r - 使用 unnest() 绘制存储在 tibble 中的多个不同长度的时间序列

Question

这是一个有更新的转贴，因为回复原贴的人能够解决部分问题，但我们发现了一个需要解决的新问题，我还没有找到其他帖子解决这个问题。如果不允许这样做，请告诉我!

所以我有一个包含四列和一大堆行的标题。我会把前几行放在帖子的末尾。第一列称为 id，每一行都有一个唯一的 id。下一列是 doy.series，第三列称为 smooth.series doy.series 和 smooth 中的每个条目。 series 列是列表。最后一列名为 doy，它是一个整数。

所以我想要的是针对每行的 smooth.series 绘制 doy.series，但将所有这些绘制为同一图上的线。我还希望线条由 doy 着色。我希望最高的 doy 值是红色的，逐渐过渡到最低的 doy 值，我希望它是蓝色的。

问题在于两个列表的长度逐行略有不同(因此给定行的 doy.series 和 smooth.series 列表具有相同的长度元素的数量，但元素的数量因行而异)。所以如果我尝试这样做:

library(tidyverse)

df2 <- df %>%
  unnest() 

ggplot(df2, aes(x = doy.series, y = smooth.series, color = doy, group = doy)) +
  geom_line() +
  scale_color_gradient(low = "blue", high = "red")

我收到错误:所有嵌套列必须具有相同数量的元素。

关于如何解决这个问题的任何想法？

数据样本:

