我有看起来像以下数据：
# A time tibble: 6 x 3
# Index: index
ID index value
<dbl> <date> <dbl>
1 276217 2001-01-01 1.42
2 276217 2001-01-08 1.14
3 276217 2001-01-15 1.35
4 276217 2001-01-22 1.30
5 276217 2001-01-29 1.33
6 276217 2001-02-05 1.11
我有2个组，对于每个组，我尝试使用facet_wrap或facet_grid来应用函数并绘制图形。
我具有以下功能：
tidy_acf <- function(data, value, lags = 0:20) {
value_expr <- enquo(value)
acf_values <- data %>%
pull(value) %>%
acf(lag.max = tail(lags, 1), plot = FALSE) %>%
.$acf %>%
.[,,1]
ret <- tibble(acf = acf_values) %>%
rowid_to_column(var = "lag") %>%
mutate(lag = lag - 1) %>%
filter(lag %in% lags)
return(ret)
}
max_lag <- 52 * 12
然后，我尝试应用以下内容：
DATA %>%
group_by(ID) %>%
tidy_acf(value, lags = 0:max_lag) %>%
ggplot(aes(lag, acf)) +
facet_grid(rows = vars(ID))
所以我期望有2个地块的网格。
我的错误是：
Error: At least one layer must contain all faceting variables: `ID`.
* Plot is missing `ID`
* Layer 1 is missing `ID`
* Layer 2 is missing `ID`
* Layer 3 is missing `ID`
我认为ACF函数会“忽略” group_by命令，并为所有数据计算ACF。我尝试使用mutate和do时没有多大运气。
此外，当ggplot尝试读取行facet_grid(rows = vars(ID))时，没有ID变量。
数据：
structure(list(ID = c(276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 276217,
276217, 276217, 276217, 276217, 276217, 276217, 276217, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535, 673535, 673535, 673535, 673535, 673535,
673535, 673535, 673535), index = structure(c(11323, 11330, 11337,
11344, 11351, 11358, 11365, 11372, 11379, 11386, 11393, 11400,
11407, 11414, 11421, 11435, 11442, 11449, 11456, 11463, 11470,
11477, 11484, 11491, 11498, 11505, 11512, 11519, 11526, 11533,
11540, 11547, 11554, 11561, 11568, 11575, 11582, 11589, 11596,
11603, 11610, 11617, 11624, 11631, 11638, 11645, 11652, 11659,
11666, 11673, 11680, 11687, 11694, 11701, 11708, 11715, 11722,
11729, 11736, 11743, 11750, 11757, 11764, 11771, 11778, 11785,
11792, 11799, 11806, 11813, 11820, 11827, 11834, 11841, 11848,
11855, 11862, 11869, 11876, 11883, 11890, 11897, 11904, 11911,
11918, 11925, 11932, 11939, 11946, 11953, 11960, 11967, 11974,
11981, 11988, 11995, 12002, 12009, 12016, 12023, 12030, 12037,
12044, 12051, 12058, 12065, 12072, 12079, 12086, 12093, 12100,
12107, 12114, 12121, 12128, 12135, 12142, 12149, 12156, 12163,
12170, 12177, 12184, 12191, 12198, 12205, 12212, 12219, 12226,
12233, 12240, 12247, 12254, 12261, 12268, 12275, 12282, 12289,
12296, 12303, 12310, 12317, 12324, 12331, 12338, 12345, 12352,
12359, 12366, 12373, 12380, 12387, 12394, 12401, 12408, 12415,
12422, 12429, 12436, 12443, 12450, 12457, 12464, 12471, 12478,
12485, 12492, 12499, 12506, 12513, 12520, 12527, 12534, 12541,
12548, 12555, 12562, 12569, 12576, 12583, 12590, 12597, 12604,
12611, 12618, 12625, 12632, 12639, 12646, 12653, 12660, 12667,
12674, 12681, 12688, 12695, 12702, 12709, 12716, 12723, 12730,
12737, 12744, 12751, 12758, 12765, 12772, 12779, 12786, 12793,
12800, 12807, 12814, 12821, 12828, 12835, 12842, 12849, 12856,
12863, 12870, 12877, 12884, 12891, 12898, 12905, 12912, 12919,
12926, 12933, 12940, 12947, 12954, 12961, 12968, 12975, 12982,
12989, 12996, 13003, 13010, 13017, 13024, 13031, 13038, 13045,
