计算嵌套的Tibble R中的比例？
[英]Calculate proportion in a nested tibble R?
问题描述
I have the following tibble object: 
我有以下tibble对象：
dt t uuid data
<date> <S3: hms> <chr> <list>
2018-06-23 18:25:24 0b27ea5fad61c99d <tibble>
2018-06-23 18:25:38 0b27ea5fad61c99d <tibble>
2018-06-23 18:26:01 0b27ea5fad61c99d <tibble>
The dput version of the first observation for illustration: 用于说明的第一个观察的dput版本：
structure(list(dt = structure(17705, class = "Date"), t = structure(66324, class = c("hms",
"difftime"), units = "secs"), uuid = "0b27ea5fad61c99d", data = list(
structure(list(Date = structure(c(17689, 17689, 17689, 17690,
17690, 17690, 17690, 17690, 17690, 17691, 17691, 17691, 17691,
17691, 17691, 17691, 17691, 17691, 17692, 17692, 17692, 17692,
17692, 17692, 17692, 17692, 17692, 17692, 17692, 17692, 17692,
17692, 17692, 17692, 17692, 17692, 17692, 17692, 17692, 17692,
17692, 17692, 17692, 17692, 17692, 17692, 17692, 17692, 17692,
17692, 17692, 17692, 17692, 17692, 17692, 17692, 17692, 17692,
17692, 17692, 17692, 17692, 17692, 17692, 17692, 17692, 17692,
17692, 17692, 17692, 17692, 17692, 17692, 17692, 17693, 17693,
17693, 17693, 17693, 17693, 17693, 17693, 17693, 17693, 17693,
17693, 17693, 17693, 17693, 17693, 17693, 17693, 17693, 17693,
17693, 17693, 17693, 17693, 17693, 17693, 17693, 17693, 17693,
17693, 17693, 17693, 17693, 17693, 17693, 17693, 17693, 17694,
17694, 17694, 17694, 17694, 17694, 17694, 17694, 17694, 17694,
17694, 17694, 17694, 17694, 17694, 17694, 17694, 17694, 17694,
17694, 17694, 17694, 17694, 17694, 17694, 17694, 17694, 17694,
17694, 17694, 17694, 17694, 17694, 17694, 17694, 17694, 17695,
17695, 17695, 17695, 17695, 17695, 17695, 17695, 17695, 17695,
17695, 17695, 17695, 17695, 17695, 17695, 17695, 17695, 17695,
17695, 17695, 17696, 17696, 17696, 17696, 17696, 17696, 17696,
17696, 17696, 17696, 17696, 17696, 17696, 17696, 17696, 17696,
17696, 17696, 17696, 17696, 17696, 17696, 17696, 17696, 17696,
17696, 17696, 17696, 17696, 17697, 17697, 17697, 17697, 17697,
17697, 17697, 17697, 17697, 17697, 17697, 17697, 17697, 17697,
17697, 17697, 17697, 17697, 17697, 17697, 17697, 17697, 17697,
17697, 17697, 17697, 17697, 17698, 17698, 17698, 17698, 17698,
17698, 17698, 17698, 17699, 17699, 17699, 17699, 17699, 17699,
17699, 17699, 17699, 17699, 17699, 17699, 17699, 17699, 17699,
17699, 17699, 17699, 17699, 17699, 17699, 17699, 17699, 17699,
17699, 17699, 17699, 17699, 17699, 17699, 17699, 17699, 17699,
17699, 17699, 17699, 17699, 17699, 17699, 17699, 17699, 17699,
17699, 17700, 17700, 17700, 17700, 17700, 17700, 17700, 17700,
17700, 17700, 17700, 17700, 17700, 17700, 17700, 17700, 17700,
17700, 17700, 17700, 17700, 17700, 17700, 17700, 17700, 17700,
17700, 17700, 17700, 17700, 17700, 17700, 17700, 17700, 17700,
17700, 17700, 17700, 17700, 17701, 17701, 17701, 17701, 17701,
17701, 17701, 17701, 17701, 17701, 17701, 17701, 17701, 17701,
17701, 17701, 17701, 17701, 17701, 17701, 17701, 17701, 17701,
17701, 17701, 17701, 17701, 17701, 17701, 17701, 17701, 17701,
17701, 17701, 17701, 17701, 17701, 17701, 17701, 17701, 17701,
17701, 17701, 17701, 17701, 17701, 17701, 17701, 17701, 17701,
