如何解决将多边形列表堆叠到单个数据框中
我有一个相对于每年的 polygons 列表，但是，我希望将它们转换，然后将它们相对于各自的列按行堆叠成一个 dataframe。
我尝试过 as.data.frame(test.all)，其中 test.all 是多边形列表，虽然它返回一个 dataframe，但它仍然具有多边形特征。我更喜欢带有相对于多边形中列名的列，其中 geometry 分别转换为 X 和 Y，删除所有 polygon 类特征。
我已将多边形尽可能缩小，如下所示：
[[1]]
Simple feature collection with 1 feature and 2 fields
geometry type: polyGON
dimension: XY
bBox: xmin: -8775709 ymin: 4572981 xmax: -8773389 ymax: 4575301
CRS: +proj=sinu +lon_0=0 +x_0=0 +y_0=0 +R=6371007.181 +units=m +no_defs
# A tibble: 1 x 3
year observation_count geometry
<chr> <dbl> <polyGON [m]>
1 2010 0 ((-8773389 4574141,-8773391 4574081,-8773396 45~
[[2]]
Simple feature collection with 1 feature and 2 fields
geometry type: polyGON
dimension: XY
bBox: xmin: -7216455 ymin: 4013155 xmax: -7214135 ymax: 4015475
CRS: +proj=sinu +lon_0=0 +x_0=0 +y_0=0 +R=6371007.181 +units=m +no_defs
# A tibble: 1 x 3
year observation_count geometry
<chr> <dbl> <polyGON [m]>
1 2011 0 ((-7214135 4014315,-7214137 4014254,-7214142 40~
预期输出：
year observation_count X Y
2010 0 -8773389 4574141
2011 0 -7214135 4014315
. . . .
. . . .
我也尝试将多边形转换为 spatialpolygon，然后通过 raster::geom(test.all.sp) 获取几何图形，但是，这只返回几何点而不是其他列值。
以下是上述功能的可重现代码，您必须先加载 library(sf)：
#install.packages("sf")
library(sf)
test.all <- list(structure(list(year = "2010",locality_id = "L2228604",observation_count = 0,geometry = structure(list(structure(list(
structure(c(-8773389.28986396,-8773390.87960364,-8773395.64446533,-8773403.57138886,-8773414.6386471,-8773428.81590546,-8773446.06430505,-8773466.33656922,-8773489.57713309,-8773515.7222959,-8773544.70039557,-8773576.43200514,-8773610.83015048,-8773647.80054867,-8773687.2418664,-8773729.04599778,-8773773.09836058,-8773819.27821034,-8773867.4589713,-8773917.50858334,-8773969.28986396,-8774022.66088426,-8774077.47535799,-8774133.58304248,-8774190.83015048,-8774249.05977164,-8774308.11230261,-8774367.82588451,-8774428.03684657,-8774488.58015471,-8774549.28986396,-8774609.9995732,-8774670.54288135,-8774730.7538434,-8774790.4674253,-8774849.51995627,-8774907.74957743,-8774964.99668543,-8775021.10436992,-8775075.91884365,-8775129.28986396,-8775181.07114457,-8775231.12075661,-8775279.30151757,-8775325.48136733,-8775369.53373013,-8775411.33786151,-8775450.77917925,-8775487.74957743,-8775522.14772277,-8775553.87933234,-8775582.85743201,-8775609.00259482,-8775632.24315869,-8775652.51542286,-8775669.76382245,-8775683.94108081,-8775695.00833905,-8775702.93526258,-8775707.70012427,-8775709.28986396,-8773389.28986396,4574141.40786374,4574080.6981545,4574020.15484635,4573959.94388429,4573900.23030239,4573841.17777142,4573782.94815026,4573725.70104226,4573669.59335777,4573614.77888404,4573561.40786374,4573509.62658312,4573459.57697108,4573411.39621012,4573365.21636036,4573321.16399756,4573279.35986618,4573239.91854845,4573202.94815026,4573168.55000492,4573136.81839535,4573107.84029568,4573081.69513287,4573058.454569,4573038.18230483,4573020.93390524,4573006.75664689,4572995.68938865,4572987.76246511,4572982.99760342,4572981.40786374,4574202.11757298,4574262.66088113,4574322.87184318,4574382.58542509,4574441.63795606,4574499.86757721,4574557.11468521,4574613.22236971,4574668.03684343,4574721.40786374,4574773.18914435,4574823.2387564,4574871.41951736,4574917.59936711,4574961.65172991,4575003.45586129,4575042.89717903,4575079.86757721,4575114.26572255,4575145.99733213,4575174.9754318,4575201.1205946,4575224.36115847,4575244.63342264,4575261.88182223,4575276.05908059,4575287.12633883,4575295.05326236,4575299.81812405,4575301.40786374,4574141.40786374),.Dim = c(121L,2L
))),class = c("XY","polyGON","sfg"))),class = c("sfc_polyGON","sfc"),precision = 0,bBox = structure(c(xmin = -8775709.28986396,ymin = 4572981.40786374,xmax = -8773389.28986396,ymax = 4575301.40786374
