我正在嘗試使用 ggrepel 創建我的第一張地圖，但如您所見，我創建了一個重疊標簽的垃圾箱火災。我正在映射和標注的大多數位置都聚集在東北部，因此標簽重疊。如何讓一些標簽滑過地圖邊界（可以說是在海洋中）？這是我用來創建這個怪物的代碼：
plot_usmap(fill = "light blue", alpha = 0.5)
ggrepel::geom_label_repel(data = top_18_2_transformed, aes(x=x, y=y, label=INSTNM),
size=3,
label.padding = unit(.75,"mm"),
nudge_y = 20,
nudge_x = 20,
box.padding=0.3,
max.overlaps=30,
point.padding=NA,
family="Avenir Next",
fill="gray99",
alpha=1.0,
label.r=unit(0.2,"lines"),
min.segment.length = 0.1,
label.size=unit(.15,"mm"),
segment.color="black",
segment.size=1,seed=1000)
geom_point(data = top_18_2_transformed, aes(x = x, y = y, size = UGDS),
color = "red",
alpha = 0.75)
labs(title = "Select Colleges",
size = "Undergrad Enrollment")
theme(legend.position = "right")
這是我有問題的地圖的圖片：
提前感謝您提供的任何更正。
2022 年 3 月 31 日更新：這是dput(top_18_2_transformed)：
structure(list(lon = c(-74.659365, -122.167359, -78.937624, -75.19391,
-71.093226, -77.073463, -118.125878, -117.709837, -71.222839,
-79.941993, -72.926688, -76.483084, -73.961885, -71.169242, -74.025334,
-75.380236, -70.624084, -71.118313), lat = c(40.348732, 37.429434,
36.001135, 39.950929, 42.359243, 38.908809, 34.137349, 34.106515,
42.385995, 40.44357, 41.311158, 42.4472, 40.808286, 42.336213,
40.744776, 40.606822, 41.739072, 42.374471), UNITID = c(186131,
243744, 198419, 215062, 166683, 131496, 110404, 115409, 164739,
211440, 130794, 190415, 190150, 164924, 186867, 213543, 166692,
166027), OPEID = c(262700, 130500, 292000, 337800, 217800, 144500,
113100, 117100, 212400, 324200, 142600, 271100, 270700, 212800,
263900, 328900, 218100, 215500), OPEID6 = c(2627, 1305, 2920,
3378, 2178, 1445, 1131, 1171, 2124, 3242, 1426, 2711, 2707, 2128,
2639, 3289, 2181, 2155), INSTNM = c("Princeton University", "Stanford University",
"Duke University", "University of Pennsylvania", "Massachusetts Institute of Technology",
"Georgetown University", "California Institute of Technology",
"Harvey Mudd College", "Bentley University", "Carnegie Mellon University",
"Yale University", "Cornell University", "Columbia University in the City of New York",
"Boston College", "Stevens Institute of Technology", "Lehigh University",
"Massachusetts Maritime Academy", "Harvard University"), CITY = c("Princeton",
"Stanford", "Durham", "Philadelphia", "Cambridge", "Washington",
"Pasadena", "Claremont", "Waltham", "Pittsburgh", "New Haven",
"Ithaca", "New York", "Chestnut Hill", "Hoboken", "Bethlehem",
"Buzzards Bay", "Cambridge"), STABBR = c("NJ", "CA", "NC", "PA",
"MA", "DC", "CA", "CA", "MA", "PA", "CT", "NY", "NY", "MA", "NJ",
"PA", "MA", "MA"), ZIP = c("08544-0070", "94305", "27708", "19104-6303",
"02139-4307", "20057-0001", "91125", "91711", "02452-4705", "15213-3890",
"6520", "14853", "10027", "2467", "07030-5991", "18015", "02532-1803",
"2138"), ACCREDAGENCY = c("Middle States Commission on Higher Education",
"Western Association of Schools and Colleges Senior Colleges and University Commission",
"Southern Association of Colleges and Schools Commission on Colleges",
"Middle States Commission on Higher Education", "New England Commission on Higher Education",