17701, 17701, 17701, 17701, 17701, 17702, 17702, 17702, 17702,
17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702,
17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702,
17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702,
17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702,
17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702,
17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702,
17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702, 17702,
17702, 17702, 17703, 17703, 17703, 17703, 17703, 17703, 17703,
17703, 17703, 17703, 17703, 17703, 17703, 17703, 17703, 17703,
17703, 17703, 17703, 17703, 17703, 17703, 17703, 17703, 17703,
17703, 17703, 17703, 17703, 17703, 17703, 17703, 17703, 17703,
17703, 17703, 17703, 17703, 17703, 17703, 17703, 17703, 17703,
17703, 17703, 17703, 17703, 17703, 17703, 17703, 17703, 17703,
17704, 17704, 17704, 17704, 17704, 17704, 17704, 17704, 17704,
17704), class = "Date"), Time = structure(c(76180, 77415,
84620, 27900, 28132, 29396, 32914, 32962, 54105, 75066, 79109,
79761, 79810, 79700, 80245, 80229, 80282, 80322, 14443, 23356,
24693, 24752, 25133, 28226, 28764, 29110, 29134, 29159, 29267,
33427, 34404, 34617, 34763, 35866, 35974, 36719, 39145, 38499,
39852, 39975, 40289, 40576, 41567, 43894, 44953, 45555, 46226,
46627, 46827, 46955, 47220, 46644, 47263, 47378, 47630, 47996,
48043, 49479, 50984, 51343, 51258, 52258, 52904, 57153, 58608,
58583, 58971, 59210, 61133, 61648, 62976, 63472, 63972, 67364,
25886, 27299, 27850, 28049, 28594, 32058, 32357, 32462, 32557,
32509, 35118, 35263, 35290, 37042, 38741, 40548, 40828, 42071,
43121, 43937, 44384, 44485, 50519, 53615, 53494, 54243, 55578,
57923, 58865, 59724, 64270, 68078, 69995, 71501, 71707, 71967,
74995, 27594, 31387, 32478, 32868, 35247, 35452, 35522, 39692,
40644, 40933, 43548, 44010, 44086, 47030, 47914, 49023, 49196,
50662, 51982, 52746, 55985, 56610, 59743, 61022, 62133, 62402,
62420, 63398, 63633, 67930, 68411, 73376, 76344, 80432, 82015,
82351, 24225, 24679, 29225, 32266, 32415, 36887, 39831, 41974,
42030, 42133, 46704, 47929, 54556, 57009, 57106, 56783, 57383,
57420, 57805, 71180, 72821, 27255, 31671, 31820, 32089, 36313,
39787, 43635, 44106, 44560, 46140, 46571, 46849, 51846, 52171,
52683, 54143, 60143, 61860, 62622, 62656, 63347, 63498, 64526,
64702, 64881, 64973, 67687, 67937, 68403, 25846, 27905, 27923,
28073, 28587, 28853, 29066, 34244, 34266, 34480, 34688, 35199,
35303, 36230, 36376, 39140, 47117, 47132, 49980, 50063, 55961,
56225, 58782, 65204, 65299, 65319, 65694, 76349, 79726, 81378,
81972, 82075, 82367, 84768, 84920, 24213, 24350, 24682, 27470,
28090, 32683, 33905, 36274, 37506, 37618, 37682, 37774, 40292,
40528, 42275, 42657, 43803, 44483, 45386, 45611, 45715, 45825,
47226, 47287, 47395, 47503, 47561, 49169, 51534, 51646, 54667,
54688, 54754, 54771, 54812, 54841, 54910, 55199, 55608, 56619,
59078, 60679, 69005, 25211, 27252, 29446, 30652, 32035, 37692,
37966, 38517, 40175, 40540, 41137, 43736, 43789, 43797, 43926,
44552, 44586, 45023, 45195, 45387, 50375, 50816, 51879, 52482,