df=structure(list(id = c("1", "2", "3"), doy = c(152, 158, 142), 
    smooth.series = list(c(0.356716711457841, 0.370050893258325, 
    0.383236999766461, 0.396376974233949, 0.40957275991249, 0.422784291482468, 
    0.435895856103075, 0.448895925744217, 0.461772972375802, 
    0.474515467967738, 0.48722268616777, 0.499933470515835, 0.512545647820125, 
    0.524957044888832, 0.537065488530148, 0.549189274496968, 
    0.561532939869938, 0.573823673448877, 0.5857886640336, 0.597155100423927, 
    0.608751798005646, 0.621116663488914, 0.633540522660091, 
    0.645314201305544, 0.655728525211634, 0.665571086939856, 
    0.675708836320647, 0.685551635043781, 0.694509344799033, 
    0.701991827276177, 0.70938842013153, 0.717660871422796, 0.725577658441836, 
    0.731907258480512, 0.735418148830686, 0.737609381488737, 
    0.740068708326791, 0.741697656450321, 0.741397752964802, 
    0.738070524975708, 0.730787113459408, 0.720275348839784, 
    0.707921792393576, 0.695113005397529, 0.683235549128384, 
    0.66854065601544, 0.648565682783239, 0.626626377151392, 0.606038486839507, 
    0.590117759567193, 0.575248354822936, 0.557183338977548, 
    0.538291820074129, 0.520942906155777, 0.507505705265592, 
    0.497170423227522, 0.487542218972326, 0.478612630203321, 
    0.470373194623822, 0.462815449937146, 0.458831683827816, 
    0.459466542404155, 0.461940101005184, 0.463472434969922, 
    0.461283619637389, 0.458826926942516, 0.459760482491641, 
    0.461611642130895, 0.461907761706409, 0.458176197064313, 
    0.45041527548862, 0.440794234319326, 0.430096794486539, 0.419106676920368, 
    0.408607602550923, 0.396242242656226, 0.380503346606902, 
    0.363449752471964, 0.347140298320423, 0.333633822221291, 
    0.321253095838767, 0.307606088569194, 0.293679435079791, 
    0.28045977003778, 0.268933728110384, 0.258699817638372, 0.248739536036072, 
    0.239114001581039, 0.22988433255083, 0.221111647222998, 0.213576575535607, 
    0.207511807976447, 0.202156553647666, 0.196750021651411, 
    0.19053142108983, 0.183900129705502, 0.177683584689661, 0.17176308431744, 
    0.166019926863971, 0.160335410604389, 0.153743267353215, 
    0.146014563103421, 0.138136597397814, 0.131096669779199, 
    0.125882079790385, 0.121448622919517, 0.116554575980903, 
    0.111890960506595, 0.10814879802864, 0.106019110079089, 0.105661169696536, 
    0.106498694582266, 0.108119373262358, 0.110110894262892, 
    0.11206094610995, 0.11540233539241, 0.120997725074791, 0.127579588246629, 
    0.133880397997461, 0.138632627416822, 0.143475963087052, 
    0.150098990228934, 0.157307529889666, 0.163907403116449, 
    0.168704430956481, 0.172368187413333, 0.176173416587563, 
    0.179833694671856, 0.183062597858895, 0.185573702341366, 
    0.187052218702838, 0.187638597324987, 0.187729274097655, 
    0.187720684910687, 0.188009265653923, 0.188094043051569, 
    0.187473296399738, 0.186542340446139, 0.185696489938482, 
    0.185331059624476, 0.18519846898834, 0.184852749545972, 0.184391634092598, 
    0.183912855423446, 0.183514146333744, 0.183117312589153, 
    0.182606699408324, 0.182023848765966, 0.181410302636787, 
    0.180807602995498, 0.180212334083628, 0.179591966640683, 
    0.178944372388341, 0.178267423048277, 0.177558990342169, 
    0.176816945991692, 0.176039161718523, 0.175223509244339, 
    0.174367860290815), c(0.774610362619149, 0.746412269781788, 
    0.719913789191898, 0.695420287796062, 0.673237132540861, 
    0.653273968452586, 0.635200894750251, 0.618963959669522, 
    0.604509211446066, 0.59178269831555, 0.581143108860635, 0.572741206185169, 
    0.566211150306591, 0.561187101242345, 0.557303219009872, 
    0.555232501533965, 0.555534753213423, 0.557674343776691, 
    0.561115642952215, 0.565323020468442, 0.573372729704498, 
    0.586895414376992, 0.603187029720595, 0.619543530969977, 
    0.63326087335981, 0.649100787927623, 0.670935206211495, 0.694725384196925, 
    0.716432577869408, 0.732018043214443, 0.745048344614319, 
    0.760240534670835, 0.775281601698759, 0.787858534012854, 
    0.795658319927888, 0.799986340749408, 0.803308852568436, 
    0.805054155877942, 0.804650551170897, 0.801526338940272, 
    0.794278541385548, 0.783000246619136, 0.769363854003397, 
    0.755041762900692, 0.741706372673384, 0.725475019829043, 
    0.703589930868272, 0.679410840142977, 0.656297482005064, 
    0.637609590806439, 0.619522671663228, 0.59768917697572, 0.574684262022063, 