13052, 13059, 13066, 13073, 13080, 13087, 13094, 13101, 13108,
13115, 13122, 13129, 13136, 13143, 11323, 11330, 11337, 11344,
11351, 11358, 11365, 11372, 11379, 11386, 11393, 11400, 11407,
11414, 11421, 11435, 11442, 11449, 11456, 11463, 11470, 11477,
11484, 11491, 11498, 11505, 11512, 11519, 11526, 11533, 11540,
11547, 11554, 11561, 11568, 11575, 11582, 11589, 11596, 11603,
11610, 11617, 11624, 11631, 11638, 11645, 11652, 11659, 11666,
11673, 11680, 11687, 11694, 11701, 11708, 11715, 11722, 11729,
11736, 11743, 11750, 11757, 11764, 11771, 11778, 11785, 11792,
11799, 11806, 11813, 11820, 11827, 11834, 11841, 11848, 11855,
11862, 11869, 11876, 11883, 11890, 11897, 11904, 11911, 11918,
11925, 11932, 11939, 11946, 11953, 11960, 11967, 11974, 11981,
11988, 11995, 12002, 12009, 12016, 12023, 12030, 12037, 12044,
12051, 12058, 12065, 12072, 12079, 12086, 12093, 12100, 12107,
12114, 12121, 12128, 12135, 12142, 12149, 12156, 12163, 12170,
12177, 12184, 12191, 12198, 12205, 12212, 12219, 12226, 12233,
12240, 12247, 12254, 12261, 12268, 12275, 12282, 12289, 12296,
12303, 12310, 12317, 12324, 12331, 12338, 12345, 12352, 12359,
12366, 12373, 12380, 12387, 12394, 12401, 12408, 12415, 12422,
12429, 12436, 12443, 12450, 12457, 12464, 12471, 12478, 12485,
12492, 12499, 12506, 12513, 12520, 12527, 12534, 12541, 12548,
12555, 12562, 12569, 12576, 12583, 12590, 12597, 12604, 12611,
12618, 12625, 12632, 12639, 12646, 12653, 12660, 12667, 12674,
12681, 12688, 12695, 12702, 12709, 12716, 12723, 12730, 12737,
12744, 12751, 12758, 12765, 12772, 12779, 12786, 12793, 12800,
12807, 12814, 12821, 12828, 12835, 12842, 12849, 12856, 12863,
12870, 12877, 12884, 12891, 12898, 12905, 12912, 12919, 12926,
12933, 12940, 12947, 12954, 12961, 12968, 12975, 12982, 12989,
12996, 13003, 13010, 13017, 13024, 13031, 13038, 13045, 13052,
13059, 13066, 13073, 13080, 13087, 13094, 13101, 13108, 13115,
13122, 13129, 13136, 13143), class = "Date"), value = c(1.41937020560682,
1.13730371661759, 1.3539311150167, 1.29696778568529, 1.3323626647449,
1.10981390720746, 1.18071375602539, 1.19207097496899, 1.19676816234154,
1.22239101776685, 1.2506070891073, 1.41996279851121, 1.12626118927859,
1.35762335181086, 1.39713439429607, 1.38612414908988, 1.34648704163679,
1.30960297429645, 1.32473144759308, 1.41881033664487, 1.42977103998914,
1.45886017825442, 1.43168869907128, 1.37756572500706, 1.68909064430956,
1.5361228794478, 1.48611232259234, 1.58072013349794, 1.45481742038903,
1.4817092550674, 1.24105214048689, 1.41069885959673, 1.28674202240156,
1.54781553519693, 1.38282364059626, 1.42928968301089, 1.17276730477843,
1.34700737129064, 1.13164253306323, 1.42389865505797, 1.17592348061104,
1.38300636631992, 1.3547327097731, 1.28131014670212, 1.2555870634607,
1.52185998250405, 1.17456066715388, 1.23671084290859, 1.35047806931946,
1.49865878240371, 1.65716461782272, 1.43726769110404, 1.31690661185925,
1.29129879112465, 1.19842719818708, 1.29484342347787, 1.52377764218684,
1.12200241957802, 1.20079971092347, 1.16407218274476, 1.34362475426389,