54255, 55184, 56594, 57074, 57448, 57854, 58102, 58116, 58382,
59777, 62726, 62845, 63068, 63568, 65434, 26420, 26600, 29047,
29134, 29222, 29295, 29636, 30698, 32763, 34298, 34432, 34485,
34954, 36989, 37891, 37947, 37972, 38009, 38052, 38094, 38150,
38308, 38533, 40329, 41015, 41260, 42744, 42899, 43001, 43235,
43621, 43881, 43909, 45112, 45090, 45648, 46116, 46686, 48270,
48786, 50962, 51051, 51330, 51395, 53075, 53896, 54042, 54142,
56698, 57344, 65960, 74606, 81947, 82059, 85004, 18916, 19188,
19353, 19848, 22190, 22303, 22963, 26657, 27389, 28392, 29519,
29565, 30635, 30949, 34961, 37536, 38142, 40358, 40567, 41231,
41761, 41729, 41993, 42723, 45463, 46900, 47061, 47139, 47215,
47654, 47931, 48519, 49267, 49329, 51611, 51676, 51821, 51897,
52148, 51159, 52215, 52227, 52247, 53331, 53401, 54133, 54528,
54964, 54913, 54998, 55241, 55331, 55352, 55496, 56646, 56707,
56749, 56782, 56914, 57400, 57827, 58055, 58234, 59105, 59453,
59742, 66231, 66418, 67704, 25500, 27174, 27363, 27651, 27850,
28815, 28817, 28919, 29060, 29148, 32568, 32791, 32909, 33094,
33016, 33202, 33398, 33430, 33912, 34564, 34667, 34886, 35117,
35815, 36093, 43248, 43340, 43999, 44142, 44116, 44275, 44177,
44371, 44457, 44989, 45137, 45226, 45709, 47674, 48013, 48057,
48237, 48282, 48366, 48890, 54286, 55108, 56714, 57376, 59419,
68770, 74236, 1897, 28879, 30194, 30570, 45975, 53719, 53738,
57533, 58730, 69699), class = c("hms", "difftime"), units = "secs"),
phone_number = c(22881, 74049, 74049, 22881, 22881, 22881,
74049, 74049, 22881, 80079, 80838, 60397, 57727, 80838,
80838, 57727, 80838, 51122, 5444, NA, 13692, 22881, 6173,
22881, 22881, 86025, 86025, 86025, 86933, 86963, 62667,
86025, 80094, 77668, 86933, 86882, 95422, 71111, 95422,
80094, 22881, 77668, 77668, 86903, 22881, 77668, 35244,
35244, 35244, 65575, 62667, 22881, 62667, 65575, 35244,
22881, 22881, 71111, 22881, 77668, 22881, 22881, 61195,
61195, 72116, 86975, 72116, 72116, 22881, 22881, 11980,
22881, 22881, 22881, 11980, 60397, 11980, 60397, 22881,
71111, 3369, 86994, 86994, 71111, 4650, 4650, 86994,
11980, 80064, 80064, 60397, 4650, 80064, 61195, 4650,
4650, 55652, 60397, 1050, 60397, 34800, 61191, 11980,
11980, 86411, 0, 60397, 22881, 22881, 51122, 1050, 78335,
NA, 22881, 80098, 22881, 80098, 22881, 61195, 80098,
86865, 22881, 86903, 22881, 86013, 8473, NA, 77668, 77668,
80111, 86865, 22881, 22881, NA, 22881, 66655, 66655,
22881, 22881, 77668, NA, 1050, 80838, NA, 6173, 6173,
5444, 6173, 6173, 8473, 84091, 21383, 21383, 86882, NA,
61191, 61191, 4500, 86882, 66655, 74049, 74049, 1050,
74049, 74049, 80838, 11980, 76532, 22881, 33555, 33555,
86903, NA, NA, 61195, 61195, 61195, NA, 80064, 80111,
NA, 86903, 94801, 80064, 11980, 22881, 22881, 22881,
22881, 22881, 22881, 22222, 68804, 68804, 22881, 22881,
22881, 22881, 22881, 22881, 22881, 68804, 68804, 22881,
68804, 68804, 68804, 68804, 68804, 22881, 22881, 22881,
74049, 74049, 74049, 80838, 74049, 29227, 29227, 74049,
29227, 29227, 29227, 60397, 9525, 9525, 22881, 50528,
50528, 22881, 50528, 50528, 50528, 50528, 50528, 22881,
78335, 84091, 21383, 1050, NA, 1050, 86882, 1050, 25987,
