412302071, 1412302486, 1412302685, 1412303041, 1412303322,
1412303772, 1412309009, 1412309538, 1412310115, 1412310550, 1412310790,
1412311416, 1412316767, 1412317842, 1412318687, 1412318903, 1412320146,
1412320582, 1412321647, 1412323054, 1412328349, 1412331259, 1412335509,
1412337906, 1412338682, 1412341785, 1412342650, 1412347731, 1412348996,
1412350741, 1412351958, 1412356106, 1412358217, 1412360531, 1412361541,
1412380769, 1412420706, 1412423868, 1412426419, 1412430146, 1412431289,
1412431579, 1412431785, 1412434407, 1412443450, 1412447254, 1412447564,
1412447744, 1412448750, 1412450045, 1412451026, 1412477820, 1412478751,
1412480602, 1412480872, 1412481514, 1412481743, 1412483135, 1412485117,
1412485572, 1412486368, 1412487018, 1412487374, 1412488450, 1412489211,
1412489741, 1412490196, 1412490642, 1412491077, 1412492273, 1412493099,
1412496347, 1412500034, 1412500259, 1412501100, 1412501880, 1412504138,
1412506160, 1412506325, 1412506575), class = c("POSIXct", "POSIXt"
), tzone = "UTC"), StartOpen = c(FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE), EndOpen = c(FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE
), location = c("IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN", "IN",
"IN", "IN", "IN", "IN")), row.names = c(NA, -100L), class = c("tbl_df",
"tbl", "data.frame"))
门关闭间隔
new("Interval", .Data = c(-81060, -117060, -59400, -16200, -76680,
-51000, -81120), start = structure(c(1412238660, 1412362800,
1412434800, 1412454600, 1412542980, 1412602200, 1412690400), class = c("POSIXct",
"POSIXt"), tzone = "UTC"), tzone = "UTC")
因此，您的示例数据存在一些问题，导致难以回答您的问题。
- 您的示例检测数据包含许多不需要解决或理解您的问题的额外信息。
- 您的示例间隔是倒退的。 （他们在开始之前就结束了）
- 您的示例数据未以易于使用的格式设置（您未包含读取它所需的包）。
也就是说，让我们简化并纠正这些问题：
library(tidyverse) # needed because your data is in tibble format
library(lubridate) # needed for time interval class used in your example
# I called your example data "Detections" and "Intervals", not importing them here
set.seed(914)
row.sample <- c(1,5,2, sample(1:100, 10)) # to include the samples not in the given intervals mixed with good values
use.cols <- c(1,4,6,7,9)
Detections.use <- Detections[row.sample, use.cols]
Detections.use
# A tibble: 13 x 5
Tag site species StartDateTime_UTC EndDateTime_UTC
<fct> <fct> <chr> <dttm> <dttm>
1 5004.24 IC1 Striped Bass 2014-09-29 22:40:40 2014-09-29 22:46:35
2 5004.24 RGD1 Striped Bass 2014-10-02 00:15:47 2014-10-02 00:30:08
3 5004.24 IC1 Striped Bass 2014-09-29 22:49:15 2014-09-29 22:50:05
4 5004.24 RGD1 Striped Bass 2014-10-04 18:38:40 2014-10-04 18:52:30
5 5004.24 RGD1 Striped Bass 2014-10-05 07:15:43 2014-10-05 08:05:47
6 5004.24 RGD1 Striped Bass 2014-10-03 02:21:36 2014-10-03 02:24:01
7 5004.24 RGD1 Striped Bass 2014-10-03 12:13:46 2014-10-03 12:18:02
8 5004.24 RGD1 Striped Bass 2014-10-03 09:30:15 2014-10-03 10:14:19
