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26
4
我正在读取两个包含地理空间数据的文件，一个为 .shp，一个为 .csv(使用 options = c('X_POSSIBLE_NAMES=lat', 'Y_POSSIBLE_NAMES=lon')。 .shp 文件在读取时在 bbox 字段中有不寻常的值，但图形很好。.csv 文件在读取时在 bbox 字段中有正确的值，但图形很糟糕。这是读取的消息和输出.
Reading layer `WWW` from data source `XXX.shp' using driver `ESRI Shapefile'
Simple feature collection with 222 features and 12 fields
geometry type: LINESTRING
dimension: XY
bbox: xmin: 745400.7 ymin: 2402049 xmax: 998753.2 ymax: 2671392
epsg (SRID): 32645
proj4string: +proj=utm +zone=45 +datum=WGS84 +units=m +no_defs
和
options: X_POSSIBLE_NAMES=lat Y_POSSIBLE_NAMES=lon
Reading layer `YYY` from data source `ZZZ`.csv' using driver `CSV'
Simple feature collection with 5 features and 3 fields
geometry type: POINT
dimension: XY
bbox: xmin: 24.70942 ymin: 87.91372 xmax: 24.70942 ymax: 88.20073
epsg (SRID): NA
proj4string: NA
structure(list(Transporta = 31159.5791334, Transpor_1 = 1, Transpor_2 = 2,
Transpor_3 = 0, TransportS = 1, Transpor_4 = 120.8226354,
Transpor_5 = 40.37383139, Transpor_6 = 0.334157844, Transpor_7 = 0.6603,
Transpor_8 = 0.8694, Transpor_9 = structure(NA_integer_, .Label = character(0), class = "factor"),
class = structure(1L, .Label = "0", class = "factor"), geometry = structure(list(
structure(c(745439.842100001, 745546.5795, 745632.3839,
745788.981400001, 745917.343899999, 745985.294699999,
746066.299, 746154.675899999, 746368.8333, 746569.5261,
746772.2455, 746881.8819, 747004.401999999, 747073.7139,
747272.5434, 747470.2489, 747669.9781, 747812.230399999,
747975.2242, 748282.6014, 748497.1264, 748706.9185, 749043.816300001,
749292.6146, 749610.7259, 749925.135099999, 750001.7305,
750624.1876, 750825.9755, 750948.688199999, 751059.9489,
751163.9131, 751327.932799999, 751563.730499999, 751814.7569,
751971.032300002, 752126.386900001, 752195.9161, 752213.0906,
752386.998999999, 752474.422399999, 752562.3503, 752732.1897,
752984.445600001, 753125.1189, 753316.914400001, 753451.7143,
753804.5972, 753975.4802, 754070.401899998, 754153.675599999,
754287.556099999, 754405.755000002, 754531.939100001,
754559.107699999, 754588.9883, 754515.016200001, 754515.4296,
754545.5989, 754566.464399999, 754662.8412, 754914.5953,
755505.306800001, 756006.1144, 757647.819899998, 757818.6545,
757857.6266, 757878.117400001, 757888.392300001, 757979.6043,
758039.2786, 758104.023299999, 758273.8898, 758353.649,
758363.7606, 758425.7181, 758461.5542, 758412.883999999,
758361.6557, 758337.5731, 758369.8289, 758400.552799999,
758599.791, 758782.7463, 758948.5656, 759066.780899999,
759122.1718, 759140.5877, 759163.8683, 759310.9385, 759418.1858,
761587.9766, 761697.946600001, 761732.9896, 761735.1635,
761771.6095, 761834.645200001, 761880.7744, 761988.7883,
762117.364700001, 762363.861100001, 762461.7972, 762577.650000001,
2549587.0462, 2549520.9314, 2549439.3669, 2549255.2505,
2549117.1188, 2548990.8909, 2548851.1706, 2548730.2398,
2548549.1469, 2548369.9096, 2548184.485, 2548055.6101,
2547843.9775, 2547702.8617, 2547377.6804, 2547071.7279,
2546836.4809, 2546710.2235, 2546607.1267, 2546468.6995,
