使用x，y x，y协调将数据帧转换为R中的空间线数据帧 [英] Convert data frame to spatial lines data frame in R with x,y x,y coordintates

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本文介绍了使用x，y x，y协调将数据帧转换为R中的空间线数据帧的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！

问题描述

我在R中有一个数据框，其中一列包含以下形式的一行中的点的坐标：

  x，yx，yx，yx，y

所以整个数据框看起来像

  id dist speed coord 
 1 45 6 1.294832,54.610240 -1.294883,54.610080 -1.294262,54.6482757 
 2 23 34 2.788732 ，34.787940 6.294883,24.567080 -5.564262，-45.7676757

我想将其转换为空间线数据框架，我假设第一步是将坐标分为两列：

  x，x， x，x 
y，y，y，y

但我不确定如何继续。



编辑



对于那些请求它的实际文件的输入

 > finalsub<  -  final [final $ rid< 3，] 
> dput（finalsub）
结构（list（rid = c（1,2），start_id = c（1L，1L），start_code = c（E02002536，
E02002536），end_id = c （106L，106L），end_code = c（E02006909，
E02006909），strategy = c（fastest，quietest），distance = c（12655L，
 12909L），time_seconds = c（2921L，3422L），卡路里= c（211L，201L 
），document.id = c（1L，1L），array.index = 1：2，start = c（Geranium Close b $ bGeranium Close），finish = c（Hylton Road，Hylton Road），
 startBearing = c（0,0），startSpeed = c（0,0），start_longitude = c -1.294832，
 -1.294832），start_latitude = c（54.610241,54.610241），finish_longitude = c（-1.249478，
 -1.249478），finish_latitude = c（54.680691,54.680691），crow_fly_distance = c（8362， 
 8362），event = c（出发，离开），whence = c（1473171787，
 1473171787），speed = c（20,20），行程= c（419956,419957 
），clientRouteId = c（0,0），plan = c（fastest，quietest
），note = c（，），length = c（12655， 12909），time = c（2921，
 3422），busynance = c（42172,17242），quietness = c（30,75），
 signalledJunctions = c（3,4），signalledCrossings = c （2,0 
），西= c（-1.300074，-1.294883），南= c（54.610006，54.609851 
），东= c（-1.232447，-1.232447），北= c（54.683814 ，54.683814 
），name = c（Geranium Close to Hylton Road，Geranium Close to Hylton Road
），walk = c（0，0），leave = c -06 15:23:07，2016-09-06 15:23:07
），arrival = c（2016-09-06 16:11:48，2016-09-06 16:20:09
），coordinates = c（ -  1.294832,54.610240 -1.294883,54.610080 -1.294262,54.610016 -1.294141,54.610006 -1.293710,54.610038 -1.293726,54.610142 -1.293742,54.610247 -1.293510,54.610262  - 1.293368,54.610258 -1.292816,54.610195 -1.292489,54.610152 -1.292298,54.610667 -1.292205,54.610951 -1.292182,54.611063 -1.292183,54.611153 -1.292239,54.611341 -1.292305,54.611447 -1.292375,54.611534 -1.292494,54.611639 -1.292739,54.611830 -1.292909， 54.611980 -1.293010,54.612107 -1.293111,54.612262 -1.293192,54.612423 -1.293235,54.612546 -1.293267,54.612684 -1.293279,54.612818 -1.293510,54.612813 -1.293732,54.612790 -1.294324,54.612691 -1.295086,54.612568 -1.295313,54.612539 -1.295379,54.612543 -1.295889 ，54.612645 -1.295945,54.612648 -1.296006,54.612642 -1.297154,54.612414 -1.297502,54.612895 -1.297733,54.612847 -1.297990,54.612796 -1.298292,54.612747 -1.298515,54.612727 -1.299088,54.612681 -1.299564,54.612669 -1.299798,54.612663 -1.299798,54.612663 -1.300006,54.612660 -1.300057,54.612809 -1.300056,54.613335 -1.300071,54.613693 -1.300074,54.614044 -1.300042,54.614482 -1.300015,54.614786 -1.299947,54.615220 -1.299907,54.615394 -1.299854,54.615644 -1.299730,54.616048 -1.299495,54.616700 -1.299196,54.617347 -1.298236 ，54.619313 -1.298010,54.619762 -1.297703,54.620418 -1.297520,54.620831 -1.297169,54.621690 -1.297061,54.621981 -1.296416,54.623873 -1.296310,54.624308 -1.296225,54.624888 -1.296215,54.625286 -1.296220,54.625546 -1.296241,54.625803 -1.296268,54.625913 -1.296323,54.626011 -1.296397,54.626096 -1.296540,54.626190 -1.296719,54.626323 -1.296893,54.626433 -1.297042,54.626589 -1.297111,54.626710 -1.297122,54.626825 -1.297110,54.626948 -1.297058,54.627052 -1.296961,54.627172 -1.296861,54.627258 -1.296760 ，54.627325 -1.296603,54.627397 -1.296491,54.627438 -1.296338,54.627472 -1.296154,54.627496 -1.295966,54.627513 -1.295746,54.627526 -1.295618,54.627522 -1.295421,54.627510 -1.295197,54.627466 -1.295102,54.627436 -1.294832,54.627376 -1.294665,54.627355 -1.294502,54.627350 -1.294331,54.627366 -1.294014,54.627415 -1.293557,54.627499 -1.293001,54.627611 -1.292613,54.627701 -1.291836,54.627902 -1.291248,54.628076 -1.290635,54.628269 -1.290142,54.628446 -1.289621,54.628649 -1.289031,54.628903 -1.288538 ，54.629137 -1.288132,54.629350 -1.287681,54.629604 -1.287262,54.629862 -1.286866,54.630124 -1.286103,54.630643 -1.285748,54.630868 -1.285396,54.631082 -1.284974,54.631322 -1.284541,54.631540 -1.284101,54.631752 -1.283390,54.632048 -1.282592,54.632385 -1.282161,54.632566 -1.281762,54.632734 -1.281111,54.633011 -1.280519,54.633274 -1.280009,54.633501 -1.279834,54.633579 -1.279392,54.633781 -1.278434,54.634210 -1.277896,54.634457 -1.276936,54.634898 -1.276210,54.635223 -1.275594,54.635485 -1.274596 ，54.635891 -1.273929,54.636180 -1.273392,54.636428 -1.272814,54.636726 -1.271627,54.637353 -1.271084,54.637605 -1.270550,54.637825 -1.269916,54.638054 -1.269389,54.638222 -1.268821,54.638383 -1.268165,54.638555 -1.265953,54.639131 -1.263766,54.639693 -1.262790,54.639953 -1.262005,54.640154 -1.261340,54.640329 -1.260658,54.640532 -1.260123,54.640712 -1.259489,54.640957 -1.258639,54.641312 -1.258010,54.641554 -1.257141,54.641861 -1.255996,54.642247 -1.254429,54.642787 -1.253524,54.643099 -1.252790 ，54.643343 -1.251636,54.643727 -1.250900,54.643982 -1.250258,54.644219 -1.249668,54.644419 -1.249123,54.644623 -1.248778,54.644762 -1.246709,54.645642 -1.244773,54.646492 -1.244140,54.646746 -1.243551,54.646973 -1.242738,54.647233 -1.242353,54.647360 -1.241810,54.647503 -1.241182,54.647642 -1.240373,54.647780 -1.239950,54.647854 -1.239961,54.647890 -1.239435,54.647967 -1.239583,54.649724 -1.239343,54.649878 -1.239011,54.650011 -1.237692,54.650177 -1.236610,54.650296 -1.236417,54.650323 -1.236257 ，54.650351 -1.236015,54.650414 -1.235833,54.650469 -1.235081,54.650723 -1.234846,54.650805 -1.234312,54.650977 -1.234094,54.651025 -1.233980,54.651044 -1.233308,54.651137 -1.233173,54.651160 -1.233063,54.651200 -1.232967,54.651252 -1.232849,54.651347 -1.232814,54.651423 -1.232810,54.651495 -1.232823,54.651569 -1.232840,54.651893 -1.232827,54.652010 -1.232504,54.653177 -1.232447,54.653500 -1.232451,54.653723 -1.232474,54.653943 -1.232535,54.654301 -1.232590,54.654635 -1.232903,54.654627 -1.232948 ，54.655599 -1.232982,54.656334 -1.232795,54.656365 -1.233131,54.658020 -1.233336,54.658428 -1.233507,54.658699 -1.233592,54.658803 -1.234197,54.659389 -1.234690,54.659825 -1.234979,54.660119 -1.235153,54.660314 -1.235343,54.660572 -1.235566,54.661037 -1.235656,54.661355 -1.235690,54.661638 -1.235677,54.661902 -1.235677,54.661984 -1.235683,54.663215 -1.235656,54.663632 -1.235639,54.664273 -1.235613,54.664639 -1.235593,54.664822 -1.235566,54.664957 -1.235508,54.665951 -1.235197,54.667327 -1.235120 ，54.668542 -1.235100,54.668897 -1.235199,54.669535 -1.235358,54.670231 -1.235437,54.670482 -1.235756,54.671241 -1.236144,54.672181 -1.236375,54.672971 -1.236309,54.673562 -1.236286,54.673704 -1.236127,54.674365 -1.235918,54.675272 -1.235827,54.675620 -1.235749,54.675960 -1.235735,54.676152 -1.235740,54.676328 -1.235754,54.676598 -1.235770,54.676987 -1.235771,54.677013 -1.235793,54.677480 -1.235758,54.677760 -1.235607,54.678134 -1.235470,54.678420 -1.235167,54.678875 -1.234263,54.679929 -1.234207 ，54.680065 -1.234175,54.680201 -1.234204,54.680465 -1.234300,54.681119 -1.234362,54.681549 -1.234427,54.681771 -1.234560,54.682172 -1.234782,54.682824 -1.236530,54.682837 -1.236725,54.682829 -1.237133,54.682813 -1.238813,54.683143 -1.241021,54.683814 -1.241819,54.683771 -1.242854,54.683717 -1.242946,54.683718 -1.243082,54.683716 -1.244694,54.683772 -1.244658,54.683077 -1.245038,54.682805 -1.245047,54.681990 -1.245011,54.681238 -1.245220,54.680975 -1.247056,54.680601 -1.248019,54.680404 -1.249478 ，54.680691，
-1.294832,54.610240 -1.294883,54.610080 -1.294262,54.610016 -1.294141,54.610006 -1.293710,54.610038 -1.293726,54.610142 -1.293742,54.610247 -1.293510,54.610262 -1.293368,54.610258 -1.292816,54.610195  - 1.292489,54.610152 -1.292298,54.610667 -1.292167,54.610651 -1.291371,54.610562 -1.291240,54.610556 -1.291107,54.610564 -1.290983,54.610581-1.290467,54.610665 -1.290253,54.610690 -1.290017,54.610689 -1.289770,54.610665 -1.289500,54.610620 -1.289281， 54.610570 -1.289124,54.610514 -1.288957,54.610440 -1.288611,54.610277 -1.288420,54.610222 -1.287445,54.610110 -1.287259,54.610664 -1.286758,54.610611 -1.285446,54.610462 -1.285308,54.610459 -1.283356,54.610475 -1.283159,54.610475 -1.283156,54.610324  - 1.283153,54.610119 -1.2828 18,54.610118 -1.282560,54.610114 -1.282110,54.610131 -1.281962,54.610153 -1.281788,54.610200 -1.281639,54.610257 -1.281298,54.609964 -1.281196,54.609851 -1.280586,54.610008 -1.280272,54.610054 -1.279816,54.610091 -1.279480,54.610104 -1.279112， 54.610121 -1.278953,54.610146 -1.278815,54.610183 -1.278669,54.610225 -1.278524,54.610279 -1.278428,54.610326 -1.278327,54.610377 -1.278042,54.610237 -1.277946,54.610211 -1.277849,54.610204 -1.277454,54.610206 -1.277268,54.610211 -1.276621,54.610222  - 1.276217,54.610233 -1.276085,54.610240 -1.275571,54.610315 -1.275426,54.610347 -1.275334,54.610373 -1.275248,54.610417 -1.275204,54.610477 -1.275066,54.610765 -1.274836,54.611248 -1.274811,54.611349 -1.274833,54.6113414 -1.274925,54.611607 -1.274953， 54.611664 -1.274669,54.611698 -1.272541,54.610433 -1.271290,54.610716 -1.270069,54.611677 -1.269365,54.611847 -1.268450,54.612165 -1.267142,54.612923 -1.266539,54.613386 -1.265920,54.614177 -1.265663,54.614259 -1.264195,54.616131 -1.263730,54.616670  - 1.2636 65,54.616739 -1.263407,54.617051 -1.262407,54.618192 -1.262185,54.618424 -1.262077,54.618537 -1.261506,54.619136 -1.261394,54.619342 -1.261507,54.619520 -1.261799,54.620013 -1.261791,54.620138 -1.261695,54.620233 -1.261342,54.620279 -1.261237， 54.620334 -1.261175,54.620442 -1.261128,54.620493 -1.260857,54.620616 -1.260783,54.620697 -1.260729,54.620807 -1.260729,54.620942 -1.260677,54.621042 -1.260600,54.621109 -1.260457,54.621250 -1.260409,54.621298 -1.260364,54.621336 -1.260140,54.621409  - 1.260052,54.621475 -1.259959,54.621607 -1.259881,54.621722 -1.259603,54.622326 -1.259445,54.622670 -1.259349,54.623096 -1.259359,54.623266 -1.259490,54.623825 -1.259497,54.623856 -1.259882,54.624563 -1.259894,54.624684 -1.259646,54.624993 -1.259529， 54.625176 -1.259093,54.625999 -1.258939,54.626244 -1.258780,54.626429 -1.258157,54.626772 -1.257604,54.627106 -1.256140,54.627787 -1.255933,54.627903 -1.255874,54.627953 -1.255754,54.628092 -1.255576,54.628504 -1.255534,54.628645 -1.255601,54.629176  - 1.2555 72,54.629415 -1.255265,54.630017 -1.255104,54.630209 -1.254200,54.630725 -1.254084,54.630831 -1.254037,54.630915 -1.254018,54.631129 -1.254128,54.631712 -1.254107,54.631961 -1.253979,54.632187 -1.253594,54.632613 -1.253530,54.632749 -1.253501， 54.632882 -1.253404,54.633827 -1.253482,54.634447 -1.253483,54.634654 -1.253445,54.634902 -1.253389,54.635040 -1.253275,54.635186 -1.252555,54.635902 -1.252473,54.636063 -1.252330,54.636859 -1.252273,54.637015 -1.252176,54.637175 -1.251977,54.637365  - 1.251763,54.637507 -1.251314,54.637755 -1.250800,54.638114 -1.250487,54.638358 -1.250153,54.638709 -1.249968,54.638840 -1.249562,54.639001 -1.248455,54.639365 -1.248124,54.639494 -1.247386,54.639821 -1.246797,54.640013 -1.246610,54.640098 -1.246513， 54.640170 -1.246574,54.640279 -1.247014,54.640580 -1.247341,54.641088 -1.247564,54.641365 -1.248256,54.642661 -1.248319,54.642919 -1.247650,54.643048 -1.246829,54.643234 -1.245867,54.643306 -1.245202,54.643286 -1.243595,54.643087 -1.243282,54.643073  - 1.2429 62,54.643076 -1.242041,54.643065 -1.241790,54.643031 -1.241369,54.642888 -1.240421,54.642544 -1.240237,54.642499 -1.240075,54.642497 -1.239926,54.642545 -1.239858,54.642627 -1.239837,54.642696 -1.239909,54.642989 -1.239960,54.643498 -1.239964， 54.643532 -1.239983,54.644175 -1.239936,54.644470 -1.239883,54.644807 -1.239842,54.645116 -1.239825,54.645489 -1.239748,54.646014 -1.239733,54.646299 -1.239798,54.646734 -1.239789,54.646896 -1.239705,54.647229 -1.239683,54.647331 -1.239608,54.647496  - 1.239566,54.647621 -1.239562,54.647760 -1.239618,54.647903 -1.239421,54.647932 -1.239435,54.647967 -1.239583,54.649724 -1.239343,54.649878 -1.239011,54.650011 -1.237692,54.650177 -1.236610,54.650296 -1.236417,54.650323 -1.236257,54.650351 -1.236015， 54.650414 -1.235833,54.650469 -1.235081,54.650723 -1.234846,54.650805 -1.234312,54.650977 -1.234094,54.651025 -1.233980,54.651044 -1.233308,54.651137 -1.233173,54.651160 -1.233063,54.651200 -1.232967,54.651252 -1.232849,54.651347 -1.232814,54.651423  - 1.2328 10,54.651495 -1.232823,54.651569 -1.232840,54.651893 -1.232827,54.652010 -1.232504,54.653177 -1.232447,54.653500 -1.232451,54.653723 -1.232474,54.653943 -1.232535,54.654301 -1.232590,54.654635 -1.232619,54.654960 -1.232723,54.655606 -1.232795， 54.656365 -1.233131,54.658020 -1.233336,54.658428 -1.233507,54.658699 -1.233592,54.658803 -1.234197,54.659389 -1.234690,54.659825 -1.234979,54.660119 -1.235153,54.660314 -1.235343,54.660572 -1.235566,54.661037 -1.235656,54.661355 -1.235690,54.661638  - 1.235677,54.661902 -1.235677,54.661984 -1.235683,54.663215 -1.235656,54.663632 -1.235639,54.664273 -1.235613,54.664639 -1.235593,54.664822 -1.235566,54.664957 -1.235508,54.665351 -1.235197,54.667327 -1.235120,54.668542 -1.235100,54.668897 -1.235199， 54.669535 -1.235358,54.670231 -1.235437,54.670482 -1.235756,54.671241 -1.236144,54.672181 -1.236375,54.672971 -1.236309,54.673562 -1.236286,54.673704 -1.236127,54.674365 -1.235918,54.675272 -1.235827,54.675620 -1.235749,54.675960 -1.235735,54.676152  - 1.2357 40,54.676328 -1.235754,54.676598 -1.235770,54.676987 -1.235771,54.677013 -1.235793,54.677480 -1.235758,54.677760 -1.235607,54.678134 -1.235470,54.678420 -1.235167,54.678875 -1.234263,54.679929 -1.234207,54.680065 -1.234175,54.680201 -1.234204， 54.680465 -1.234300,54.681119 -1.234362,54.681549 -1.234427,54.681771 -1.234560,54.682172 -1.234782,54.682824 -1.236530,54.682837 -1.236725,54.682829 -1.237133,54.682813 -1.238813,54.683143 -1.241021,54.683814 -1.241819,54.683771 -1.242854,54.683717  - 1.242946,54.683718 -1.243082,54.683716 -1.244694,54.683772 -1.244658,54.683077 -1.245038,54.682805 -1.245047,54.681990 -1.245011,54.681238 -1.245220,54.680975 -1.247056,54.680601 -1.248019,54.680401 -1.249478,54.680691
）， grammesCO2saved = c（2359,2406），卡路里= c（211,201 
），type = c（route，route）），.Names = c（rid，start_id，
start_code，end_id，end_code，策略，距离，time_seconds，
卡路里，document.id，array.index ，完成， 
startBearing，startSpeed，start_longitude，start_latitude，
finish_longitude，finish_latitude，crow_fly_distance，event，
whence 行程，客户端，计划，笔记，
长度，时间，busynance，安静，signalledJunctions，
signalledCrossings 西，南，东，北，名，
步行，离开，到达，坐标，grammesCO2saved，
 ，type），row.names = 1：2，class =data.frame）
>