1.32208564023239, 1.25706881626001, 1.29752528762653, 1.25449120532999,
1.19172390630137, 1.31170344960018, 1.24839862907423, 1.21805675875317,
1.12246668431943, 1.21680442566904, 1.233324635472, 1.3183740810356,
1.34191361856964, 1.27794948142411, 1.2350002695076, 1.40188172678391,
1.3905788567514, 1.52842869568866, 1.34555771095665, 1.47268660991843,
1.46644830848524, 1.32154683578951, 1.24416519323, 1.21297851393759,
1.33453445324598, 1.39167121745469, 1.47121045110368, 1.28918946132591,
1.27498741795507, 1.31327037340205, 1.27139947787948, 1.30133531812561,
1.45850847546917, 1.31951867476118, 1.04465952644041, 1.26616814025568,
1.45491572126488, 1.49066211565058, 1.21260446801099, 1.51101227343164,
1.28374730661533, 1.4606510930363, 1.54310674593129, 1.3943023792947,
1.21617488502602, 1.27779510696235, 1.26492049349337, 1.28893561379684,
1.34101339160729, 1.23653444605546, 1.52937951802558, 1.24611066742983,
1.40556767894264, 1.36613239155494, 1.15566891632031, 1.36978139561172,
1.21620591005457, 1.19672278171019, 1.31878337610884, 1.23841209401771,
1.34868610368419, 1.18860731906096, 1.43455676790059, 1.28875013956958,
1.27312347874578, 1.29363479109929, 1.33262043145855, 1.38160602058133,
1.61479387947761, 1.35804447140576, 1.41149040095419, 1.48017031490425,
1.47576645263688, 1.5245822496389, 1.33559282862022, 1.2599120663954,
1.35966779424493, 1.2266712872336, 1.33798458662942, 1.20584978864545,
1.18799246468728, 1.18385487480062, 1.0622352775507, 1.10529104509327,
1.35359695992605, 1.12279116483699, 1.03213829824401, 1.08654744699064,
1.26657156230531, 1.40230470980855, 1.02834232411836, 1.40946282039393,
1.28539537543728, 1.43892218365149, 1.49298397663843, 1.15976118620392,
1.20804939370669, 1.10072248466824, 1.14422045115725, 1.2028133706493,
1.11274509334125, 1.21394374577131, 1.12952599532327, 1.10682691857272,
1.22839520113321, 1.30304178253435, 1.18115210023735, 1.21616506619252,
1.1486616532461, 1.06528565526184, 1.28015893048186, 1.04568291345179,
1.19030647756617, 1.17271787931786, 1.24257225165359, 1.28837051097269,
1.21364584611854, 1.32183965388118, 1.62565762633464, 1.34108886133387,
1.45861718634725, 1.40680343219648, 1.49898988719805, 1.37365484263548,
1.40194709465205, 1.52119768777043, 1.1546139113979, 1.34663756991197,
1.19175504361163, 1.38802433610545, 1.42482301211201, 1.28861676565775,
1.29583234931414, 1.3539253596777, 1.19371894069907, 1.29596409461602,
1.31604466739086, 1.16953727329986, 1.24571329130068, 1.20977722712303,
1.32133145369149, 1.22022262451546, 1.11043339713881, 1.18314381744431,
1.26442168060822, 1.20687048368665, 1.19001235469596, 1.13379603549586,
1.15500524682456, 1.29730166142161, 1.42125202522948, 1.30979026623885,
1.19822081427195, 0.970223979901651, 1.01170895674301, 1.06833234437818,
1.1567954374083, 1.14600483321563, 1.28862549400355, 1.26172237771525,
1.02111868419395, 1.07703997971764, 1.16778050692621, 1.23274164934758,
1.14220017603011, 1.26895607326201, 1.13052624629828, 1.15093653420372,
1.21421061979431, 1.31260087277151, 1.23609359665254, 1.22091083541942,