    0.553083082080407, 0.535460792428901, 0.520724989583801, 
    0.506208924554847, 0.492126234360422, 0.478690556018906, 
    0.466115526548682, 0.456163205377972, 0.449307080301381, 
    0.443827930886861, 0.438006536702364, 0.430123677315843, 
    0.422161025148951, 0.416341337462143, 0.411307021081574, 
    0.405700482833399, 0.398164129543771, 0.388509330252805, 
    0.377833000710694, 0.366705867808713, 0.355698658438137, 
    0.34538209949024, 0.334476225402477, 0.322019919293152, 0.309062181074817, 
    0.296652010660021, 0.285838407961315, 0.276447235011443, 
    0.267512949813937, 0.258897446237528, 0.250462618150946, 
    0.242070359422922, 0.234129641095434, 0.226902750204945, 
    0.220031554611916, 0.21315792217681, 0.205923720760086, 0.19852372751621, 
    0.191343478746417, 0.184310981031329, 0.177354240951568, 
    0.170401265087756, 0.163192040497278, 0.155702671847874, 
    0.148215342135701, 0.141012234356916, 0.134375531507676, 
    0.127758694427545, 0.120727232121655, 0.113731399834516, 
    0.107221452810637, 0.101647646294526, 0.0965005694542742, 
    0.091209569652388, 0.0861330394250022, 0.0816293713082512, 
    0.0780569578382695, 0.075371315752509, 0.0732346851768886, 
    0.0715655437302434, 0.0702823690314086, 0.0693036386992192, 
    0.0691863250953481, 0.0701883842483067, 0.0717797692771877, 
    0.073430433301084, 0.0746103294390886, 0.0761784204310707, 
    0.0788956524181342, 0.0820849536212236, 0.0850692522612836, 
    0.0871714765592586, 0.0890972731947091, 0.0916871981841642, 
    0.094466543754022, 0.0969606021306803, 0.0986946655405372, 
    0.0998521594454551, 0.100914181761071, 0.101852533394445, 
    0.102639015252636, 0.103245428242704, 0.103462264899288, 
    0.103250578499722, 0.102838011065113, 0.102452204616565, 
    0.102320801175184, 0.102287042959656, 0.102088178523127, 
    0.101792859388387, 0.10146973707823, 0.101187463115447, 0.100889974984667, 
    0.100495657145597, 0.100034831583652, 0.0995378202842451, 
    0.0990349452327908, 0.0985243275768939, 0.097982837008049, 
    0.0974089183275044, 0.0968010163365085, 0.0961575758363094, 
    0.0954770416281557, 0.0947578585132956, 0.0939984712929773, 
    0.0931973247684494), c(0.754994105046569, 0.759262980856892, 
    0.763248462599852, 0.767062652758686, 0.77081765381663, 0.774472838830307, 
    0.777902459086919, 0.781090934415562, 0.784022684645335, 
    0.786682129605334, 0.789179136777192, 0.791558707699299, 
    0.793707963285894, 0.795514024451214, 0.796864012109498, 
    0.798059444416928, 0.799307737538445, 0.800354859401417, 
    0.800946777933214, 0.800829461061205, 0.800535183022801, 
    0.800489794522664, 0.800279628189041, 0.799491016650182, 
    0.797710292534332, 0.793727807721641, 0.787531875152631, 
    0.780505769046113, 0.774032763620899, 0.7694961330958, 0.766814565429895, 
    0.764644322900798, 0.76247504120512, 0.759796356039472, 0.756097903100465, 
    0.753105409945246, 0.751812834849642, 0.750612159588286, 
    0.747895365935809, 0.742054435666847, 0.734349211270437, 
    0.726724708968583, 0.718600671135361, 0.709396840144846, 
    0.698532958371117, 0.685958066059214, 0.672217339551, 0.657624725365782, 
    0.642494170022865, 0.627139620041553, 0.608952937377657, 
    0.586693889874402, 0.562728282882226, 0.539421921751564, 
    0.519140611832852, 0.498827185487661, 0.475313450129851, 
    0.450798673688293, 0.427482124091856, 0.40756306926941, 0.391594783774196, 
    0.377888811456193, 0.365281824189383, 0.352610493847746, 
    0.338711492305265, 0.324742577633052, 0.312133619351959, 
    0.300129456510569, 0.287974928157469, 0.274914873341241, 
    0.260271155053797, 0.244483391182105, 0.228473053117332, 
    0.21316161225065, 0.199470539973226, 0.18615371420193, 0.171962954821233, 
    0.157816646173702, 0.144633172601908, 0.13333091844842, 0.12330701757161, 
    0.113524600030087, 0.104251044466771, 0.0957537295245833, 
    0.0883000338464436, 0.0824702507214148, 0.0782344478172879, 
    0.0749446653450757, 0.0719529435157916, 0.0686113225404485, 
    0.0661995394292459, 0.0657367472597934, 0.0661841103442199, 
    0.0665027929946539, 0.0656539595232242, 0.0644681965998428, 
    0.0641406846621584, 0.0641794786739045, 0.0640926335988149, 
    0.0633882044006231, 0.0619833956742033, 0.0602788637336122, 
    0.058507841121357, 0.0569035603799449, 0.0556992540518834, 
