r - R - 根据条件启动和重置 R 中的计数列
问题描述
我要提前感谢所有帮助，因为到目前为止的帮助使我能够获得关于如何分析我的数据的新想法/假设。
数据
structure(list(record_id = c(110101, 110101, 110101, 110101,
110101, 110101, 110101, 110101, 110101, 110101, 110101, 110101,
110101, 110101, 110101, 110101, 110101, 110101, 110101, 110101,
110101, 110101, 110101, 110101, 110101, 110101, 110101, 110101,
110101, 110101, 110101, 110101, 110101, 110101, 110101, 110101,
110101, 110101, 110101, 110101, 110101, 110101, 110101, 110101,
110101, 110101, 110101, 110101, 110101, 110101, 110101, 110101,
110101, 110101, 110101, 110101, 110101, 110101, 110101, 110101
), start = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30,
31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46,
47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59), stop = c(1,
2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,
52, 53, 54, 55, 56, 57, 58, 59, 60), `treatment (type)` = c(1,
1, 1, 0, 0, 0, 0, 2, 2, 2, 0, 0, 0, 0, 0, 0, 3, 3, 0, 3, 3, 3,
0, 2, 2, 2, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), vulnerable_period_30count = c(0,
0, 0, 1, 1, 1, 1, 2, 3, 4, 1, 1, 1, 1, 1, 1, 2, 3, 1, 2, 3, 4,
1, 2, 3, 4, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,
14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
30, 0, 0), vulnerable_period_yn = c(0, 0, 0, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 0, 0), vulnerable_period_30count_3days = c(0,
0, 0, 0, 0, 1, 1, 2, 3, 4, 5, 6, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7,
8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28,
29, 30, 0, 0), vulnerable_period_3days_yn = c(0, 0, 0, 0, 0,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 11, 1, 1, 1, 1, 1, 1, 1, 0, 0)), row.names = c(NA, -60L
), class = c("tbl_df", "tbl", "data.frame"))
解释
输入
start和stop是天数。每日治疗列于 中treatment，0 = 不治疗，为中断治疗，1:3 为治疗 A/B/C。
假设是，一旦一个人的治疗中断，他或她在接下来的 30 天内很容易受到伤害。
因此，基于这些输入，我想计算/计算以下输出：
输出
vulnerable_period_30count：发生治疗中断时（治疗（类型）=0），开始计数到30。发生治疗中断时自动复位。
vulnerable_period_30count_3days：仅当治疗中断持续三天（因此连续三个 0）或更长时间时，中断才相关。然后，它会开始计数到 30。如果中断持续时间超过三天，它将重新计数。注意：见第 6 天，中断总共持续 4 天。当 4 天的中断结束时，计数会重置。
当计数超过 30 时，它会恢复为 0，并且只有在再次发生相关中断时才会开始计数。
这里尝试为脆弱_周期_30 计数。
尝试脆弱_period_30count
data$vulnerable_period_30count <- data %>%
group_by(record_id, idx = cumsum(`treatment (type)` == 0L)) %>%
mutate(counter = row_number()) %>%
ungroup %>%
select(-idx)
data$test[data$test >30] <- 0
这里的问题是它已经从 1、2、3 开始了。我用最后一行硬停止计数。
对于如何仅在发生三个或更多中断时才开始计数，我完全不知道。
希望你能帮忙
体重
在答案 2 上评论 OP @Ekoam 再次感谢。代码现在运行很好。我设法找到了两个错误。我将用一个案例来说明：
structure(list(record_id = c(110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003), day_count = c(0, 1,
2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,
52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67,
68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,
84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99,
100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112,
113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125,
126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138,
139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151,
152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164,
165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177,
178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190,
191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203,
204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216,
217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229,
230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242,
243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255,
256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268,
269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281,
282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294,
295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307,
308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320,
321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333,
334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346,