),class = "bBox"),crs = structure(list(input = "+proj=sinu +lon_0=0 +x_0=0 +y_0=0 +R=6371007.181 +units=m +no_defs",wkt = "PROJCRS[\"unkNown\",\n BASEGEOGCRS[\"unkNown\",\n DATUM[\"unkNown\",\n ELLIPSOID[\"unkNown\",6371007.181,\n LENGTHUNIT[\"metre\",1,\n ID[\"epsg\",9001]]]],\n PRIMEM[\"Greenwich\",\n ANGLEUNIT[\"degree\",0.0174532925199433],\n ID[\"epsg\",8901]]],\n CONVERSION[\"unkNown\",\n METHOD[\"Sinusoidal\"],\n ParaMETER[\"Longitude of natural origin\",8802]],\n ParaMETER[\"False easting\",\n LENGTHUNIT[\"metre\",1],8806]],\n ParaMETER[\"False northing\",8807]]],\n CS[Cartesian,2],\n AXIS[\"(E)\",east,\n ORDER[1],\n ID[\"epsg\",9001]]],\n AXIS[\"(N)\",north,\n ORDER[2],9001]]]]"),class = "crs"),n_empty = 0L)),sf_column = "geometry",agr = structure(c(year = NA_integer_,locality_id = NA_integer_,observation_count = NA_integer_),class = "factor",.Label = c("constant","aggregate","identity")),row.names = c(NA,-1L),class = c("sf","tbl_df","tbl","data.frame")),structure(list(year = "2011",locality_id = "L1472874",geometry = structure(list(
structure(list(structure(c(-7214135.48475349,-7214137.07449317,-7214141.83935486,-7214149.7662784,-7214160.83353664,-7214175.01079499,-7214192.25919458,-7214212.53145875,-7214235.77202262,-7214261.91718543,-7214290.8952851,-7214322.62689467,-7214357.02504001,-7214393.9954382,-7214433.43675593,-7214475.24088731,-7214519.29325011,-7214565.47309987,-7214613.65386083,-7214663.70347287,-7214715.48475349,-7214768.85577379,-7214823.67024752,-7214879.77793201,-7214937.02504001,-7214995.25466117,-7215054.30719214,-7215114.02077404,-7215174.2317361,-7215234.77504424,-7215295.48475349,-7215356.19446273,-7215416.73777088,-7215476.94873293,-7215536.66231484,-7215595.71484581,-7215653.94446696,-7215711.19157496,-7215767.29925945,-7215822.11373318,-7215875.48475349,-7215927.2660341,-7215977.31564615,-7216025.4964071,-7216071.67625686,-7216115.72861966,-7216157.53275104,-7216196.97406878,-7216233.94446696,-7216268.3426123,-7216300.07422188,-7216329.05232154,-7216355.19748435,-7216378.43804822,-7216398.71031239,-7216415.95871198,-7216430.13597034,-7216441.20322858,-7216449.13015211,-7216453.8950138,-7216455.48475349,-7214135.48475349,4014314.81839922,4014254.10868998,4014193.56538183,4014133.35441977,4014073.64083787,4014014.5883069,4013956.35868575,4013899.11157775,4013843.00389325,4013788.18941952,4013734.81839922,4013683.0371186,4013632.98750656,4013584.8067456,4013538.62689584,4013494.57453304,4013452.77040167,4013413.32908393,4013376.35868575,4013341.9605404,4013310.22893083,4013281.25083116,4013255.10566836,4013231.86510448,4013211.59284032,4013194.34444073,4013180.16718237,4013169.09992413,4013161.17300059,4013156.40813891,4013154.81839922,4014375.52810846,4014436.07141661,4014496.28237867,4014555.99596057,4014615.04849154,4014673.2781127,4014730.52522069,4014786.63290519,4014841.44737892,4014894.81839922,4014946.59967984,4014996.64929188,4015044.83005284,4015091.0099026,4015135.0622654,4015176.86639678,4015216.30771451,4015253.2781127,4015287.67625804,4015319.40786761,4015348.38596728,4015374.53113009,4015397.77169396,4015418.04395812,4015435.29235772,4015449.46961607,4015460.53687431,4015468.46379785,4015473.22865954,4015474.81839922,4014314.81839922),2L))),bBox = structure(c(xmin = -7216455.48475349,ymin = 4013154.81839922,xmax = -7214135.48475349,ymax = 4015474.81839922
),"data.frame")))
解决方法
如果要检索组成多边形的点的所有坐标，可以使用：
public function collection(Collection $rows)
{
foreach ($rows as $row)
{
$this->gradelevel = $row['grade_level_code'];
$employeegrade = HrEmployee::where('company_id',auth()->user()->company_id)->where('employee_code',$row['staff_id'])->where('email',$row['official_email']) ->first();
$employeegrade->grade_level_id = $this->getGradeLevel();
$employeegrade->save();
}
}
public function getGradeLevel(){
if(!empty($this->gradelevel) || !$this->gradelevel){
return HrGradeLevel::where('grade_level_code',$this->gradelevel)->where('company_id',Auth::user()->company_id)->pluck('id')->first();
} else {
return 0;
}
}
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