使用列上的条件计算行的净值
Calculating net value of a row with condition on the column
我的数据框有 195 个变量的 2695 个观察值，它的第一个 100x10 象限如下所示：
structure(list(name = c("Afghanistan", "Afghanistan", "Afghanistan",
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan",
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan",
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan",
"Afghanistan", "Afghanistan", "Afghanistan", "Albania", "Albania",
"Albania", "Albania", "Albania", "Albania", "Albania", "Albania",
"Albania", "Albania", "Albania", "Albania", "Albania", "Albania",
"Albania", "Albania", "Albania", "Albania", "Albania", "Albania",
"Albania", "Algeria", "Algeria", "Algeria", "Algeria", "Algeria",
"Algeria", "Algeria", "Algeria", "Algeria", "Algeria", "Algeria",
"Algeria", "Algeria", "Algeria", "Algeria", "Algeria", "Algeria",
"Algeria", "Algeria", "Algeria", "Algeria", "Andorra", "Andorra",
"Andorra", "Andorra", "Andorra", "Andorra", "Andorra", "Andorra",
"Andorra", "Andorra", "Andorra", "Andorra", "Andorra", "Andorra",
"Andorra", "Andorra", "Andorra", "Andorra", "Andorra", "Andorra",
"Andorra", "Angola", "Angola", "Angola", "Angola", "Angola",
"Angola", "Angola", "Angola", "Angola", "Angola", "Angola", "Angola",
"Angola", "Angola", "Angola", "Angola"), code = c("AFG", "AFG",
"AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG",
"AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG",
"AFG", "ALB", "ALB", "ALB", "ALB", "ALB", "ALB", "ALB", "ALB",
"ALB", "ALB", "ALB", "ALB", "ALB", "ALB", "ALB", "ALB", "ALB",
"ALB", "ALB", "ALB", "ALB", "DZA", "DZA", "DZA", "DZA", "DZA",
"DZA", "DZA", "DZA", "DZA", "DZA", "DZA", "DZA", "DZA", "DZA",
"DZA", "DZA", "DZA", "DZA", "DZA", "DZA", "DZA", "AND", "AND",
"AND", "AND", "AND", "AND", "AND", "AND", "AND", "AND", "AND",
"AND", "AND", "AND", "AND", "AND", "AND", "AND", "AND", "AND",
"AND", "AGO", "AGO", "AGO", "AGO", "AGO", "AGO", "AGO", "AGO",
"AGO", "AGO", "AGO", "AGO", "AGO", "AGO", "AGO", "AGO"), cluster = c("Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries"), sector = c("Agriculture",
"Fishing", "Mining and Quarrying", "Textiles and Wearing Apparel",
"Wood and Paper", "Petroleum, Chemical and Non-Metallic Mineral Products",
"Metal Products", "Transport Equipment", "Other Manufacturing",
"Electricity, Gas and Water", "Construction", "Maintenance and Repair",
"Wholesale Trade", "Retail Trade", "Transport", "Post and Telecommunications",
"Public Administration", "Education, Health and Other Services",
"Private Households", "Others", "Re-export & Re-import", "Agriculture",
"Fishing", "Mining and Quarrying", "Textiles and Wearing Apparel",
"Wood and Paper", "Petroleum, Chemical and Non-Metallic Mineral Products",
"Metal Products", "Transport Equipment", "Other Manufacturing",
"Electricity, Gas and Water", "Construction", "Maintenance and Repair",
"Wholesale Trade", "Retail Trade", "Transport", "Post and Telecommunications",
"Public Administration", "Education, Health and Other Services",
"Private Households", "Others", "Re-export & Re-import", "Agriculture",
"Fishing", "Mining and Quarrying", "Textiles and Wearing Apparel",