解决方案

我相信你想要的结果是您的数据框中的每列的列是具有 x.coord 和 y.coord 列。为了达到这个目的，我们可以使用 unsest 和 nest 从 tidyr 与 dplyr ：

 库（dplyr）
库（tidyr）
 result<  -  finalsub％>％mutate（coordinates = strsplit（coordinates，split =，fixed = TRUE））％>％
 unnest（coordinates）％>％ 
 mutate（coordinates = strsplit（coordinates，split =，，fixed = TRUE），
 x.coord = as.numeric（unlist（coordinates）[c（TRUE，FALSE）]），
 y.coord = as.numeric（unlist（coordinates）[c（FALSE，TRUE）]））％>％
 select（-coordinates）％>％
 nest（x。 coord，y.coord，.key = coordinates）

注意：


  1. 第一个 mutate 将您的坐标中的字符向量拆分列由分隔每个坐标 x，y 导致一个列表这些。

  2. unnest 将此列表分成行。 >
  3. 在第二个 mutate 中，我们首先将每个坐标 x，y 通过，将每个坐标分隔成 x 和 y 。然后，我们创建单独的 x.coord 和 y.coord 列来保存这些。注意在这里转换为数字。

  4. 最后，我们使用 nest 来收集 x.coord 和 y.coord 列作为名为坐标的列表。请注意，我们首先必须删除原始的坐标列。

结果使用 dput 数据，仅打印坐标列：

  print（result $ coordinates）
 ## [[1]] 
 ###一个字符串：284 x 2 
 ## x.coord y.coord 
 ##< dbl> < db1> 
 ## 1 -1.294832 54.61024 
 ## 2 -1.294883 54.61008 
 ## 3 -1.294262 54.61002 
 ## 4 -1.294141 54.61001 
 ## 5 -1.293710 54.61004 
 ## 6 -1.293726 54.61014 
 ## 7 -1.293742 54.61025 
 ## 8 -1.293510 54.61026 
 ## 9 -1.293368 54.61026 
 ## 10 -1.292816 54.61019 
 ### ...与另外274行
 ## 
 ## [[2]] 
 ###一个字符串：322 x 2 
 ## x.coord y.coord 
 ##< dbl> < db1> 
 ## 1 -1.294832 54.61024 
 ## 2 -1.294883 54.61008 
 ## 3 -1.294262 54.61002 
 ## 4 -1.294141 54.61001 
 ## 5 -1.293710 54.61004 
 ## 6 -1.293726 54.61014 
 ## 7 -1.293742 54.61025 
 ## 8 -1.293510 54.61026 
 ## 9 -1.293368 54.61026 
 ## 10 -1.292816 54.61019 
 ### ...再添加312行


I have a data frame in R, one of the columns contains the coordinates for points along a line in the form:

x,y x,y x,y x,y

So the whole data frame looks like

id dist speed coord
1  45   6     1.294832,54.610240 -1.294883,54.610080 -1.294262,54.6482757
2  23   34    2.788732,34.787940 6.294883,24.567080 -5.564262,-45.7676757

I would like to convert this to a spatial lines data frame, and I assume that the fist step would be to separate the coordinates into two columns in the from:

x, x, x, x
y, y, y, y

But I am unsure how to proceed.