2546397.9558, 2546368.2405, 2546431.9041, 2546481.667,
2546520.1404, 2546550.2619, 2546534.1647, 2546540.4899,
2546584.3733, 2546647.1947, 2546721.98, 2546784.4899,
2546843.9544, 2546872.2121, 2546826.1245, 2546737.2423,
2546642.6158, 2546522.2403, 2546392.8828, 2545671.1662,
2545403.889, 2545106.76, 2544870.7301, 2544665.9495,
2544572.9174, 2544320.907, 2544112.5035, 2543574.9242,
2543279.2004, 2543016.8945, 2542750.9041, 2542376.3794,
2542042.1049, 2541679.6057, 2541467.5463, 2541190.3413,
2540905.4868, 2540780.0052, 2540631.2105, 2540525.5178,
2540373.1915, 2540070.0945, 2539482.8831, 2539046.8166,
2537839.0783, 2537724.5041, 2537640.0879, 2537539.1494,
2537377.2627, 2537091.1622, 2536893.6567, 2536619.2583,
2536123.8235, 2535849.6827, 2535679.4848, 2535292.3446,
2534815.1725, 2534426.1384, 2534186.3689, 2533976.9259,
2533708.7239, 2533530.0804, 2533205.0132, 2532931.801,
2532675.3421, 2532349.1915, 2532184.0268, 2531985.8156,
2531722.8626, 2531466.0844, 2531342.3258, 2531359.46,
2531296.537, 2531224.2141, 2531098.6506, 2530945.319,
2530557.4524, 2530278.6875, 2529895.6515, 2529626.4184,
2529270.0938, 2529090.8971, 2528794.2838), .Dim = c(103L,
2L), class = c("XY", "LINESTRING", "sfg"))), class = c("sfc_LINESTRING",
"sfc"), precision = 0, bbox = structure(c(xmin = 745439.842100001,
ymin = 2528794.2838, xmax = 762577.650000001, ymax = 2549587.0462
), class = "bbox"), crs = structure(list(epsg = 32645L, proj4string = "+proj=utm +zone=45 +datum=WGS84 +units=m +no_defs"), class = "crs"), n_empty = 0L)), sf_column = "geometry", agr = structure(c(Transporta = NA_integer_,
Transpor_1 = NA_integer_, Transpor_2 = NA_integer_, Transpor_3 = NA_integer_,
TransportS = NA_integer_, Transpor_4 = NA_integer_, Transpor_5 = NA_integer_,
Transpor_6 = NA_integer_, Transpor_7 = NA_integer_, Transpor_8 = NA_integer_,
Transpor_9 = NA_integer_, class = NA_integer_), .Label = c("constant",
"aggregate", "identity"), class = "factor"), row.names = 1L, class = c("sf",
"data.frame"))
和
structure(list(width = structure(c(1L, 2L, 5L, 3L, 4L), .Label = c("2.4716396025460600",
"2.6281478054445400", "3.0063089766321100", "3.3519104918569500",
"4.263698279008270"), class = "factor"), lat = c(24.7094195311052,
24.7094195311052, 24.7094195311052, 24.7094195311052, 24.7094195311052
), lon = c(87.9137151118854, 87.9139846064706, 88.1161055453975,
88.1996488668206, 88.2007268451616), geometry = structure(list(
structure(c(24.7094195311052, 87.9137151118854), class = c("XY",
"POINT", "sfg")), structure(c(24.7094195311052, 87.9139846064706
), class = c("XY", "POINT", "sfg")), structure(c(24.7094195311052,
88.1161055453975), class = c("XY", "POINT", "sfg")), structure(c(24.7094195311052,
88.1996488668206), class = c("XY", "POINT", "sfg")), structure(c(24.7094195311052,
88.2007268451616), class = c("XY", "POINT", "sfg"))), class = c("sfc_POINT",
"sfc"), precision = 0, bbox = structure(c(xmin = 24.7094195311052,
ymin = 87.9137151118854, xmax = 24.7094195311052, ymax = 88.2007268451616
), class = "bbox"), crs = structure(list(epsg = NA_integer_,
proj4string = NA_character_), class = "crs"), n_empty = 0L)), sf_column = "geometry", agr = structure(c(width = NA_integer_,