"Wood and Paper", "Petroleum, Chemical and Non-Metallic Mineral Products",
"Metal Products", "Transport Equipment", "Other Manufacturing",
"Electricity, Gas and Water", "Construction", "Maintenance and Repair",
"Wholesale Trade", "Retail Trade", "Transport", "Post and Telecommunications",
"Public Administration", "Education, Health and Other Services",
"Private Households", "Others", "Re-export & Re-import", "Agriculture",
"Fishing", "Mining and Quarrying", "Textiles and Wearing Apparel",
"Wood and Paper", "Petroleum, Chemical and Non-Metallic Mineral Products",
"Metal Products", "Transport Equipment", "Other Manufacturing",
"Electricity, Gas and Water", "Construction", "Maintenance and Repair",
"Wholesale Trade", "Retail Trade", "Transport", "Post and Telecommunications",
"Public Administration", "Education, Health and Other Services",
"Private Households", "Others", "Re-export & Re-import", "Agriculture",
"Fishing", "Mining and Quarrying", "Textiles and Wearing Apparel",
"Wood and Paper", "Petroleum, Chemical and Non-Metallic Mineral Products",
"Metal Products", "Transport Equipment", "Other Manufacturing",
"Electricity, Gas and Water", "Construction", "Maintenance and Repair",
"Wholesale Trade", "Retail Trade", "Transport", "Post and Telecommunications"
), Total = c(313056.134909551, 1269.32391427775, 6702.10091092139,
20822.9824174335, 3277.35295343427, 7075.57751406419, 5809.54856404444,
6374.97667034069, 6573.16606009056, 1520.47502801121, 10658.977916637,
7414.61509425962, 12290.7967126299, 11398.2992559452, 40272.8802077045,
11195.0970347162, 9608.34006394526, 15892.9447789989, 7520.16190432492,
1309.97105807522, 5863.24413932713, 84798.6701470358, 5287.89543614681,
7019.68464118458, 207555.54211305, 42610.6785141417, 57455.2766420949,
50880.0662736183, 8562.70774978471, 35615.0812816442, 3209.61081796767,
13425.7891844031, 10172.0898252207, 25135.1384491464, 10171.5875982993,
24546.3331711539, 20219.2191239651, 12492.0819211004, 19829.1935665882,
10538.3674396562, 860.212193244676, 10441.8877791697, 109944.342344373,
10130.4848607536, 38399430.0758622, 54346.1819763583, 60588.7451272658,
10333339.8435353, 166914.291830525, 15106.291762901, 6992.51143191634,
2096.00364208704, 178873.707038741, 32430.7567673094, 828119.280778115,
172465.345148761, 2608478.34637721, 975944.341821359, 129890.525779898,
781459.183975379, 13967.9236719995, 1460.95459419176, 1239.25223987981,
2006.16751711888, 579.408605356926, 567.392719967148, 10646.2491986802,
15849.8055842179, 15533.2886586566, 9405.82927410387, 30004.8039316661,
5970.2054602464, 959.45168395392, 10588.6969072962, 7797.41788929008,
11103.6195368155, 11422.3263920103, 11030.0357536182, 11005.3874434708,
10256.8119809788, 11665.7731598811, 6780.08819348487, 939.441815889167,
10049.3382667714, 17194.9845438908, 2105.35872638104, 15962587.4508949,
2681.40283207019, 8290.02901841903, 199873.949286869, 14846.7790432671,
10800.3647727473, 7104.21565574377, 1878.9292703595, 370849.323130881,
22336.8687091073, 189194.987574215, 62353.0494427796, 2465448.35656496,