61195, 80079, 86882, 86865, 86903, 65633, 5701, 78335,
86850, 86882, 68695, 22881, 79521, 79521, 22881, 86882,
65633, 84091, 84091, 84091, 90772, 80064, 84091, 80064,
84091, 22881, 86963, 10869, 22881, 22881, 77668, 22881,
22881, 5477, 77668, 54963, 22881, 77668, 21383, 22881,
77326, 86903, 86963, 86963, 78335, 86903, 21383, 86903,
86903, 86963, 77668, 86882, 80062, 80062, 49296, 7067,
4650, 4650, 22881, 61195, 61195, 61195, 22881, 51122,
22881, 61195, 51122, 80098, 22881, 22881, 22881, 5444,
77668, 5444, 77668, 77668, 35244, 62667, 78877, 77668,
22881, 86411, 4650, 76723, 68695, 68695, 35244, 77668,
77668, 35244, 9875, 86948, 76532, 62667, 13077, 62667,
62667, 62667, 80064, 62667, 77668, 86903, 90772, 77668,
62667, 62667, 61195, 62236, 86903, 77668, 77668, 77668,
86882, 62667, 77668, 77668, 77668, 24120, 77668, 22881,
60397, 50528, 50528, 50528, 63560, 63560, 63560, 63560,
50528, 50528, 50528, 11980, 11980, 22881, 80079, 86882,
6209, 77668, 63043, 86882, 73146, 86882, 84091, 73146,
86865, 73146, 86865, 86979, 62236, 86963, 58090, 62667,
58090, 7067, 86963, 4650, 4650, 86882, 21383, 21383,
62667, 62667, 21383, 9232, 62667, 21383, 62667, 86903,
86903, 86903, 86882, 86865, 85833, 86865, 61195, 84091,
84091, 22881, 3000, 22881, 85833, 85833, 51122, 51122,
85833, 22881, 22881, 22881, 57727, 22881, 22881, 22881,
22881, 22881, 22881, 22881, 1050, 1050, 84091, 84091,
22881, 84091, 61195, 80062, 72116, 65575, 31620, 65575,
31620, 80079, 80064, 80064, 53329, NA, 4650, 22881, 22881,
86882, 61195, 86882, 61195, 13077, 61195, 61195, 86882,
13077, 13077, 86903, 86882, 72116, 72116, 61195, 61195,
5595, 5595, 61195, 5431, 22881, 86903, 86903, 21383,
61195, 61195, 84219, 0, 95422, 22881, 22881, 22881, 90849,
22881, 22881, 22881, 11980, 22881), isInContact = c(TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE,
FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE,
TRUE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE,
FALSE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, TRUE, FALSE,
FALSE, TRUE, TRUE, TRUE, FALSE, TRUE, TRUE, FALSE, TRUE,
TRUE, TRUE, TRUE, TRUE, FALSE, TRUE, TRUE, TRUE, TRUE,
FALSE, TRUE, TRUE, FALSE, TRUE, FALSE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, TRUE, TRUE, FALSE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, TRUE, TRUE, TRUE,
FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, FALSE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, TRUE, FALSE, TRUE,
FALSE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE,
TRUE, FALSE, FALSE, TRUE, TRUE, FALSE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
FALSE, TRUE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE), callDuration = c(1, 0, 0, 71,
13, 54, 0, 315, 135, 87, 34, 0, 0, 233, 0, 3249, 3193,
3142, 10, 11, 0, 117, 0, 59, 137, 0, 0, 0, 1, 33, 27,
85, 0, 7, 145, 23, 0, 1039, 25, 305, 0, 0, 35, 58, 21,
110, 0, 0, 0, 0, 0, 601, 98, 228, 349, 0, 526, 1045,
0, 5, 515, 167, 76, 30, 0, 65, 112, 100, 0, 215, 362,
0, 301, 109, 1379, 0, 199, 532, 10, 8, 83, 0, 0, 1563,
130, 23, 116, 0, 0, 0, 505, 146, 71, 0, 17, 107, 0, 0,