1.18755107607541, 1.20276269855061, 1.15596099825208, 1.29433716711344,
1.34000352773031, 1.374339559464, 1.3320530338296, 1.38213986834908,
1.09417814672424, 1.41175179189304, 1.4443513919479, 1.18686762085048,
1.12443328747865, 1.29014597840925, 1.25944166196376, 1.11314610197784,
1.12316114098931, 1.08278643471745, 1.08446914721635, 1.07284297889302,
1.26479980128396, 1.22784784783676, 1.16565880517992, 1.1331496618174,
1.14958582045566, 1.42505611714813, 1.36497139656022, 0.762877732531809,
0.5894904370784, 0.52640374646506, 0.760587540343175, 0.857893882608007,
0.782581957325627, 0.642950696238089, 0.773040192810864, 0.692955963984261,
0.608798647608425, 0.719257304351197, 1.09157551261522, 0.605847308747244,
0.607101755350968, 0.931947730208544, 0.623059079872713, 0.652200825716763,
0.783988475111917, 0.708693777149976, 0.851179407205504, 0.867212188981653,
1.01249123310826, 0.832261335348492, 1.01642068444198, 0.768581853602418,
0.738178550284871, 1.07087389090617, 0.725185530890722, 0.915022447538265,
1.03656372445932, 0.683513589539164, 0.760759035493538, 0.962607981940909,
0.881106061148774, 1.07992272712261, 0.6940197513087, 1.24427844954137,
0.937092846348055, 0.785797045379898, 1.09913118425944, 0.984160545246009,
0.769094802245811, 0.892485889935335, 0.762981553768869, 0.962905698297224,
0.910723959387533, 0.796823913083302, 1.11776176611975, 0.990528711597118,
0.916277885817988, 0.754922846376312, 0.789859817063917, 0.583252537946175,
0.869048949001103, 0.904241238082762, 0.792797391202002, 0.824905104850026,
0.796067287268244, 0.705002929794062, 0.610738122940513, 0.740039977653799,
0.610202923126631, 0.730617879642999, 0.818060623496325, 0.686573473815161,
0.705818060545842, 0.7344556153191, 0.621681577668493, 1.01291062465701,
0.726797765613636, 0.799983190290583, 0.81352068284914, 1.20290672862058,
0.956972752784302, 0.899695591941931, 0.734494760133977, 0.918082644120655,
0.803144251887721, 0.90840105184199, 1.01870315081598, 0.754963006088199,
0.655924111314657, 0.635979000600382, 0.637823081118935, 0.74219078811824,
0.658443679394198, 0.848643856810564, 1.01679807837156, 0.64924000203248,
0.721495807650437, 0.995843616253178, 0.587567067234205, 0.885388384396393,
0.804755702236206, 0.88039649895026, 1.22892254775891, 0.654383489887676,
0.684414353519528, 0.82311483323441, 0.738445568441471, 0.985270508555264,
0.538027793838735, 0.67254042415109, 0.633305896313126, 0.677514338408576,
0.707861122799185, 0.898879947396628, 0.568007850104993, 0.820356325826786,
0.890132617561718, 0.819518861020891, 0.640866340833552, 0.740566063515691,
0.645941423240264, 0.640005312025865, 0.512662089777166, 0.545981143731435,
0.645783228140564, 0.650566996249936, 0.932063079996881, 0.8297715985113,
0.583812645526694, 0.79671714309694, 0.554608909530225, 0.772774431644987,
0.612018242382329, 0.632731183161737, 1.10874043293385, 0.691113408480122,
0.67670539385424, 0.756826654641211, 0.768060859016454, 0.885031727269359,
0.823484255503393, 0.73517482053536, 1.03739291336419, 0.870623096705543,