443041.875133795), Afghanistan = c(304848.2, 1244.815, 5992.698,
18010.06, 2975.027, 6331.944, 5160.831, 5384.333, 5747.278, 1392.815,
10046.36, 6304.916, 11137.87, 10923.54, 36934.41, 10822.21, 8730.08,
15105.91, 5966.117, 1117.582, 26.16316, 1.83796, 0.4187321, 0.7053242,
16.82224, 2.368265, 2.229667, 2.969031, 0.4339618, 3.330972,
0.1409332, 0.3907028, 2.256146, 0.4993595, 0.2239593, 0.8452328,
0.4606935, 0.2311659, 0.4483911, 3.229056, 0.1869243, 14.26183,
0.6368992, 0.1774615, 855.0543, 2.059841, 0.9784637, 326.125,
2.480306, 0.6295102, 0.2723101, 0.009939627, 2.58328, 0.7858758,
4.796921, 2.209655, 29.30604, 7.516025, 2.180713, 15.07286, 1.155397,
0.03922217, 0.6618161, 0.3569212, 0.5384865, 0.156222, 3.320798,
2.33509, 1.42815, 1.389516, 3.446843, 1.356888, 0.1334601, 0.510716,
2.723687, 0.3888807, 0.4487993, 0.8531269, 0.6789875, 0.4435601,
0.4159068, 3.614623, 0.3341556, 7.505752, 0.1033085, 0.08569755,
972.7443, 0.1132736, 0.1158019, 2.354941, 0.2283046, 0.4196883,
0.2569963, 0.01133495, 5.883291, 1.139181, 1.037388, 0.6386013,
38.7435, 3.419991), Albania = c(3.535969, 0.03840783, 0.3863751,
0.9954086, 0.08775854, 0.2030882, 1.391618, 0.5245008, 0.6190842,
0.05073775, 0.3891475, 0.6727891, 0.1539272, 0.1706042, 0.5426898,
0.1037151, 0.1823552, 0.2115925, 1.069002, 0.1062371, 3.949615,
79527.31, 5061.744, 5606.964, 140981.7, 27107.64, 33462.2, 31183.07,
4460.67, 21130.07, 2729.427, 10630.79, 8044.345, 22253.97, 9347.96,
18225.96, 18097.29, 10439.65, 17669.2, 7737.212, 658.327, 2512.097,
0.04379642, 0.007626944, 120.1914, 0.8615488, 0.4047151, 38.60637,
1.123844, 0.1297725, 0.09295459, 0.002695269, 0.5615575, 0.7208675,
1.350622, 0.3834361, 6.671941, 2.181208, 0.3419616, 1.298375,
0.6230328, 0.02060596, 0.7954482, 0.1158716, 0.1792077, 0.05296581,
0.9807616, 0.7176638, 0.4338842, 0.4336918, 1.129224, 0.4319445,
0.04283256, 0.1534184, 0.7950113, 0.1193977, 0.1371983, 0.2555027,
0.1975643, 0.1304942, 0.1132505, 1.009906, 0.1040789, 1.761093,
0.02053985, 0.01377083, 54.03197, 0.05894175, 0.06595316, 0.9770419,
0.1309219, 0.09237173, 0.1061737, 0.004385261, 1.031491, 0.6977874,
0.4370498, 0.1476074, 8.667269, 1.531756), Algeria = c(5.240079,
0.02104366, 0.5161704, 1.742304, 0.1884929, 0.638416, 0.3971941,
0.5894792, 0.5243543, 0.09268831, 0.3778295, 0.8218906, 0.3903957,
0.2782294, 1.946016, 0.2005679, 0.4673061, 0.46685, 1.315667,
0.1372425, 5.728609, 14.15439, 0.6593845, 4.430993, 153.2115,
35.62573, 92.96048, 52.28874, 8.492265, 32.08374, 1.774228, 7.498232,
4.302572, 5.717841, 1.817346, 18.18068, 4.45664, 5.554349, 5.279886,
5.870353, 0.4191698, 17.09926, 107132.8, 9887.484, 33714360,
37499.33, 44093.85, 7940498, 117407.7, 9193.506, 4680.662, 2018.159,
152113.8, 25992.47, 691562.8, 151294.7, 2163505, 848482.5, 102530.9,
690073.7, 11346.21, 1308.455, 98.49957, 1.596688, 0.8939674,
0.5979496, 12.63072, 17.78408, 26.27299, 10.60669, 36.0613, 7.210763,
0.8374489, 4.829583, 4.684588, 2.309686, 2.157866, 8.470586,
3.90022, 4.690984, 3.752759, 5.94401, 0.658466, 9.524497, 0.4095283,
0.09161661, 2198.32, 0.6536236, 1.393105, 58.27179, 3.16544,
3.330465, 1.636288, 0.06272295, 31.69208, 1.537006, 6.454557,