lat = NA_integer_, lon = NA_integer_), .Label = c("constant",
"aggregate", "identity"), class = "factor"), row.names = c(NA,
5L), class = c("sf", "data.frame"))
st_crs() 和 st_transform() 进行修复我已经尝试将第二个的 epsg 和 proj4string 属性设置为第一个的属性，但它没有修复图形或错误的几何值:
# make a copy of second_sf
second_sf_transformed <- second_sf
# make EPSG of the copy of the second the same as the first
st_crs(second_sf_transformed) <- st_crs(first_sf)
# make the proj4string of the copy of the second the same as the first
second_sf_transformed <- st_transform(second_sf_transformed, '+proj=utm +zone=45 +datum=WGS84 +units=m +no_defs')
我需要对来自 csv 的数据进行转换，以便我可以一起分析两个 shapefile，但我不知道它是什么。有人知道吗？
感谢@dww，我得到了正确的 shapefile 坐标，但 csv 数据仍然无法正确绘制图表。
# make EPSG of the copy of the second the same as the first (keeps ggplot() from complaining)
st_crs(second_sf_transformed) <- st_crs(first_sf)
# reproject data
first_sf_transformed <- st_transform(first_sf, "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0" )
shp数据
structure(list(Transporta = 31159.5791334, Transpor_1 = 1, Transpor_2 = 2,
Transpor_3 = 0, TransportS = 1, Transpor_4 = 120.8226354,
Transpor_5 = 40.37383139, Transpor_6 = 0.334157844, Transpor_7 = 0.6603,
Transpor_8 = 0.8694, Transpor_9 = structure(NA_integer_, .Label = character(0), class = "factor"),
class = structure(1L, .Label = "0", class = "factor"), geometry = structure(list(
structure(c(89.3951268474236, 89.3961571846398, 89.3969809093774,
89.3984785916188, 89.3997082546062, 89.4003506946848,
89.4011182562287, 89.401960703154, 89.4040200160893,
89.4059482811558, 89.4078952678924, 89.4089436459468,
89.4101043491955, 89.4107575329244, 89.4126439952916,
89.4145225108038, 89.4164320555286, 89.4177986910559,
89.4193712573017, 89.4223458004554, 89.4244259337919,
89.4264665255084, 89.4297614260539, 89.4321951598272,
89.4353028498903, 89.4383730983178, 89.439117259213,
89.4451869671167, 89.4471614499647, 89.4483680787049,
89.4494650144704, 89.4504888199855, 89.4520976579026,
89.4544012217856, 89.4568411070362, 89.4583501885189,
89.4598493329306, 89.4605074942507, 89.4606537526005,
89.4622309990771, 89.4630394820499, 89.4638479664175,
89.4654649342105, 89.4678903853704, 89.4692464104709,
89.4710746363703, 89.4723543932316, 89.4757057279109,
89.4773226951387, 89.4782047141727, 89.4789725685317,
89.4802157622041, 89.4813126972553, 89.4824827608323,
89.4827125868794, 89.4829581002389, 89.4821902450637,
89.4821735976744, 89.4824430933553, 89.4826290191, 89.4835431323413,
89.4859465218357, 89.4916059082089, 89.4964138369265,
89.5122097031426, 89.5138551060626, 89.5142207513114,
89.5144035734198, 89.5144767019004, 89.5153176863904,
89.5158661532172, 89.5164511855445, 89.5180234596532,
89.5187547490365, 89.518824862045, 89.5193638514563,
89.5196333452499, 89.5190943561545, 89.5185553667664,
89.5182858719894, 89.5185553670613, 89.5188248615575,
89.5207113235949, 89.5224477642401, 89.5240200382999,
89.5251169729864, 89.525628876173, 89.5257751340317,
89.5259579570345, 89.5273474078494, 89.5283712135035,
89.5495054976574, 89.5505658674762, 89.5508949488069,