9 5004.24 RGD1 Striped Bass 2014-10-04 14:09:39 2014-10-04 14:09:45
10 5004.24 RGD1 Striped Bass 2014-10-03 02:17:05 2014-10-03 02:18:05
11 5004.24 RGD1 Striped Bass 2014-10-05 03:08:26 2014-10-05 03:12:31
12 5004.24 RGD1 Striped Bass 2014-10-03 01:42:02 2014-10-03 01:58:18
13 5004.24 RGD1 Striped Bass 2014-10-02 00:33:12 2014-10-02 01:10:21
# Convert your intervals to a table, then correct them to make them positive time intevals
Interval.table <- tibble(Intervals, "ID" = seq(from = 1, to = length(Intervals))) %>%
mutate(end_time = Intervals$start,
start_time = end_time+Intervals$.Data,
new_Interval = start_time %--% end_time) %>%
select(ID, new_Interval)
Interval.table
# A tibble: 7 x 2
ID new_Interval
<int> <Interval>
1 1 2014-10-01 10:00:00 UTC--2014-10-02 08:31:00 UTC
2 2 2014-10-02 10:29:00 UTC--2014-10-03 19:00:00 UTC
3 3 2014-10-03 22:30:00 UTC--2014-10-04 15:00:00 UTC
4 4 2014-10-04 16:00:00 UTC--2014-10-04 20:30:00 UTC
5 5 2014-10-04 23:45:00 UTC--2014-10-05 21:03:00 UTC
6 6 2014-10-05 23:20:00 UTC--2014-10-06 13:30:00 UTC
7 7 2014-10-06 15:28:00 UTC--2014-10-07 14:00:00 UTC
现在回答你的问题
lubridate 包包含一个函数 %within%，用于测试时间是否在时间间隔内，但对于 tidyverse 函数来说奇怪的是，它似乎不能很好地向量化。我无法弄清楚如何使它在典型的 dplyr/tidyr 语法中工作，但是使用 for 循环，我们可以创建一个向量，其中包含每次适合的间隔的 ID 和 NA 的间隔不在任何给定的内部。
y <- c()
for (i in 1:length(Detections.use$StartDateTime_UTC)){
z<- which(Detections.use$StartDateTime_UTC[i] %within% Interval.table$new_Interval)
y[i] <- ifelse(isTRUE(z>0), z, NA)
}
Detections.use$Interval <- y
Detections.use
# A tibble: 13 x 6
Tag site species StartDateTime_UTC EndDateTime_UTC Interval
<fct> <fct> <chr> <dttm> <dttm> <int>
1 5004.24 IC1 Striped Bass 2014-09-29 22:40:40 2014-09-29 22:46:35 NA
2 5004.24 RGD1 Striped Bass 2014-10-02 00:15:47 2014-10-02 00:30:08 1
3 5004.24 IC1 Striped Bass 2014-09-29 22:49:15 2014-09-29 22:50:05 NA
4 5004.24 RGD1 Striped Bass 2014-10-04 18:38:40 2014-10-04 18:52:30 4
5 5004.24 RGD1 Striped Bass 2014-10-05 07:15:43 2014-10-05 08:05:47 5
6 5004.24 RGD1 Striped Bass 2014-10-03 02:21:36 2014-10-03 02:24:01 2
7 5004.24 RGD1 Striped Bass 2014-10-03 12:13:46 2014-10-03 12:18:02 2
8 5004.24 RGD1 Striped Bass 2014-10-03 09:30:15 2014-10-03 10:14:19 2
9 5004.24 RGD1 Striped Bass 2014-10-04 14:09:39 2014-10-04 14:09:45 3
10 5004.24 RGD1 Striped Bass 2014-10-03 02:17:05 2014-10-03 02:18:05 2
11 5004.24 RGD1 Striped Bass 2014-10-05 03:08:26 2014-10-05 03:12:31 5
12 5004.24 RGD1 Striped Bass 2014-10-03 01:42:02 2014-10-03 01:58:18 2
13 5004.24 RGD1 Striped Bass 2014-10-02 00:33:12 2014-10-02 01:10:21 1
编辑添加sapply解决方案---
这也可以 sapply 更平滑一些，并且不会留下工件：
which.join <- function(x, y) {
z <- which(x %within% y)
z <- ifelse(isTRUE(z > 0), z, NA)
z
}
Detections.use$Interval <- sapply(Detections.use$StartDateTime_UTC,
function(x) which.join(x,Interval.table$new_Interval)
另一种方法可能是使用 fuzzyjoin 包，如图所示 here