EDIT

For those requesting it a dput of the actual file

> finalsub <- final[final$rid <3,]
> dput(finalsub)
structure(list(rid = c(1, 2), start_id = c(1L, 1L), start_code = c("E02002536", 
"E02002536"), end_id = c(106L, 106L), end_code = c("E02006909", 
"E02006909"), strategy = c("fastest", "quietest"), distance = c(12655L, 
12909L), time_seconds = c(2921L, 3422L), calories = c(211L, 201L
), document.id = c(1L, 1L), array.index = 1:2, start = c("Geranium Close", 
"Geranium Close"), finish = c("Hylton Road", "Hylton Road"), 
    startBearing = c(0, 0), startSpeed = c(0, 0), start_longitude = c(-1.294832, 
    -1.294832), start_latitude = c(54.610241, 54.610241), finish_longitude = c(-1.249478, 
    -1.249478), finish_latitude = c(54.680691, 54.680691), crow_fly_distance = c(8362, 
    8362), event = c("depart", "depart"), whence = c(1473171787, 
    1473171787), speed = c(20, 20), itinerary = c(419956, 419957
    ), clientRouteId = c(0, 0), plan = c("fastest", "quietest"
    ), note = c("", ""), length = c(12655, 12909), time = c(2921, 
    3422), busynance = c(42172, 17242), quietness = c(30, 75), 
    signalledJunctions = c(3, 4), signalledCrossings = c(2, 0
    ), west = c(-1.300074, -1.294883), south = c(54.610006, 54.609851
    ), east = c(-1.232447, -1.232447), north = c(54.683814, 54.683814
    ), name = c("Geranium Close to Hylton Road", "Geranium Close to Hylton Road"
    ), walk = c(0, 0), leaving = c("2016-09-06 15:23:07", "2016-09-06 15:23:07"
    ), arriving = c("2016-09-06 16:11:48", "2016-09-06 16:20:09"
    ), coordinates = c("-1.294832,54.610240 -1.294883,54.610080 -1.294262,54.610016 -1.294141,54.610006 -1.293710,54.610038 -1.293726,54.610142 -1.293742,54.610247 -1.293510,54.610262 -1.293368,54.610258 -1.292816,54.610195 -1.292489,54.610152 -1.292298,54.610667 -1.292205,54.610951 -1.292182,54.611063 -1.292183,54.611153 -1.292239,54.611341 -1.292305,54.611447 -1.292375,54.611534 -1.292494,54.611639 -1.292739,54.611830 -1.292909,54.611980 -1.293010,54.612107 -1.293111,54.612262 -1.293192,54.612423 -1.293235,54.612546 -1.293267,54.612684 -1.293279,54.612818 -1.293510,54.612813 -1.293732,54.612790 -1.294324,54.612691 -1.295086,54.612568 -1.295313,54.612539 -1.295379,54.612543 -1.295889,54.612645 -1.295945,54.612648 -1.296006,54.612642 -1.297154,54.612414 -1.297502,54.612895 -1.297733,54.612847 -1.297990,54.612796 -1.298292,54.612747 -1.298515,54.612727 -1.299088,54.612681 -1.299564,54.612669 -1.299798,54.612663 -1.300006,54.612660 -1.300057,54.612809 -1.300056,54.613335 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-1.233131,54.658020 -1.233336,54.658428 -1.233507,54.658699 -1.233592,54.658803 -1.234197,54.659389 -1.234690,54.659825 -1.234979,54.660119 -1.235153,54.660314 -1.235343,54.660572 -1.235566,54.661037 -1.235656,54.661355 -1.235690,54.661638 -1.235677,54.661902 -1.235677,54.661984 -1.235683,54.663215 -1.235656,54.663632 -1.235639,54.664273 -1.235613,54.664639 -1.235593,54.664822 -1.235566,54.664957 -1.235508,54.665351 -1.235197,54.667327 -1.235120,54.668542 -1.235100,54.668897 -1.235199,54.669535 -1.235358,54.670231 -1.235437,54.670482 -1.235756,54.671241 -1.236144,54.672181 -1.236375,54.672971 -1.236309,54.673562 -1.236286,54.673704 -1.236127,54.674365 -1.235918,54.675272 -1.235827,54.675620 -1.235749,54.675960 -1.235735,54.676152 -1.235740,54.676328 -1.235754,54.676598 -1.235770,54.676987 -1.235771,54.677013 -1.235793,54.677480 -1.235758,54.677760 -1.235607,54.678134 -1.235470,54.678420 -1.235167,54.678875 -1.234263,54.679929 -1.234207,54.680065 -1.234175,54.680201 -1.234204,54.680465 -1.234300,54.681119 -1.234362,54.681549 -1.234427,54.681771 -1.234560,54.682172 -1.234782,54.682824 -1.236530,54.682837 -1.236725,54.682829 -1.237133,54.682813 -1.238813,54.683143 -1.241021,54.683814 -1.241819,54.683771 -1.242854,54.683717 -1.242946,54.683718 -1.243082,54.683716 -1.244694,54.683772 -1.244658,54.683077 -1.245038,54.682805 -1.245047,54.681990 -1.245011,54.681238 -1.245220,54.680975 -1.247056,54.680601 -1.248019,54.680404 -1.249478,54.680691"
    ), grammesCO2saved = c(2359, 2406), calories = c(211, 201
    ), type = c("route", "route")), .Names = c("rid", "start_id", 
"start_code", "end_id", "end_code", "strategy", "distance", "time_seconds", 
"calories", "document.id", "array.index", "start", "finish", 
"startBearing", "startSpeed", "start_longitude", "start_latitude", 
"finish_longitude", "finish_latitude", "crow_fly_distance", "event", 
"whence", "speed", "itinerary", "clientRouteId", "plan", "note", 
"length", "time", "busynance", "quietness", "signalledJunctions", 
"signalledCrossings", "west", "south", "east", "north", "name", 
"walk", "leaving", "arriving", "coordinates", "grammesCO2saved", 
"calories", "type"), row.names = 1:2, class = "data.frame")
>