89.5508949489754, 89.5512240291922, 89.5517724970054,
89.5521747065285, 89.5531619475244, 89.5543685767302,
89.556708704603, 89.557632082246, 89.5587100597639, 23.0366666407601,
23.0360541520806, 23.0353053114777, 23.0336204191383,
23.0323547265548, 23.0312054063198, 23.0299323767221,
23.0288278360431, 23.0271616644131, 23.0255142147017,
23.0238106014021, 23.0226311762231, 23.0207029106886,
23.0194189874174, 23.0164545471189, 23.013663804625,
23.0115108869883, 23.0103501834476, 23.0093954108462,
23.0081002152887, 23.0074297034657, 23.0071301670893,
23.0076543553864, 23.0080662184381, 23.0083657545691,
23.0085904068476, 23.0084336181262, 23.008397053537,
23.0087626986679, 23.009311166109, 23.0099693276515,
23.0105177951238, 23.0110296978796, 23.0112490852379,
23.0107951600909, 23.0099693278917, 23.0090917796211,
23.007994844059, 23.006824780279, 23.0002848724084, 22.9978594199624,
22.9951644743623, 22.9930085179719, 22.9911220557635,
22.9902610598549, 22.9879574957376, 22.9860561421864,
22.9811507560206, 22.9784558101354, 22.9760740319897,
22.9736607748343, 22.9702602760285, 22.9672254217359,
22.9639346170366, 22.9620166398532, 22.9595103113266,
22.956950796692, 22.9558182646749, 22.9544707918072,
22.9535137332223, 22.9521242822197, 22.949350394888,
22.9439605028831, 22.939948302187, 22.928796127859, 22.9277357574655,
22.9269679028182, 22.9260537905528, 22.9245912104683,
22.9219951306966, 22.9202034702482, 22.9177170836491,
22.9132196495687, 22.9107332636081, 22.9091957023515,
22.9056922716249, 22.9013803590159, 22.8978769292378,
22.8957209717259, 22.893834509633, 22.8914090590013,
22.8897920924525, 22.8868276509463, 22.8843336909749,
22.8819935625524, 22.8790318381511, 22.8775326931856,
22.87574103285, 22.8733643396172, 22.8710242115184, 22.8698907125254,
22.8697078900248, 22.8691228573515, 22.8684646968471,
22.8673311965241, 22.8659417452486, 22.8624315537002,
22.8599086028934, 22.8564349744818, 22.8539851531464,
22.8507309120264, 22.8490984092694, 22.846403462933), .Dim = c(103L,
2L), class = c("XY", "LINESTRING", "sfg"))), class = c("sfc_LINESTRING",
"sfc"), precision = 0, bbox = structure(c(xmin = 89.3951268474236,
ymin = 22.846403462933, xmax = 89.5587100597639, ymax = 23.0366666407601
), class = "bbox"), crs = structure(list(epsg = 4326L, proj4string = "+proj=longlat +datum=WGS84 +no_defs"), class = "crs"), n_empty = 0L)), sf_column = "geometry", agr = structure(c(Transporta = NA_integer_,
Transpor_1 = NA_integer_, Transpor_2 = NA_integer_, Transpor_3 = NA_integer_,
TransportS = NA_integer_, Transpor_4 = NA_integer_, Transpor_5 = NA_integer_,
Transpor_6 = NA_integer_, Transpor_7 = NA_integer_, Transpor_8 = NA_integer_,
Transpor_9 = NA_integer_, class = NA_integer_), .Label = c("constant",
"aggregate", "identity"), class = "factor"), row.names = 1L, class = c("sf",
"data.frame"))
csv 数据
structure(list(width = structure(c(1L, 2L, 5L, 3L, 4L), .Label = c("2.4716396025460600",
"2.6281478054445400", "3.0063089766321100", "3.3519104918569500",
"4.263698279008270"), class = "factor"), lat = c(24.7094195311052,