732, 670, 0, 0, 0, 32, 0, 0, 280, 0, 61, 0, 0, 21, 34,
68, 126, 0, 0, 49, 81, 12, 0, 0, 35, 196, 16, 0, 33,
0, 24, 88, 181, 0, 0, 24, 146, 163, 10, 0, 87, 52, 24,
1208, 946, 0, 0, 0, 24, 0, 0, 0, 82, 48, 130, 1769, 0,
0, 242, 52, 209, 35, 0, 0, 567, 0, 126, 900, 0, 0, 257,
93, 95, 8, 17, 33, 0, 23, 15, 237, 116, 25, 16, 56, 6,
0, 619, 119, 0, 163, 0, 73, 107, 154, 0, 56, 0, 0, 58,
44, 0, 0, 43, 0, 29, 27, 0, 0, 0, 0, 0, 7, 0, 15, 60,
0, 66, 52, 11, 53, 79, 106, 0, 0, 112, 872, 0, 308, 0,
0, 0, 172, 0, 0, 0, 0, 0, 39, 18, 126, 39, 0, 34, 0,
48, 1462, 56, 0, 0, 105, 300, 0, 27, 75, 22, 51, 38,
71, 0, 0, 20, 0, 24, 7, 0, 0, 0, 19, 0, 0, 0, 16, 232,
74, 66, 108, 272, 0, 695, 25, 14, 25, 215, 0, 9, 183,
540, 6, 29, 0, 41, 51, 0, 8, 0, 22, 26, 29, 42, 0, 85,
8, 52, 107, 23, 14, 62, 0, 29, 0, 44, 91, 143, 15, 89,
144, 0, 0, 11, 69, 10, 106, 49, 65, 94, 33, 39, 0, 804,
17, 34, 0, 29, 61, 15, 38, 65, 62, 15, 58, 109, 394,
85, 17, 21, 91, 62, 8, 30, 0, 34, 83, 56, 121, 32, 88,
79, 0, 172, 101, 75, 0, 40, 35, 363, 44, 0, 111, 0, 0,
0, 33, 0, 100, 85, 0, 0, 0, 88, 528, 364, 0, 91, 31,
60, 162, 6, 0, 66, 34, 0, 0, 250, 501, 66, 18, 0, 46,
8, 71, 13, 71, 0, 38, 68, 0, 0, 0, 0, 0, 1040, 0, 17,
124, 0, 354, 60, 218, 0, 79, 109, 56, 0, 133, 653, 22,
0, 0, 14, 0, 105, 11, 0, 2, 220, 76, 174, 0, 24, 113,
22, 30, 269, 0, 925, 0, 16, 43, 26, 80, 0, 82, 0, 0,
110, 0, 0, 25, 17, 47, 19, 12, 0, 40, 21, 0, 27, 49,
0, 41, 0, 174, 0, 85, 36, 0, 0, 9, 0, 17, 0, 0, 35, 57,
150, 0, 133, 18, 0, 169, 129, 0, 0, 88, 62, 142, 433,
0, 4, 0, 1, 1)), .Names = c("Date", "Time", "phone_number",
"isInContact", "callDuration"), row.names = c(NA, -500L), class = c("tbl_df",
"tbl", "data.frame")))), .Names = c("dt", "t", "uuid", "data"
), row.names = c(NA, -1L), class = c("tbl_df", "tbl", "data.frame"
))
Now I want to calculate the proportion of the isInContact == 1 : 现在我要计算isInContact == 1的比例：
df %>% mutate(tmp = lapply(data, pull, var = isInContact),
prop_in_contact = mean(tmp == TRUE))
But this doesn't work, please advise what I am missing here? 但这不起作用，请告知我在这里缺少什么？ I would like to understand the principal and the logic behind your answer to learn how to perform such tasks in the future. 我想了解您的答案背后的原理和逻辑，以了解如何在将来执行此类任务。 Every time I am trying to calculate it it behaves different. 每次我试图计算它时，它的行为都不同。
Expected output: 预期产量：
dt t uuid data data_is_in_contact_prop_TRUE
<date> <S3: hms> <chr> <list> <double>
2018-06-23 18:25:24 0b27ea5fad61c99d <tibble> 0.87
2018-06-23 18:25:38 0b27ea5fad61c99d <tibble> 0.01
2018-06-23 18:26:01 0b27ea5fad61c99d <tibble> 0.9
1 个解决方案
解决方案1
3 已采纳 2018-07-02 08:26:22
Here is a possibility using purrr::map_dbl 这是使用purrr::map_dbl的可能性
df %>%
mutate(frac_isInContact = map_dbl(
data,
~sum(.x$isInContact == TRUE) / length(.x$isInContact)))
## A tibble: 1 x 5
# dt t uuid data frac_isInContact
# <date> <time> <chr> <list> <dbl>
#1 2018-06-23 18:25 0b27ea5fad61c99d <tibble [500 × 5]> 0.878
Explanation: We use map_dbl to calculate the fraction of TRUE entries in data$isInContact . 说明：我们使用map_dbl来计算data$isInContact中TRUE条目的分数。
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