347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359,
360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372,
373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385,
386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398,
399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411,
412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424,
425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437,
438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450,
451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463,
464, 465, 466, 467, 468, 469, 470, 471, 472), day_count_stop = c(1,
2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,
52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67,
68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,
84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99,
100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112,
113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125,
126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138,
139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151,
152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164,
165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177,
178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190,
191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203,
204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216,
217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229,
230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242,
243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255,
256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268,
269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281,
282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294,
295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307,
308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320,
321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333,
334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346,
347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359,
360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372,
373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385,
386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398,
399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411,
412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424,
425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437,
438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450,
451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463,
464, 465, 466, 467, 468, 469, 470, 471, 472, 473), oac_class = 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, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 0), vulnerable_period_30count = 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, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L,
24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L,
37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L,
50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L,
63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 74L, 75L,
76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 88L,
89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L,
101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 111L,
112L, 113L, 114L, 115L, 116L, 117L, 118L, 119L, 120L, 121L, 122L,
123L, 124L, 125L, 126L, 127L, 128L, 129L, 130L, 131L, 132L, 133L,
134L, 135L, 136L, 137L, 138L, 139L, 140L, 141L, 142L, 143L, 144L,
145L, 146L, 147L, 148L, 149L, 150L, 151L, 152L, 153L, 154L, 155L,
156L, 157L, 158L, 159L, 160L, 161L, 162L, 163L, 164L, 165L, 166L,
167L, 168L, 169L, 170L, 171L, 172L, 173L, 174L, 175L, 176L, 177L,
178L, 179L, 180L, 181L, 182L, 183L, 184L, 185L, 186L, 187L, 188L,
189L, 190L, 191L, 192L, 193L, 194L, 195L, 196L, 197L, 198L, 199L,
200L, 201L, 202L, 203L, 204L, 205L, 206L, 207L, 208L, 209L, 210L,
211L, 212L, 213L, 214L, 215L, 216L, 217L, 218L, 219L, 220L, 221L,
222L, 223L, 224L, 225L, 226L, 227L, 228L, 229L, 230L, 231L, 232L,