24.7094195311052, 24.7094195311052, 24.7094195311052, 24.7094195311052
), lon = c(87.9137151118854, 87.9139846064706, 88.1161055453975,
88.1996488668206, 88.2007268451616), geometry = structure(list(
structure(c(24.7094195311052, 87.9137151118854), class = c("XY",
"POINT", "sfg")), structure(c(24.7094195311052, 87.9139846064706
), class = c("XY", "POINT", "sfg")), structure(c(24.7094195311052,
88.1161055453975), class = c("XY", "POINT", "sfg")), structure(c(24.7094195311052,
88.1996488668206), class = c("XY", "POINT", "sfg")), structure(c(24.7094195311052,
88.2007268451616), class = c("XY", "POINT", "sfg"))), n_empty = 0L, crs = structure(list(
epsg = 32645L, proj4string = "+proj=utm +zone=45 +datum=WGS84 +units=m +no_defs"), class = "crs"), class = c("sfc_POINT",
"sfc"), precision = 0, bbox = structure(c(xmin = 24.7094195311052,
ymin = 87.9137151118854, xmax = 24.7094195311052, ymax = 88.2007268451616
), class = "bbox"))), row.names = c(NA, -5L), sf_column = "geometry", agr = structure(c(width = NA_integer_,
lat = NA_integer_, lon = NA_integer_), class = "factor", .Label = c("constant",
"aggregate", "identity")), class = c("sf", "data.frame"))
最佳答案
问题似乎是 sf从 csv 数据创建的对象在几何列中似乎具有倒置的纬度和经度:
csv_in <- structure(list(width = structure(c(1L, 2L, 5L, 3L, 4L), .Label = c("2.4716396025460600",
"2.6281478054445400", "3.0063089766321100", "3.3519104918569500",
"4.263698279008270"), class = "factor"), lat = c(24.7094195311052,
24.7094195311052, 24.7094195311052, 24.7094195311052, 24.7094195311052
), lon = c(87.9137151118854, 87.9139846064706, 88.1161055453975,
88.1996488668206, 88.2007268451616), geometry = structure(list(
structure(c(24.7094195311052, 87.9137151118854), class = c("XY",
"POINT", "sfg")), structure(c(24.7094195311052, 87.9139846064706
), class = c("XY", "POINT", "sfg")), structure(c(24.7094195311052,
88.1161055453975), class = c("XY", "POINT", "sfg")), structure(c(24.7094195311052,
88.1996488668206), class = c("XY", "POINT", "sfg")), structure(c(24.7094195311052,
88.2007268451616), class = c("XY", "POINT", "sfg"))), class = c("sfc_POINT",
"sfc"), precision = 0, bbox = structure(c(xmin = 24.7094195311052,
ymin = 87.9137151118854, xmax = 24.7094195311052, ymax = 88.2007268451616
), class = "bbox"), crs = structure(list(epsg = NA_integer_,
proj4string = NA_character_), class = "crs"), n_empty = 0L)), sf_column = "geometry", agr = structure(c(width = NA_integer_,
lat = NA_integer_, lon = NA_integer_), .Label = c("constant",
"aggregate", "identity"), class = "factor"), row.names = c(NA,
5L), class = c("sf", "data.frame"))
Simple feature collection with 5 features and 3 fields
geometry type: POINT
dimension: XY
bbox: xmin: 24.70942 ymin: 87.91372 xmax: 24.70942 ymax: 88.20073
epsg (SRID): NA
proj4string: NA
width lat lon geometry
1 2.4716396025460600 24.70942 87.91372 POINT (24.70942 87.91372)
2 2.6281478054445400 24.70942 87.91398 POINT (24.70942 87.91398)
3 4.263698279008270 24.70942 88.11611 POINT (24.70942 88.11611)
4 3.0063089766321100 24.70942 88.19965 POINT (24.70942 88.19965)
5 3.3519104918569500 24.70942 88.20073 POINT (24.70942 88.20073)
(请注意，在几何列中，第一列是经度)。
