我想利用tmap包绘制1950年世界人口密度图。
我手动将人口数据分成了22个类别，并为每个类别填充不同的颜色。
我的代码如下：
library(tmap)
data(World)
map <- tm_shape(World)+
tm_fill("1950",
title = "Population class",
breaks = c(0, 100 ,200, 300, 400, 500, 600, 700, 800, 900,
1000, 1100, 1200, 1300, 1400, 1500, 1600, 1700, 1800,
1900, 2000, 3000, 4000),
textNA = "No data",
colorNA = "white",
palette = "topo")+
tm_borders()+
tm_layout("World Density Population Map")
tm_style_classic()
current.mode <- tmap_mode("plot")
map
在最后一步“map”时发生了错误：
错误：无效的调色板
我有一个来自wpp2015的公共数据集，虽然不完全与我的数据集相同，但可以提供对我的数据框结构的直觉理解。
dput(df) <- structure(list(name = structure(c(1L, 3L, 4L, 5L, 6L, 14L, 7L, 11L, 13L, 15L, 16L, 17L, 8L, 18L, 20L, 23L, 24L, 25L, 26L, 27L, 21L, 190L, 28L, 29L, 146L, 31L, 19L, 33L, 34L, 35L, 32L, 37L, 201L, 40L, 42L, 43L, 46L, 47L, 48L, 134L, 49L, 58L, 50L, 52L, 53L, 55L, 56L, 22L, 59L, 61L, 65L, 67L, 68L, 71L, 69L, 70L, 73L, 74L, 75L, 76L, 77L, 60L, 78L, 80L, 79L, 203L, 81L, 82L, 108L, 83L, 84L, 85L, 86L, 87L, 88L, 90L, 91L, 93L, 44L, 94L, 95L, 96L, 97L, 98L, 99L, 100L, 101L, 102L, 51L, 103L, 104L, 106L, 105L, 107L, 57L, 173L, 109L, 110L, 111L, 115L, 116L, 113L, 119L, 120L, 121L, 124L, 45L, 125L, 126L, 127L, 128L, 129L, 130L, 131L, 132L, 133L, 136L, 141L, 174L, 142L, 144L, 145L, 160L, 147L, 148L, 149L, 54L, 9L, 150L, 231L, 151L, 152L, 153L, 154L, 158L, 138L, 162L, 163L, 164L, 165L, 166L, 167L, 168L, 170L, 89L, 214L, 171L, 172L, 175L, 176L, 177L, 178L, 179L, 202L, 181L, 182L, 183L, 184L, 185L, 186L, 187L, 188L, 233L, 189L, 191L, 194L, 241L, 200L, 196L, 205L, 237L, 206L, 207L, 208L, 209L, 210L, 211L, 213L, 215L, 216L, 217L, 223L, 218L, 219L, 220L, 221L, 222L, 212L, 66L, 224L, 41L, 225L, 226L, 227L, 30L, 229L, 230L, 232L, 180L, 239L, 240L, 238L, 143L, 117L, 2L, 112L, 156L, 63L, 72L, 159L, 62L, 140L, 155L, 197L, 234L, 36L, 38L, 193L, 192L, 235L, 64L, 157L, 199L, 236L, 12L, 135L, 195L, 161L, 10L, 114L, 204L, 118L, 137L, 169L, 122L, 123L, 228L, 92L, 139L, 39L, 198L), .Label = c("Afghanistan", "Africa", "Albania", "Algeria", "Angola", "Antigua and Barbuda", "Argentina", "Armenia", "Aruba", "Asia", "Australia", "Australia/New Zealand", "Austria", "Azerbaijan", "Bahamas", "Bahrain", "Bangladesh", "Barbados", "Belarus", "Belgium", "Belize", "Benin", "Bhutan", "Bolivia (Plurinational State of)", "Bosnia and Herzegovina", "Botswana", "Brazil", "Brunei Darussalam", "Bulgaria", "Burkina Faso", "Burundi", "Cabo Verde", "Cambodia", "Cameroon", "Canada", "Caribbean", "Central African Republic", "Central America", "Central Asia", "Chad", "Channel Islands", "Chile", "China", "China, Hong Kong SAR", "China, Macao SAR", "China, Taiwan Province of China", "Colombia", "Comoros", "Congo", "Costa Rica", "Cote d'Ivoire", "Croatia", "Cuba", "Curacao", "Cyprus", "Czech