    0.0546528395507013, 0.0534742168963767, 0.0523245925410911, 
    0.0513651729370255, 0.0507571645363614, 0.0504376622860656, 
    0.050241048436331, 0.0501744603941783, 0.0502450355666279, 
    0.0504599113607003, 0.0510283221178971, 0.052012828131863, 
    0.0532005557378333, 0.0543786312710432, 0.055334181066728, 
    0.0564245098836434, 0.057962991953209, 0.0596708578196554, 
    0.0612693380272137, 0.0624796631201147, 0.0635479377810315, 
    0.0648035693895804, 0.0660927425354069, 0.0672616418081562, 
    0.0681564517974736, 0.0687850088878122, 0.0692835297177245, 
    0.0696907692580061, 0.0700454824794523, 0.0703864243528584, 
    0.0706277104270338, 0.0707098566767007, 0.0707112187115236, 
    0.0707101521411668, 0.0707850125752948, 0.0708833573425856, 
    0.0709155836751044, 0.0709043070375961, 0.0708721428948058, 
    0.0708417067114787, 0.070795102344694, 0.0707055967085618, 
    0.0705825498533734, 0.0704353218294197, 0.0702732726869918, 
    0.0700959115439309, 0.0698961835839182, 0.069673602956005, 
    0.0694276838092427, 0.0691579402926828, 0.0688638865553766, 
    0.0685450367463756, 0.0682009050147312, 0.0678310055094947
    )), doy.series = list(c(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), c(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), c(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
    )), year = c("2000", "2000", "2000"), geometry = structure(list(
        structure(c(-164.047259999849, -164.044659999559, -164.044719999628, 
        -164.038089999654, -164.028189999968, -164.019179999957, 
        -164.005899999985, -164.004819999643, -164.006060000169, 
        -164.01439999986, -164.020739999951, 62.9589599997043, 
        62.9570600002189, 62.9551799998571, 62.9500200002229, 
        62.9453699998257, 62.9321099998767, 62.9228599995894, 
        62.9198900002234, 62.9182900001834, 62.9161899995689, 
        62.9119300000695), .Dim = c(11L, 2L), class = c("XY", 
        "LINESTRING", "sfg")), structure(c(-163.950299999945, 
        -163.929679999632, -163.91427000036, -163.903839999616, 
        -163.892950000142, -163.874760000374, -163.857260000049, 
        -163.83827000026, -163.831219999803, -163.826049999708, 
        -163.831939999731, -163.830590000428, -163.822, -163.815322687912, 
        62.7265500001824, 62.7286899999436, 62.7327399996513, 
        62.7292899997337, 62.7222099996918, 62.7222000001299, 
        62.7196300003243, 62.7251300003493, 62.7253400001409, 
        62.7224699999905, 62.7144400002059, 62.7114699999406, 
        62.7062799998222, 62.7052201090963), .Dim = c(14L, 2L
        ), class = c("XY", "LINESTRING", "sfg")), structure(c(-163.815322687912, 
        -163.798689999744, -163.782269999761, -163.768690000343, 
        -163.762120000438, -163.757980000177, -163.754040000146, 
        -163.750479999652, -163.741150000172, -163.731440000256, 
        -163.727959999854, -163.716170000245, -163.707080000142, 
        -163.69419999973, -163.687290000333, -163.670841577631, 
        62.7052201090963, 62.7025800000671, 62.7027099997667, 
        62.7047399998511, 62.7076500000475, 62.7154200004327, 
        62.7186199996133, 62.7195300002094, 62.718240000076, 
        62.7119499995929, 62.7111100004263, 62.7123500000526, 
        62.71900000005, 62.7184800003518, 62.7155900001783, 62.7051667771758
        ), .Dim = c(16L, 2L), class = c("XY", "LINESTRING", "sfg"
        ))), class = c("sfc_LINESTRING", "sfc"), precision = 0, bbox = structure(c(-164.047259999849, 
    62.7025800000671, -163.670841577631, 62.9589599997043), .Names = c("xmin", 
    "ymin", "xmax", "ymax"), class = "bbox"), crs = structure(list(
        epsg = 4326L, proj4string = "+proj=longlat +datum=WGS84 +no_defs"), .Names = c("epsg", 
    "proj4string"), class = "crs"), n_empty = 0L)), .Names = c("id", 
"doy", "smooth.series", "doy.series", "year", "geometry"), row.names = c(NA, 
3L), class = c("sf", "data.frame"), sf_column = "geometry", agr = structure(c(NA_integer_, 
NA_integer_, NA_integer_, NA_integer_, NA_integer_), .Names = c("id", 
"doy", "smooth.series", "doy.series", "year"), .Label = c("constant", 
"aggregate", "identity"), class = "factor"))

Answer 1

对于你给出的小例子，我只添加了select(-geometry):

library(tidyverse)

df3 <- df %>%
  select(-geometry) %>%
  unnest()

df3 %>% 
  ggplot(aes(x = doy.series, y = smooth.series, color = doy, group = doy)) +
  geom_line() +
  scale_color_gradient(low = "blue", high = "red")