2.202606, 287.937, 26.93717), Andorra = c(2.046408, 0.03199265,
0.1913253, 0.6384646, 0.04210553, 0.05989684, 0.08395811, 0.08547009,
0.1640007, 0.02629837, 0.06544481, 0.5198038, 0.0704934, 0.07354977,
0.2318274, 0.05006094, 0.05805839, 0.07343344, 0.8471854, 0.08000277,
3.281725, 1.166039, 0.1937104, 0.5849786, 14.64168, 2.014269,
1.634169, 2.62503, 0.4598703, 3.004348, 0.1156719, 0.3324458,
2.258714, 0.4214368, 0.1890398, 0.6775366, 0.4166179, 0.1967594,
0.2213797, 3.279177, 0.1841389, 18.42281, 0.06572487, 0.0151666,
241.5491, 0.734705, 0.5635472, 68.69543, 3.025981, 0.328492,
0.1079413, 0.004644561, 1.220245, 0.776872, 4.995991, 0.5595545,
22.07305, 5.319428, 0.9709488, 2.607332, 0.4908999, 0.02019178,
0.5850328, 1497.731, 217.3481, 378.3719, 6415.105, 10549.02,
10058.02, 6282.365, 16703.89, 3597.702, 744.6967, 9176.902, 5960.622,
10163.73, 10653.15, 8799.109, 9645.094, 8923.656, 10560.27, 4362.44,
687.0441, 5951.223, 0.01764571, 0.01243527, 41.01675, 0.04743286,
0.05422601, 0.7896524, 0.1068679, 0.07563721, 0.08683252, 0.003704872,
0.8285007, 0.5872343, 0.3658586, 0.1194013, 7.110707, 1.272627
), Angola = c(7.126427, 0.02126276, 0.7013776, 2.584582, 0.2207993,
0.6455885, 0.5102651, 0.673658, 0.7199301, 0.1172209, 0.4537595,
1.497391, 0.4881724, 0.3670951, 2.803086, 0.2650796, 0.6734943,
0.5744068, 2.549689, 0.2411082, 13.97644, 3.896676, 0.5745994,
1.517034, 45.23805, 6.866533, 8.479498, 9.423369, 1.715862, 9.02622,
0.3268822, 1.231526, 4.494482, 1.333423, 0.5345557, 2.800145,
1.197053, 0.8376675, 1.132491, 6.272173, 0.3792077, 28.0768,
1.509137, 0.1199938, 2864.661, 11.52246, 6.664335, 1731.045,
22.18162, 2.835002, 1.308098, 0.05257571, 13.34905, 4.500684,
29.18065, 8.044516, 211.2769, 45.41144, 12.96821, 51.85862, 4.30742,
0.1704663, 3.274468, 0.9248837, 1.163733, 0.4030822, 7.497041,
6.648192, 7.311064, 4.187048, 11.8977, 3.649344, 0.4054804, 1.667877,
5.738257, 1.079308, 1.176356, 3.087699, 1.857479, 1.600233, 1.335246,
7.249851, 0.7536257, 12.16895, 16902.28, 2053.868, 14629320,
2176.549, 7247.814, 167657.8, 12729.29, 8228.971, 5893.646, 1834.933,
348980.5, 21047.25, 182549, 60673.71, 2279856, 421157.8)), class = "data.frame", row.names = c("V2",
"V3", "V4", "V6", "V7", "V8", "V9", "V11", "V12", "V14", "V15",
"V16", "V17", "V18", "V20", "V21", "V23", "V24", "V25", "V26",
"V27", "V28", "V29", "V30", "V32", "V33", "V34", "V35", "V37",
"V38", "V40", "V41", "V42", "V43", "V44", "V46", "V47", "V49",
"V50", "V51", "V52", "V53", "V54", "V55", "V56", "V58", "V59",
"V60", "V61", "V63", "V64", "V66", "V67", "V68", "V69", "V70",
"V72", "V73", "V75", "V76", "V77", "V78", "V79", "V80", "V81",
"V82", "V84", "V85", "V86", "V87", "V89", "V90", "V92", "V93",
"V94", "V95", "V96", "V98", "V99", "V101", "V102", "V103", "V104",
"V105", "V106", "V107", "V108", "V110", "V111", "V112", "V113",
"V115", "V116", "V118", "V119", "V120", "V121", "V122", "V124",
"V125"))
如您所见，一个国家有多行但只有一列。对于每一行，“总计”值是通过将第 5 列到第 194 列的所有值相加计算得出的。
我的目标是计算净总计，从总计中减去相应的国家/地区列。例如，前 26 行分配给阿富汗。我想从他们的“总计”中减去第 5 列的值（对应于同一个国家）。第二个 26 分配给阿尔巴尼亚，因此减法必须发生在“总计”和第 6 列之间。 Etc.Etc.