Republic", "Dem. People's Rep. of Korea", "Dem. Republic of the Congo", "Denmark", "Djibouti", "Dominican Republic", "Eastern Africa", "Eastern Asia", "Eastern Europe", "Ecuador", "Egypt", "El Salvador", "Equatorial Guinea", "Eritrea", "Estonia", "Ethiopia", "Europe", "Fiji", "Finland", "France", "French Guiana", "French Polynesia", "Gabon", "Gambia", "Georgia", "Germany", "Ghana", "Greece", "Grenada", "Guadeloupe", "Guam", "Guatemala", "Guinea", "Guinea-Bissau", "Guyana", "Haiti", "High-income countries", "Honduras", "Hungary", "Iceland", "India", "Indonesia", "Iran (Islamic Republic of)", "Iraq", "Ireland", "Israel", "Italy", "Jamaica", "Japan", "Jordan", "Kazakhstan", "Kenya", "Kiribati", "Kuwait", "Kyrgyzstan", "Lao People's Dem. Republic", "Latin America and the Caribbean", "Latvia", "Least developed countries", "Lebanon", "Lesotho", "Less developed regions", "Less developed regions, excluding China", "Liberia", "Libya", "Lithuania", "Low-income countries", "Lower-middle-income countries", "Luxembourg", "Madagascar", "Malawi", "Malaysia", "Maldives", "Mali", "Malta", "Martinique", "Mauritania", "Mauritius", "Mayotte", "Melanesia", "Mexico", "Micronesia", "Micronesia (Fed. States of)", "Middle-income countries", "Middle Africa", "Mongolia", "Montenegro", "More developed regions", "Morocco", "Mozambique", "Myanmar", "Namibia", "Nepal", "Netherlands", "New Caledonia", "New Zealand", "Nicaragua", "Niger", "Nigeria", "Northern Africa", "Northern America", "Northern Europe", "Norway", "Oceania", "Oman", "Other less developed countries", "Pakistan", "Panama", "Papua New Guinea", "Paraguay", "Peru", "Philippines", "Poland", "Polynesia", "Portugal", "Puerto Rico", "Qatar", "Republic of Korea", "Republic of Moldova", "Reunion", "Romania", "Russian Federation", "Rwanda", "Saint Lucia", "Samoa", "Sao Tome and Principe", "Saudi Arabia", "Senegal", "Serbia", "Seychelles", "Sierra Leone", "Singapore", "Slovakia", "Slovenia", "Solomon Islands", "Somalia", "South-Central Asia", "South-Eastern Asia", "South Africa", "South America", "South Sudan", "Southern Africa", "Southern Asia", "Southern Europe", "Spain", "Sri Lanka", "St. Vincent and the Grenadines", "State of Palestine", "Sub-Saharan Africa", "Sudan", "Suriname", "Swaziland", "Sweden", "Switzerland", "Syrian Arab Republic", "Tajikistan", "TFYR Macedonia", "Thailand", "Timor-Leste", "Togo", "Tonga", "Trinidad and Tobago", "Tunisia", "Turkey", "Turkmenistan", "Uganda", "Ukraine", "United Arab Emirates", "United Kingdom", "United Republic of Tanzania", "United States of America", "United States Virgin Islands", "Upper-middle-income countries", "Uruguay", "Uzbekistan", "Vanuatu", "Venezuela (Bolivarian Republic of)", "Viet Nam", "Western Africa", "Western Asia", "Western Europe", "Western Sahara", "World", "Yemen", "Zambia", "Zimbabwe"), class = "factor"), `1950` = c(7752.118, 1263.171, 8872.247, 4354.882, 46.301, 2895.997, 17150.335, 8177.344, 6936.445, 79.088, 115.614, 37894.68, 1353.506, 210.995, 8628.489, 176.795, 3089.649, 2661.293, 412.533, 53974.726, 68.918, 89.793, 48.001, 7250.999, 17527.243, 2308.923, 7745.003, 4432.716, 4466.498, 13736.997, 178.066, 1326.653, 8075.81, 2502.314, 6142.899, 544112.923, 7561.863, 12340.899, 156.334, 15.141, 807.726, 12183.661, 959.489, 3850.295, 5919.997, 494.014, 8902.619, 2255.221, 4268.27, 2364.65, 3470.162, 2199.897, 225.536, 18128.034, 1142.15, 1100.998, 288.993, 4008.299, 41879.607, 25.479, 60.268, 62.001, 473.3, 3527.004, 271.372, 931.926, 69786.246, 4980.878, 33.05, 7566.002, 76.676, 209.999, 59.65, 3146.073, 3093.651, 406.562, 3221.277, 1487.235, 1973.998, 9337.723, 142.656, 376325.205, 69543.319, 17119.263, 5719.191, 2913.093, 1257.971, 46598.602, 2630.131, 1402.896, 82199.47, 6702.996, 448.861, 6076.757, 10549.469, 19211.386, 152.25, 1740, 1682.916, 1334.618, 733.942, 1949, 930.026, 1113.382, 2567.402, 296.001, 196.482, 4083.554, 2953.871, 6109.907, 73.715, 4708.425, 311.997, 222.001, 660.491, 493.254, 28012.558, 780.2, 2341.003, 394.738, 8985.99, 6313.29, 456.418, 485.274, 8483.321, 10027.047, 100.184, 38.066, 64.824, 47.695, 1908.001, 1294.993, 2559.703, 37859.745, 3265.278, 32, 37542.38, 859.66, 1708.192, 1473.245, 7727.735, 18580.487, 24824.013, 8416.969, 535.429, 433.398, 2218, 24.999, 248.111, 16236.292, 102798.657, 2186.187, 82.783, 67, 60, 3121.336, 2476.638, 6732.256, 36.322, 1944.001, 1022.098, 3436.574, 24809.903, 1473.094, 2264.081, 13683.162, 2746.854, 28069.737, 2582.929, 5733.944, 13.766, 214.999, 273, 7009.913, 4668.088, 3413.329, 1531.502, 20710.356, 1395.458, 47.22, 645.628, 69.59, 3605.31, 21238.496, 1211, 5158.193, 37297.652, 1254.444, 20897.237, 50616.012, 102.235, 7649.766, 157813.04, 26.795, 4284.457, 2238.506, 6945.397, 5481.977, 82.102, 4402.32, 2316.95, 2525149.312, 812988.79, 1712160.522, 228901.723, 168843.911, 171614.868, 666585.791, 549089.107, 12681.946, 66922.702, 26400.57, 49221.876, 15587.911, 70768.664, 17075.654, 38028.823, 164900.344, 511574.182, 50957.44, 220170.535, 78029.913, 108632.979, 142255.68, 10085.345, 2199.497, 113739.434, 1516435.967, 1394017.757, 195724.555, 179679.847, 1158315.256, 155.093, 242.011, 130103.438, 768893.01, 824937.314, 800383.367, 1593830.324, 18130.895, 493443.287)), .Names = c("name", "1950"), class = "data.frame", row.names = c(NA, -241L))
我希望有人能够帮忙。
这段内容与IT技术无关。
tm_bubble()图中，是否可以为大小变量添加固定的间断？ - philiporlandotm_bubble无关。 - www