"Middle States Commission on Higher Education", "Western Association of Schools and Colleges Senior Colleges and University Commission",
"Western Association of Schools and Colleges Senior Colleges and University Commission",
"New England Commission on Higher Education", "Middle States Commission on Higher Education",
"New England Commission on Higher Education", "Middle States Commission on Higher Education",
"Middle States Commission on Higher Education", "New England Commission on Higher Education",
"Middle States Commission on Higher Education", "Middle States Commission on Higher Education",
"New England Commission on Higher Education", "New England Commission on Higher Education"
), INSTURL = c("www.princeton.edu/", "www.stanford.edu/", "www.duke.edu/",
"www.upenn.edu/", "web.mit.edu/", "www.georgetown.edu/", "www.caltech.edu/",
"https://www.hmc.edu/", "www.bentley.edu/", "www.cmu.edu/", "https://www.yale.edu/",
"www.cornell.edu/", "www.columbia.edu/", "www.bc.edu/", "www.stevens.edu/",
"www.lehigh.edu/", "https://www.maritime.edu/", "www.harvard.edu/"
), SCH_DEG = c(3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3), PREDDEG = c(3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3), HIGHDEG = c(4, 4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4), REGION = c(2, 8, 5, 2, 1, 2, 8, 8, 1, 2, 1,
2, 2, 1, 2, 2, 1, 1), CCBASIC = c(15, 15, 15, 15, 15, 15, 15,
21, 18, 15, 15, 15, 15, 15, 16, 16, 22, 15), ADM_RATE = c(0.0578,
0.0434, 0.076, 0.0766, 0.067, 0.1436, 0.0642, 0.1367, 0.4672,
0.1544, 0.0608, 0.1085, 0.0545, 0.2722, 0.3996, 0.321, 0.9146,
0.0464), ACTCM25 = c(33, 32, 33, 33, 34, 31, 35, 33, 27, 33,
33, 32, 33, 31, 31, 29, 19, 33), ACTCM75 = c(35, 35, 35, 35,
36, 35, 36, 35, 31, 35, 35, 35, 35, 34, 34, 33, 24, 35), SAT_AVG = c(1517,
1503, 1522, 1511, 1547, 1473, 1557, 1526, 1327, 1513, 1517, 1487,
1511, 1437, 1429, 1380, 1100, 1517), DISTANCEONLY = c(0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), UGDS = c(5308,
6994, 6546, 10774, 4516, 7141, 938, 893, 4157, 6535, 6089, 14976,
8221, 9637, 3641, 5164, 1654, 7547), CURROPER = c(1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), COSTT4_A = c(70900,
71587, 75105, 75303, 70240, 73840, 72084, 76953, 68577, 72265,
73900, 73879, 76907, 73053, 68734, 68383, 27858, 73485), COSTT4_P = c("NULL",
"NULL", "NULL", "NULL", "NULL", "NULL", "NULL", "NULL", "NULL",
"NULL", "NULL", "NULL", "NULL", "NULL", "NULL", "NULL", "NULL",
"NULL"), TUITIONFEE_IN = c(52800, 53529, 58031, 57770, 53790,
56058, 54600, 58660, 51830, 57119, 55500, 57222, 61788, 57910,
54014, 55240, 10018, 51925), TUITIONFEE_OUT = c(52800, 53529,
58031, 57770, 53790, 56058, 54600, 58660, 51830, 57119, 55500,
57222, 61788, 57910, 54014, 55240, 25752, 51925), AVGFACSAL = c(20724,
20865, 16863, 18277, 19624, 15798, 20595, 14397, 14592, 12296,
19830, 15574, 19431, 15599, 15318, 13763, 8928, 20988), PFTFAC = c("0.835",
"0.9881", "0.9364", "0.7779", "0.9885", "0.4815", "0.9289", "0.8992",
"0.6696", "0.9161", "0.717", "0.9074", "0.4521", "0.6662", "1",