预期输出应如下所示（示例是暂定的，因为原始 data.frame 很大）：
姓名
代码
集群
部门
总计
净总计
阿富汗
阿尔巴尼亚
阿富汗
AFG
行业
农业
100
92
8
1
阿富汗
AFG
行业
钓鱼
105
99
6
2
阿富汗
AFG
行业
采矿
98
96
2
3
阿富汗
AFG
行业
纺织品
101
80
21
4
阿富汗
AFG
行业
木材
90
79
11
5
阿富汗
AFG
行业
石油
101
100
1
1
阿富汗
AFG
行业
金属
50
30
20
3
重要的是“净总计”计算为“总计”-“阿富汗”，但仅适用于阿富汗行。事实上，另一个国家行的“净总数”应该计算为“总计”-“另一个国家”列。
如何编写此类操作的代码？我更喜欢将减法链接到国家名称而不是列号的代码，因为我注意到有 190 个国家列，但“名称”列中只有 171 个不同的国家。
非常感谢您的宝贵时间。
你可以试试下面的代码-
df$net_total <- df$Total - as.numeric(df[cbind(1:nrow(df), match(df$name, names(df)))])
我的数据框有 195 个变量的 2695 个观察值，它的第一个 100x10 象限如下所示：
structure(list(name = c("Afghanistan", "Afghanistan", "Afghanistan",
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan",
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan",
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan",
"Afghanistan", "Afghanistan", "Afghanistan", "Albania", "Albania",
"Albania", "Albania", "Albania", "Albania", "Albania", "Albania",
"Albania", "Albania", "Albania", "Albania", "Albania", "Albania",
"Albania", "Albania", "Albania", "Albania", "Albania", "Albania",
"Albania", "Algeria", "Algeria", "Algeria", "Algeria", "Algeria",
"Algeria", "Algeria", "Algeria", "Algeria", "Algeria", "Algeria",
"Algeria", "Algeria", "Algeria", "Algeria", "Algeria", "Algeria",
"Algeria", "Algeria", "Algeria", "Algeria", "Andorra", "Andorra",
"Andorra", "Andorra", "Andorra", "Andorra", "Andorra", "Andorra",
"Andorra", "Andorra", "Andorra", "Andorra", "Andorra", "Andorra",
"Andorra", "Andorra", "Andorra", "Andorra", "Andorra", "Andorra",
"Andorra", "Angola", "Angola", "Angola", "Angola", "Angola",
"Angola", "Angola", "Angola", "Angola", "Angola", "Angola", "Angola",
"Angola", "Angola", "Angola", "Angola"), code = c("AFG", "AFG",
"AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG",
"AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG", "AFG",
"AFG", "ALB", "ALB", "ALB", "ALB", "ALB", "ALB", "ALB", "ALB",
"ALB", "ALB", "ALB", "ALB", "ALB", "ALB", "ALB", "ALB", "ALB",
"ALB", "ALB", "ALB", "ALB", "DZA", "DZA", "DZA", "DZA", "DZA",
"DZA", "DZA", "DZA", "DZA", "DZA", "DZA", "DZA", "DZA", "DZA",
"DZA", "DZA", "DZA", "DZA", "DZA", "DZA", "DZA", "AND", "AND",
"AND", "AND", "AND", "AND", "AND", "AND", "AND", "AND", "AND",
"AND", "AND", "AND", "AND", "AND", "AND", "AND", "AND", "AND",
"AND", "AGO", "AGO", "AGO", "AGO", "AGO", "AGO", "AGO", "AGO",
"AGO", "AGO", "AGO", "AGO", "AGO", "AGO", "AGO", "AGO"), cluster = c("Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries", "Industries",
"Industries", "Industries", "Industries", "Industries"), sector = c("Agriculture",
"Fishing", "Mining and Quarrying", "Textiles and Wearing Apparel",
"Wood and Paper", "Petroleum, Chemical and Non-Metallic Mineral Products",