233L, 234L, 235L, 236L, 237L, 238L, 239L, 240L, 241L, 242L, 243L,
244L, 245L, 246L, 247L, 248L, 249L, 250L, 251L, 252L, 253L, 254L,
255L, 256L, 257L, 258L, 259L, 260L, 261L, 262L, 263L, 264L, 265L,
266L, 267L, 268L, 269L, 270L, 271L, 272L, 273L, 274L, 275L, 276L,
277L, 278L, 279L, 280L, 281L, 282L, 283L, 284L, 285L, 286L, 287L,
288L, 289L, 290L, 291L, 292L, 293L, 294L, 295L, 296L, 297L, 298L,
299L, 300L, 301L, 302L, 303L, 304L, 305L, 306L, 307L, 308L, 309L,
310L, 311L, 312L, 313L, 314L, 315L, 316L, 317L, 318L, 319L, 320L,
321L, 322L, 323L, 324L, 325L, 326L, 327L, 328L, 329L, 330L, 331L,
332L, 333L, 334L, 335L, 336L, 337L, 338L, 339L, 340L, 341L, 342L,
343L, 344L, 345L, 346L, 347L, 348L, 349L, 350L, 351L, 352L, 353L,
354L, 355L, 356L, 357L, 358L, 359L, 360L, 361L, 362L, 363L, 364L,
365L, 366L, 367L, 368L, 369L, 370L, 371L, 372L, 373L, 374L, 375L,
376L, 377L, 378L, 379L, 380L, 381L, 382L, 383L, 384L, 385L, 386L,
387L, 388L, 389L, 390L, 391L, 392L, 393L, 394L, 395L, 396L, 397L,
398L, 399L, 400L, 401L, 402L, 403L, 404L, 405L, 406L, 407L, 408L,
409L, 410L, 411L, 412L, 413L, 414L, 415L, 416L, 417L, 418L, 419L,
420L, 421L, 422L, 423L, 424L, 425L, 426L, 427L, 428L, 429L, 430L,
431L, 432L, 433L, 434L, 1L), vulnerable_period_30count_3days = 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, 2L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L,
25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L,
38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L,
51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L,
64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 74L, 75L, 76L,
77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L, 87L, 88L, 89L,
90L, 91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L, 101L,
102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 111L, 112L,
113L, 114L, 115L, 116L, 117L, 118L, 119L, 120L, 121L, 122L, 123L,
124L, 125L, 126L, 127L, 128L, 129L, 130L, 131L, 132L, 133L, 134L,
135L, 136L, 137L, 138L, 139L, 140L, 141L, 142L, 143L, 144L, 145L,
146L, 147L, 148L, 149L, 150L, 151L, 152L, 153L, 154L, 155L, 156L,
157L, 158L, 159L, 160L, 161L, 162L, 163L, 164L, 165L, 166L, 167L,
168L, 169L, 170L, 171L, 172L, 173L, 174L, 175L, 176L, 177L, 178L,
179L, 180L, 181L, 182L, 183L, 184L, 185L, 186L, 187L, 188L, 189L,
190L, 191L, 192L, 193L, 194L, 195L, 196L, 197L, 198L, 199L, 200L,
201L, 202L, 203L, 204L, 205L, 206L, 207L, 208L, 209L, 210L, 211L,
212L, 213L, 214L, 215L, 216L, 217L, 218L, 219L, 220L, 221L, 222L,
223L, 224L, 225L, 226L, 227L, 228L, 229L, 230L, 231L, 232L, 233L,
234L, 235L, 236L, 237L, 238L, 239L, 240L, 241L, 242L, 243L, 244L,
245L, 246L, 247L, 248L, 249L, 250L, 251L, 252L, 253L, 254L, 255L,
256L, 257L, 258L, 259L, 260L, 261L, 262L, 263L, 264L, 265L, 266L,
267L, 268L, 269L, 270L, 271L, 272L, 273L, 274L, 275L, 276L, 277L,
278L, 279L, 280L, 281L, 282L, 283L, 284L, 285L, 286L, 287L, 288L,
289L, 290L, 291L, 292L, 293L, 294L, 295L, 296L, 297L, 298L, 299L,
300L, 301L, 302L, 303L, 304L, 305L, 306L, 307L, 308L, 309L, 310L,
311L, 312L, 313L, 314L, 315L, 316L, 317L, 318L, 319L, 320L, 321L,
322L, 323L, 324L, 325L, 326L, 327L, 328L, 329L, 330L, 331L, 332L,
333L, 334L, 335L, 336L, 337L, 338L, 339L, 340L, 341L, 342L, 343L,
344L, 345L, 346L, 347L, 348L, 349L, 350L, 351L, 352L, 353L, 354L,
355L, 356L, 357L, 358L, 359L, 360L, 361L, 362L, 363L, 364L, 365L,
366L, 367L, 368L, 369L, 370L, 371L, 372L, 373L, 374L, 375L, 376L,
377L, 378L, 379L, 380L, 381L, 382L, 383L, 384L, 385L, 386L, 387L,
388L, 389L, 390L, 391L, 392L, 393L, 394L, 395L, 396L, 397L, 398L,
399L, 400L, 401L, 402L, 403L, 404L, 405L, 406L, 407L, 408L, 409L,
410L, 411L, 412L, 413L, 414L, 415L, 416L, 417L, 418L, 419L, 420L,
421L, 422L, 423L, 424L, 425L, 426L, 427L, 428L, 429L, 430L, 431L,
432L, 433L, 434L, 435L, 1L)), row.names = c(NA, -473L), groups = structure(list(
record_id = 110003, .rows = structure(list(1:473), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -1L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))