1.1194311197314, 0.726119289744962, 0.644851629240191, 0.76013331519735,
0.560668740229276, 0.931616505672441, 0.762174394414433, 0.607422071693735,
0.794972372981508, 0.853881172459784, 0.843633537139329, 1.05041450556316,
0.536434294372646, 0.656612696998115, 0.558405219921965, 0.755700609928556,
0.671622788195764, 0.773200131224459, 0.787809813915869, 0.752185735418751,
0.66574833782471, 0.745533410847401, 0.812030376024714, 0.856602413966287,
0.791251263099112, 0.792360401499752, 0.544983809039963, 0.677788404933327,
0.811903043853608, 0.794753307517171, 0.723075319600815, 0.562075181459737,
0.678502428959742, 0.77053008135789, 1.14362850092319, 0.741834489079122,
0.546785233571552, 0.795344208194642, 0.505119229967037, 0.920730172911113,
0.796735200185373, 0.75490879746383, 0.766143669886884, 0.858382127622966,
0.741361275131017, 0.958796686496966, 0.730874542052134, 0.743581487352913,
0.794645828336577, 0.827064450971909, 0.535165553807624, 0.79714773022668,
0.933647930767804, 0.904781872982919, 0.778038374261388, 0.737032233790766,
0.636467007427987, 0.588315531583391, 0.57789678487892, 0.653445424930302,
0.716818765540808, 0.681654384075588, 0.941300215713349, 0.816145818070346,
0.653499164576688, 0.65366241688387, 0.635082148614803, 0.782506231125364,
0.540581221109251, 0.880390955968106, 0.949533548689565, 0.656740433162245,
0.645784296818701, 0.835744907749697, 0.883383077894964, 0.856871617610107,
0.793507512069987, 0.644649833901959, 0.667659239793578, 0.566975791202607,
0.805072718065176, 0.76189782781533, 0.908993183134203, 0.57958180848488,
0.595493495671665, 0.595298981005907, 0.691244844002269, 0.559001941268423,
0.841944908413524, 0.502638437519587, 0.995560002118792, 1.03400866336882,
0.781447555328994, 0.848505938905025, 1.10657203868824, 1.00949522054762,
0.680172374435646, 0.980497319076417, 0.640836501543487, 1.03473567233595,
0.970381583577073, 1.15687939463795, 0.775243943082199, 0.75378979506369,
0.636035597193233, 0.691945202550093, 0.712384411483125, 0.780216998875879,
0.465494109331028, 0.683261414179953, 0.791400883275817, 0.555590485062775,
0.536696577165946, 0.413733248705531, 0.691415618521668, 0.65952361324002,
0.562421063932012, 0.810094133287698, 0.601494620395893, 0.43699550503586,
0.679366721960758, 0.518055035225684, 0.663463830695837)), row.names = c(NA,
-520L), index_quo = ~index, index_time_zone = "UTC", class = c("tbl_time",
"tbl_df", "tbl", "data.frame"))
答案 0 :(得分：2)
您可以尝试使用split和map代替group_by
DATA %>%
split(.$ID) %>%
map(~tidy_acf(.,value, lags = 0:max_lag)) %>%
bind_rows(.id = "ID") %>%
ggplot(aes(lag, acf)) +
geom_point() +
facet_grid(rows = vars(ID))
可以像这样优化您的功能
tidy_acf_fix <- function(data, value, lags = 0:20) {
value_expr <- enquo(value)
acf_values <- data %>%
pull(!!value_expr) %>%
acf(lag.max = tail(lags, 1), plot = FALSE) %>%
broom::tidy()
}
或者没有任何功能
DATA %>%
split(.$ID) %>%
map(~with(.,acf(value, lag.max =max_lag, plot = FALSE)) %>%
broom::tidy()) %>%
bind_rows(.id = "ID") %>%
ggplot(aes(lag, acf)) +
geom_point() +
facet_grid(rows = vars(ID))