解决方案

I believe what you want to end up with is a column in your data frame that for each row is a list (or data frame) with x.coord and y.coord columns. To achieve that, we can use unnest and nest from tidyr with dplyr:

library(dplyr)
library(tidyr)
result <- finalsub %>% mutate(coordinates = strsplit(coordinates,split=" ",fixed=TRUE)) %>%
                       unnest(coordinates) %>%
                       mutate(coordinates = strsplit(coordinates,split=",",fixed=TRUE),
                              x.coord = as.numeric(unlist(coordinates)[c(TRUE,FALSE)]),
                              y.coord = as.numeric(unlist(coordinates)[c(FALSE,TRUE)])) %>%
                       select(-coordinates) %>%
                       nest(x.coord,y.coord,.key=coordinates)

Notes:

  1. The first mutate splits the character vector in your coordinates column by " " to separate each coordinate x,y resulting in a list of these.
  2. unnest separates this list into rows.
  3. In the second mutate, we first split each coordinate x,y, this time by "," to separate each coordinate into x and y. Then we create separate x.coord and y.coord columns to hold these. Note the conversion to numeric here.
  4. Finally, we use nest to collect the x.coord and y.coord columns as a list under the column named coordinates. Note that we first have to remove the original coordinates column.

The result using your dput data, printing only the coordinates column:

print(result$coordinates)
##[[1]]
### A tibble: 284 x 2
##     x.coord  y.coord
##       <dbl>    <dbl>
##1  -1.294832 54.61024
##2  -1.294883 54.61008
##3  -1.294262 54.61002
##4  -1.294141 54.61001
##5  -1.293710 54.61004
##6  -1.293726 54.61014
##7  -1.293742 54.61025
##8  -1.293510 54.61026
##9  -1.293368 54.61026
##10 -1.292816 54.61019
### ... with 274 more rows
##
##[[2]]
### A tibble: 322 x 2
##     x.coord  y.coord
##       <dbl>    <dbl>
##1  -1.294832 54.61024
##2  -1.294883 54.61008
##3  -1.294262 54.61002
##4  -1.294141 54.61001
##5  -1.293710 54.61004
##6  -1.293726 54.61014
##7  -1.293742 54.61025
##8  -1.293510 54.61026
##9  -1.293368 54.61026
##10 -1.292816 54.61019
### ... with 312 more rows

这篇关于使用x，y x，y协调将数据帧转换为R中的空间线数据帧的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！

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