在第 66 天或第 67 天，天数不会停止，而是继续计数。这发生在其他几个record_id 上。
在第 36 天和第 38 天，explorer_day_30_count 开始计算得太早了。
在最后一天，vulnerable_day_30_count 已经开始计数，尽管没有中断 3 天。
解决方案
考虑这样的函数：
# 1. Determine the positions of zeros (p0) in `x`.
# 2. Test whether p0 - 1, p0 - 2, ..., p0 - n + 1 are zeros;
# reduce p0 to those that satisfy all conditions.
# 3. Find the upper bounds (ub). For example, if p0 = c(1,2,3),
# then upper bounds will be c(2,3,?) (i.e. lead p0).
# ? is then 3 + 30 (the max you set) if it is still within
# the length of `x`; otherwise is the length of `x` plus 1.
# 4. Compute the sequence between each pair of p0 and ub and
# then unlist the result to a vector.
# 5. Assign the vector back to its correct position.
conditional_count <- function(x, n, max = 30L) {
len <- length(x); out <- integer(len)
p0 <- which(x == 0L)
if (n > 1L)
p0 <- Reduce(function(idx, i) idx[x[(idx - i + 1L)] == 0L], seq_len(n)[-1L], p0)
ub <- c(tail(p0, -1L), min(len + 1L, tail(p0, 1L) + max))
res <- unlist(lapply(ub - p0, seq_len))
`[<-`(out, p0[[1L]] + seq.int(0L, length(res) - 1L), res)
}
然后你可以
df %>%
mutate(
vulnerable_period_30count = conditional_count(`treatment (type)`, 1L),
vulnerable_period_30count_3days = conditional_count(`treatment (type)`, 3L)
)
输出（df我使用的只有四个变量：record_id, start, stop, treatment (type). 其他变量被删除了。）
record_id start stop treatment (type) vulnerable_period_30count vulnerable_period_30count_3days
1 110101 0 1 1 0 0
2 110101 1 2 1 0 0
3 110101 2 3 1 0 0
4 110101 3 4 0 1 0
5 110101 4 5 0 1 0
6 110101 5 6 0 1 1
7 110101 6 7 0 1 1
8 110101 7 8 2 2 2
9 110101 8 9 2 3 3
10 110101 9 10 2 4 4
11 110101 10 11 0 1 5
12 110101 11 12 0 1 6
13 110101 12 13 0 1 1
14 110101 13 14 0 1 1
15 110101 14 15 0 1 1
16 110101 15 16 0 1 1
17 110101 16 17 3 2 2
18 110101 17 18 3 3 3
19 110101 18 19 0 1 4
20 110101 19 20 3 2 5
21 110101 20 21 3 3 6
22 110101 21 22 3 4 7
23 110101 22 23 0 1 8
24 110101 23 24 2 2 9
25 110101 24 25 2 3 10
26 110101 25 26 2 4 11
27 110101 26 27 0 1 12
28 110101 27 28 0 1 13
29 110101 28 29 0 1 1
30 110101 29 30 1 2 2
31 110101 30 31 1 3 3
32 110101 31 32 1 4 4
33 110101 32 33 1 5 5
34 110101 33 34 1 6 6
35 110101 34 35 1 7 7
36 110101 35 36 1 8 8
37 110101 36 37 1 9 9
38 110101 37 38 1 10 10
39 110101 38 39 1 11 11
40 110101 39 40 1 12 12
41 110101 40 41 1 13 13
42 110101 41 42 1 14 14
43 110101 42 43 1 15 15
44 110101 43 44 1 16 16
45 110101 44 45 1 17 17
46 110101 45 46 1 18 18
47 110101 46 47 1 19 19
48 110101 47 48 1 20 20
49 110101 48 49 1 21 21
50 110101 49 50 1 22 22
51 110101 50 51 1 23 23
52 110101 51 52 1 24 24
53 110101 52 53 1 25 25
54 110101 53 54 1 26 26
55 110101 54 55 1 27 27
56 110101 55 56 1 28 28
57 110101 56 57 1 29 29
58 110101 57 58 1 30 30
59 110101 58 59 1 0 0
60 110101 59 60 1 0 0
更新
conditional_count <- function(x, n, max = 30L) {
len <- length(x); out <- integer(len)
p0 <- which(x == 0L)
if (n > 1L)
p0 <- Reduce(function(idx, i) idx[x[(idx - i + 1L)] == 0L], seq_len(n)[-1L], p0)
if (length(p0) < 1L)
return(out)
ub <- c(tail(p0, -1L), min(len + 1L, tail(p0, 1L) + max))
res <- unlist(lapply(ub - p0, seq_len))
`[<-`(out, p0[[1L]] + seq.int(0L, length(res) - 1L), res)
}
此错误可能是由于没有满足您上述条件的零。因此，p0 的长度为 0。我们可以再添加一个 if-else 语句来处理这个边界条件。尝试使用上面显示的代码。如果它仍然无法正常工作，请考虑使用类似 的内容更新您的问题dput(df[record_id == *, ])，其中*代表不稳定的组（即在本例中为 110005）。
更新 2
conditional_count <- function(x, n, max = 30L) {
len <- length(x); out <- integer(len)
p0 <- which(x == 0L)
if (n > 1L)
p0 <- Reduce(function(idx, i) {
lidx <- idx - i + 1L; lidx <- lidx[lidx > 0L]
idx[x[lidx] == 0L]
}, seq_len(n)[-1L], p0)
if (length(p0) < 1L)
return(out)
ub <- c(tail(p0, -1L), min(len + 1L, tail(p0, 1L) + max))
res <- unlist(lapply(ub - p0, seq_len))
`[<-`(out, p0[[1L]] + seq.int(0L, length(res) - 1L), res)
}
我设法使用一些模拟数据重现了您的问题。该错误也是由边界条件引起的。当代码尝试验证序列 p0 - 1, p0 - 2, ... 时，如果向量的开头有一个零，它可能会变为负数treatment (type)。我已经纠正了那部分。尝试使用上面的更新代码。
更新 3
conditional_count <- function(x, n, max = 30L) {
len <- length(x); out <- integer(len)
p0 <- which(x == 0L)
if (n > 1L)
p0 <- Reduce(function(idx, i) {
lidx <- idx - i + 1L
idx <- idx[lidx > 0L]; lidx <- lidx[lidx > 0L]
idx[x[lidx] == 0L]
}, seq_len(n)[-1L], p0)
if (length(p0) < 1L)
return(out)
ub <- pmin(c(tail(p0, -1L), len), p0 + max - 1L)
rl <- ub - p0 + 1L
res <- unlist(lapply(rl, seq_len))
pos <- inverse.rle(list(lengths = rl, values = p0)) + res - 1L
`[<-`(out, pos, res)
}
试试这个新的。我修改了一些逻辑。我之前假设只有最后一个有效零的计数可以超过 30 天。这就是为什么在有效零之间计数永远不会停止的原因。此外，合成向量没有分配到正确的位置。此错误还会造成您观察到的一些异常情况。我已经纠正了两者。结果现在看起来像这样
structure(list(record_id = c(110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003, 110003, 110003, 110003,
110003, 110003, 110003, 110003, 110003), day_count = c(0, 1,
2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,
52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67,
68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,
84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99,
100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112,
113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125,