"Metal Products", "Transport Equipment", "Other Manufacturing",
"Electricity, Gas and Water", "Construction", "Maintenance and Repair",
"Wholesale Trade", "Retail Trade", "Transport", "Post and Telecommunications",
"Public Administration", "Education, Health and Other Services",
"Private Households", "Others", "Re-export & Re-import", "Agriculture",
"Fishing", "Mining and Quarrying", "Textiles and Wearing Apparel",
"Wood and Paper", "Petroleum, Chemical and Non-Metallic Mineral Products",
"Metal Products", "Transport Equipment", "Other Manufacturing",
"Electricity, Gas and Water", "Construction", "Maintenance and Repair",
"Wholesale Trade", "Retail Trade", "Transport", "Post and Telecommunications",
"Public Administration", "Education, Health and Other Services",
"Private Households", "Others", "Re-export & Re-import", "Agriculture",
"Fishing", "Mining and Quarrying", "Textiles and Wearing Apparel",
"Wood and Paper", "Petroleum, Chemical and Non-Metallic Mineral Products",
"Metal Products", "Transport Equipment", "Other Manufacturing",
"Electricity, Gas and Water", "Construction", "Maintenance and Repair",
"Wholesale Trade", "Retail Trade", "Transport", "Post and Telecommunications",
"Public Administration", "Education, Health and Other Services",
"Private Households", "Others", "Re-export & Re-import", "Agriculture",
"Fishing", "Mining and Quarrying", "Textiles and Wearing Apparel",
"Wood and Paper", "Petroleum, Chemical and Non-Metallic Mineral Products",
"Metal Products", "Transport Equipment", "Other Manufacturing",
"Electricity, Gas and Water", "Construction", "Maintenance and Repair",
"Wholesale Trade", "Retail Trade", "Transport", "Post and Telecommunications",
"Public Administration", "Education, Health and Other Services",
"Private Households", "Others", "Re-export & Re-import", "Agriculture",
"Fishing", "Mining and Quarrying", "Textiles and Wearing Apparel",
"Wood and Paper", "Petroleum, Chemical and Non-Metallic Mineral Products",
"Metal Products", "Transport Equipment", "Other Manufacturing",
"Electricity, Gas and Water", "Construction", "Maintenance and Repair",
"Wholesale Trade", "Retail Trade", "Transport", "Post and Telecommunications"
), Total = c(313056.134909551, 1269.32391427775, 6702.10091092139,
20822.9824174335, 3277.35295343427, 7075.57751406419, 5809.54856404444,
6374.97667034069, 6573.16606009056, 1520.47502801121, 10658.977916637,
7414.61509425962, 12290.7967126299, 11398.2992559452, 40272.8802077045,
11195.0970347162, 9608.34006394526, 15892.9447789989, 7520.16190432492,
1309.97105807522, 5863.24413932713, 84798.6701470358, 5287.89543614681,
7019.68464118458, 207555.54211305, 42610.6785141417, 57455.2766420949,
50880.0662736183, 8562.70774978471, 35615.0812816442, 3209.61081796767,