您可以通过更正导入脚本然后为 CRS 分配 sf::st_crs(csv_in) <- 4326 来解决此问题，或使用类似的东西:
csv_in <- sf::st_as_sf(sf::st_drop_geometry(csv_in), coords = c("lon","lat"), remove= FALSE)
sf::st_crs(csv_in) <- 4326
csv_in
Simple feature collection with 5 features and 3 fields
geometry type: POINT
dimension: XY
bbox: xmin: 87.91372 ymin: 24.70942 xmax: 88.20073 ymax: 24.70942
epsg (SRID): 4326
proj4string: +proj=longlat +datum=WGS84 +no_defs
width lat lon geometry
1 2.4716396025460600 24.70942 87.91372 POINT (87.91372 24.70942)
2 2.6281478054445400 24.70942 87.91398 POINT (87.91398 24.70942)
3 4.263698279008270 24.70942 88.11611 POINT (88.11611 24.70942)
4 3.0063089766321100 24.70942 88.19965 POINT (88.19965 24.70942)
5 3.3519104918569500 24.70942 88.20073 POINT (88.20073 24.70942)
(请注意，现在几何列中的坐标是“倒置的”)。
尝试绘制这个给出:
ggplot(csv_in) + geom_sf() + geom_sf(data = shp_in)
，这似乎没问题
关于r - 如何转换从 CSV 读取为纬度/经度坐标的地理空间数据以匹配从 SHP 读取的数据？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/57257835/
26
4
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我有两个 csv 文件 file1.csv 和 file2.csv。 file1.csv 包含 4 列。 文件1: Header1,Header2,Header3,Header4 aaaaaaa,bb
我想知道是否有任何方法可以在导入数据库之前测试 CSV 文件？ 我有一个包含多列的巨大 CSV 文件，每列都有不同的数据类型和大小。如何测试生成的 CSV 文件中出现的数据是否与每列的大小一致？ 还有
我正在从 SCOM 中提取服务器列表，并希望根据包含以下数据的 CSV 检查此列表: Computername,Collection Name Server01,NA - All DA Servers
我有一个包含 24 列的 csv 文件。其中我只想阅读 3 列。我看到 super CSV 是一个非常强大的库，但我不知道如何部分读取 CSV。 partial reading上的链接坏了。 请帮我举
我正在尝试将加特林日志文件导出到 CSV，因为我需要更新 google 电子表格中的所有全局值，因为我的经理需要电子表格中的值。 最佳答案 此 CSV 文件被删除并替换为 JSON 文件，名为 glo
我对 csv 是结构化数据还是半结构化数据感到困惑。 就像 RDBMS 是一个有关系的结构化数据，但 csv 没有关系。 我无法找到确切的答案。 最佳答案 我可以说，具有恒定列和行(二维)的 CSV
我正在使用 pipes-csv 库读取一个 csv 文件。我想先读第一行，然后再读其余的。不幸的是，在 Pipes.Prelude.head 函数返回之后。管道正在以某种方式关闭。有没有办法先读取 c
起初这似乎很明显，但现在我不太确定。 如果 CSV 文件具有以下行: a, 我会将其解释为具有值“a”和“”的两个字段。但是然后查看一个空行，我可以很容易地争辩说它表示一个值为“”的字段。 我接受文件
我正在尝试将列表字典写入 CSV 文件。我希望这些键是 CSV 文件的标题，以及与该键关联的列中的每个键关联的值。 如果我的字典是: {'600': [321.4, 123.5, 564.1, 764
关闭。这个问题是off-topic .它目前不接受答案。 想改进这个问题吗？ Update the question所以它是on-topic用于堆栈溢出。 关闭 10 年前。 Improve thi
是否有任何官方方法允许 CSV 格式的文件允许评论，无论是在其自己的行上还是在行尾？ 我尝试检查wikipedia关于此以及RFC 4180但两者都没有提到任何让我相信它不是文件格式的一部分的内容，所
我有一些 csv 格式的数据。然而它们已经是一个字符串，因为我是从 HTTP 请求中获取它们的。我想使用数据框来查看数据。但是我不知道如何解析它，因为 CSV 包只接受文件，而不接受字符串。 一种解决
我有一个 CSV 文件，其中包含一些字段的值列表。它们作为 HTML“ul”元素存储在数据库中，但我想将它们转换为对电子表格更友好的东西。 我应该使用什么作为分隔符？我可以使用转义的逗号、竖线、分号或
我使用 Google 表格(电子表格)来合并我的 Gambio 商店的不同来源的文章数据。要导入数据，我需要在 .csv 文件中使用管道符号作为分隔符/分隔符，并使用 "作为文本分隔符。在用于导出为
这是一个奇怪的请求，因为我们都知道数据库头不应该包含空格。 但是，我正在使用的系统需要在其标题中使用空格才能导入。 我创建了一个 Report Builder 报告，它将数据构建到一个表中，并在我运行
我有一个 .csv 文件，我需要将其转换为 coldfusion 查询。我使用了 cflib.org CSVtoQuery 方法，它工作正常......但是...... 如果 csv 中的“单元格”在
我想知道是否有任何方法可以生成文化中性 CSV 文件，或者至少指定文件中存在的特定列的数据格式。 例如，我生成了包含带小数点分隔符 (.) 的数字的 CSV 文件，然后 将其传递给小数点分隔符为 (,
我正在构建一个 CSV 字符串 - 因此用户单击 div 的所有内容 - 5 个字符的字符串都会传递到隐藏字段中 - 我想做的是附加每个新值并创建一个 CSV 字符串 - 完成后- 在文本框中显示 -
我正在努力从另外两个文件创建一个 CSV 文件 这是我需要的 我想要的文件(很多其他行) “AB”；“A”；“B”；“C”；“D”；“E” 我拥有的文件: 文件 1:"A";"B";"C";"D";"
我正在尝试将表导出到配置单元中的本地 csv 文件。 INSERT OVERWRITE LOCAL DIRECTORY '/home/sofia/temp.csv' ROW FORMAT DELIMI
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