"0.8392", "0.5867", "0.862"), C150_4 = c(0.979, 0.9432, 0.9462,
0.96, 0.954, 0.9491, 0.9357, 0.9167, 0.8952, 0.9049, 0.972, 0.9453,
0.9549, 0.9404, 0.8473, 0.8981, 0.7629, 0.971), RET_FT4 = c(0.9768,
0.9876, 0.9827, 0.9808, 0.9946, 0.9679, 0.9826, 0.9744, 0.9201,
0.9732, 0.9892, 0.9748, 0.9853, 0.9467, 0.9394, 0.9349, 0.8672,
0.9722), RET_PT4 = c("NULL", "NULL", "NULL", "0.9245", "NULL",
"0.6667", "NULL", "NULL", "NULL", "NULL", "NULL", "NULL", "0.95",
"NULL", "NULL", "NULL", "NULL", "NULL"), MD_EARN_WNE_P10 = c("95689",
"97798", "93115", "103246", "111222", "96375", "112166", "108988",
"107974", "99998", "88655", "91176", "89871", "93021", "98159",
"95033", "91668", "84918"), PCT25_EARN_WNE_P10 = c("52729", "61965",
"61558", "65218", "67120", "61372", "67501", "69466", "73117",
"62003", "60311", "59566", "56005", "62006", "72669", "65644",
"68187", "56301"), PCT75_EARN_WNE_P10 = c("167686", "172245",
"151838", "174907", "169465", "147685", "175675", "173725", "146079",
"159483", "146102", "147189", "141158", "147010", "127298", "134075",
"129421", "153746"), MD_EARN_WNE_P6 = c("84713", "88873", "77260",
"80445", "112623", "71107", "129420", "112059", "78514", "87824",
"72046", "78779", "79434", "70858", "82237", "79832", "79354",
"77816"), GRAD_DEBT_MDN_SUPP = c("10450", "12000", "13500", "16763",
"13418", "16500", "PrivacySuppressed", "22089", "25000", "22014",
"13142", "14500", "21500", "18000", "27000", "23000", "26000",
"12665"), GRAD_DEBT_MDN10YR_SUPP = c("104.4654099", "119.9602793",
"134.9553142", "167.5745134", "134.1355856", "164.945384", "PrivacySuppressed",
"220.8168841", "249.9172485", "220.0671323", "131.3764992", "144.9520041",
"214.9288337", "179.9404189", "269.9106283", "229.9238686", "259.9139384",
"126.6080781"), C100_4 = c(0.898, 0.7288, 0.8831, 0.8571, 0.8691,
0.9076, 0.8434, 0.8565, 0.8479, 0.7599, 0.8777, 0.8694, 0.8635,
0.9003, 0.4566, 0.8003, 0.6322, 0.8476), ICLEVEL = c(1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), OPENADMP = c(2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2), GRADS = c("2997",
"10253", "10037", "14803", "6990", "12080", "1299", "NULL", "1086",
"7562", "7517", "8984", "23235", "4846", "3624", "1775", "97",
"21592"), ACCREDCODE = c("MSACHE", "WASCSR", "SACSCC", "MSACHE",
"NECHE", "MSACHE", "WASCSR", "WASCSR", "NECHE", "MSACHE", "NECHE",
"MSACHE", "MSACHE", "NECHE", "MSACHE", "MSACHE", "NECHE", "NECHE"
), RET_FT4_POOLED = c(0.9788, 0.9879, 0.9793, 0.9821, 0.9909,
0.9651, 0.9806, 0.9716, 0.9262, 0.97, 0.9892, 0.9741, 0.9825,
0.9479, 0.9423, 0.9378, 0.8633, 0.9817), C100_4_POOLED = c(0.8856,
0.739, 0.8788, 0.8546, 0.8602, 0.9009, 0.8242, 0.8551, 0.8326,
0.7546, 0.8772, 0.8766, 0.8677, 0.8918, 0.4515, 0.7621, 0.5955,
0.8573), BOOKSUPPLY = c("1050", "1245", "1434", "1358", "820",
"1200", "1428", "800", "1300", "1000", "1050", "970", "1294",
"1250", "1200", "1000", "1500", "1000"), ADMCON7 = c(1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 5, 1, 1, 1), MDCOMP_ALL = c(0.5845,
0.5845, 0.5845, 0.5845, 0.5845, 0.5845, 0.5845, 0.5845, 0.5845,