126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138,
139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151,
152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164,
165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177,
178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190,
191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203,
204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216,
217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229,
230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242,
243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255,
256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268,
269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281,
282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294,
295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307,
308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320,
321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333,
334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346,
347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359,
360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372,
373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385,
386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398,
399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411,
412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424,
425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437,
438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450,
451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463,
464, 465, 466, 467, 468, 469, 470, 471, 472), day_count_stop = c(1,
2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51,
52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67,
68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,
84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99,
100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112,
113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125,
126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138,
139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151,
152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164,
165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177,
178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190,
191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203,
204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216,
217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229,
230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242,
243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255,
256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268,
269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281,
282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294,
295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307,
308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320,
321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333,
334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346,
347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359,
360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372,
373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385,
386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398,
399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411,
412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424,
425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437,
438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450,
451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463,
464, 465, 466, 467, 468, 469, 470, 471, 472, 473), oac_class = 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, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 0), vulnerable_period_30count = 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, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L,
24L, 25L, 26L, 27L, 28L, 29L, 30L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L), vulnerable_period_30count_3days = c(0L,
0L, 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, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L,
24L, 25L, 26L, 27L, 28L, 29L, 30L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L)), row.names = c(NA,
-473L), groups = structure(list(record_id = 110003, .rows = structure(list(
1:473), ptype = integer(0), class = c("vctrs_list_of", "vctrs_vctr",
"list"))), row.names = 1L, class = c("tbl_df", "tbl", "data.frame"
), .drop = TRUE), class = c("grouped_df", "tbl_df", "tbl", "data.frame"
))
推荐阅读
- regex - 发生第 n 次后正则表达式 Oracle 替换
- jasper-reports - Jasper 中的细节带在中间和页面大小限制中被切断
- javascript - JQuery $.fn 在 Internet Explorer 11 上不起作用
- regex - 从 http 重定向到 https 时 mod_rewrite 中的无限重定向
- java - 如何在 Android 中提供 Firestore 身份验证？
- php - Chrome 上的 php 会话
- python - 导入系统如何在 python 中工作？
- node.js - (Dialogflow) 如何将 Place API 中的地点信息存储到意图参数中？
- sql - 从 DB2 中的列条目中查找多个子字符串
- android - '错误：包不存在' React Native Android Studio