0.5845, 0.5845, 0.5845, 0.5845, 0.5845, 0.5845, 0.5845, 0.5845,
0.5845), MDCOST_ALL = c(15387.5, 15387.5, 15387.5, 15387.5, 15387.5,
15387.5, 15387.5, 15387.5, 15387.5, 15387.5, 15387.5, 15387.5,
15387.5, 15387.5, 15387.5, 15387.5, 15387.5, 15387.5), MDEARN_ALL = c(37078,
37078, 37078, 37078, 37078, 37078, 37078, 37078, 37078, 37078,
37078, 37078, 37078, 37078, 37078, 37078, 37078, 37078), PPTUG_EF = c(0,
0, 0.0031, 0.0537, 0.0064, 0.0214, 0, 0.0011, 0.0118, 0.017,
2e-04, 3e-04, 0.0633, 0.0127, 0, 0.0128, 0.023, 0.0745), INEXPFTE = c(60048,
113338, 68756, 56874, 80756, 31693, 105185, 34419, 15842, 28167,
57231, 29893, 96463, 23266, 12504, 24995, 9687, 46272), C150_4_POOLED = c(0.9712,
0.9435, 0.9512, 0.9574, 0.9477, 0.9452, 0.9278, 0.9179, 0.8917,
0.8968, 0.969, 0.9452, 0.9566, 0.9297, 0.8608, 0.886, 0.7484,
0.974), GRAD_DEBT_MDN = c("10450", "12000", "13500", "16763",
"13418", "16500", "17747", "22089", "25000", "22014", "13142",
"14500", "21500", "18000", "27000", "23000", "26000", "12665"
), x = c(2107384.76948701, -1933340.27810509, 1876178.25472949,
2077243.02501463, 2314261.77712267, 1955381.08673633, -1660141.85673732,
-1623368.30493136, 2303424.70345276, 1678023.03854027, 2211596.23078863,
1896995.53745184, 2147624.50302849, 2309370.68277906, 2144734.86774305,
2041573.64168227, 2373567.48443726, 2311783.20749272), y = c(-188894.792987744,
-582296.149881856, -762721.806918975, -245389.810253038, 123275.753360416,
-404107.357328073, -1027748.36033576, -1039201.65863312, 122405.777575308,
-300870.762534603, -39714.5927185968, -7748.73302456512, -121333.925485063,
118650.586978148, -129820.607837031, -179439.260821836, 71069.0976923304,
124173.1993115)), class = "data.frame", row.names = c(NA, -18L
))
uj5u.com熱心網友回復：
通過一些資料操作，您可以將標簽移到該國的任一側，繪制部分以將標簽連接到大學：
top_18_2_transformed <- top_18_2_transformed[order(-top_18_2_transformed$y),]
colleges_east <- top_18_2_transformed[top_18_2_transformed$x > 0,]
colleges_west <- top_18_2_transformed[top_18_2_transformed$x < 0,]
colleges_west$lab_x <- -2300000
colleges_west$lab_y <- seq(-1000000, -1500000, -250000)
colleges_east$lab_x <- 2800000
colleges_east$lab_y <- seq(1000000, -2500000, -250000)
plot_usmap(fill = "light blue", alpha = 0.5)
geom_text(data = colleges_west,
aes(x = lab_x, y = lab_y, label =stringr::str_wrap(INSTNM, 25)),
hjust = 1, size = 3, lineheight = 0.8)
geom_text(data = colleges_east,
aes(x = lab_x, y = lab_y, label = stringr::str_wrap(INSTNM, 25)),
hjust = 0, size = 3, lineheight = 0.8)
geom_point(data = top_18_2_transformed, aes(x = x, y = y, size = UGDS),
color = "red",
alpha = 0.75)
geom_segment(data = colleges_east,
aes(x, y, xend = lab_x - 100000, yend = lab_y))
geom_segment(data = colleges_west,
aes(x, y, xend = lab_x 100000, yend = lab_y))
labs(title = "Select Colleges",
size = "Undergrad Enrollment")
theme(legend.position = c(0.35, 0),
legend.direction = 'horizontal')
coord_cartesian(xlim = c( -3500000, 4000000),
ylim = c(-3000000, 1500000))
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