13425.7891844031, 10172.0898252207, 25135.1384491464, 10171.5875982993,
24546.3331711539, 20219.2191239651, 12492.0819211004, 19829.1935665882,
10538.3674396562, 860.212193244676, 10441.8877791697, 109944.342344373,
10130.4848607536, 38399430.0758622, 54346.1819763583, 60588.7451272658,
10333339.8435353, 166914.291830525, 15106.291762901, 6992.51143191634,
2096.00364208704, 178873.707038741, 32430.7567673094, 828119.280778115,
172465.345148761, 2608478.34637721, 975944.341821359, 129890.525779898,
781459.183975379, 13967.9236719995, 1460.95459419176, 1239.25223987981,
2006.16751711888, 579.408605356926, 567.392719967148, 10646.2491986802,
15849.8055842179, 15533.2886586566, 9405.82927410387, 30004.8039316661,
5970.2054602464, 959.45168395392, 10588.6969072962, 7797.41788929008,
11103.6195368155, 11422.3263920103, 11030.0357536182, 11005.3874434708,
10256.8119809788, 11665.7731598811, 6780.08819348487, 939.441815889167,
10049.3382667714, 17194.9845438908, 2105.35872638104, 15962587.4508949,
2681.40283207019, 8290.02901841903, 199873.949286869, 14846.7790432671,
10800.3647727473, 7104.21565574377, 1878.9292703595, 370849.323130881,
22336.8687091073, 189194.987574215, 62353.0494427796, 2465448.35656496,
443041.875133795), Afghanistan = c(304848.2, 1244.815, 5992.698,
18010.06, 2975.027, 6331.944, 5160.831, 5384.333, 5747.278, 1392.815,
10046.36, 6304.916, 11137.87, 10923.54, 36934.41, 10822.21, 8730.08,
15105.91, 5966.117, 1117.582, 26.16316, 1.83796, 0.4187321, 0.7053242,
16.82224, 2.368265, 2.229667, 2.969031, 0.4339618, 3.330972,
0.1409332, 0.3907028, 2.256146, 0.4993595, 0.2239593, 0.8452328,
0.4606935, 0.2311659, 0.4483911, 3.229056, 0.1869243, 14.26183,
0.6368992, 0.1774615, 855.0543, 2.059841, 0.9784637, 326.125,
2.480306, 0.6295102, 0.2723101, 0.009939627, 2.58328, 0.7858758,
4.796921, 2.209655, 29.30604, 7.516025, 2.180713, 15.07286, 1.155397,
0.03922217, 0.6618161, 0.3569212, 0.5384865, 0.156222, 3.320798,
2.33509, 1.42815, 1.389516, 3.446843, 1.356888, 0.1334601, 0.510716,
2.723687, 0.3888807, 0.4487993, 0.8531269, 0.6789875, 0.4435601,
0.4159068, 3.614623, 0.3341556, 7.505752, 0.1033085, 0.08569755,
972.7443, 0.1132736, 0.1158019, 2.354941, 0.2283046, 0.4196883,
0.2569963, 0.01133495, 5.883291, 1.139181, 1.037388, 0.6386013,
38.7435, 3.419991), Albania = c(3.535969, 0.03840783, 0.3863751,
0.9954086, 0.08775854, 0.2030882, 1.391618, 0.5245008, 0.6190842,
0.05073775, 0.3891475, 0.6727891, 0.1539272, 0.1706042, 0.5426898,
0.1037151, 0.1823552, 0.2115925, 1.069002, 0.1062371, 3.949615,
79527.31, 5061.744, 5606.964, 140981.7, 27107.64, 33462.2, 31183.07,
4460.67, 21130.07, 2729.427, 10630.79, 8044.345, 22253.97, 9347.96,
18225.96, 18097.29, 10439.65, 17669.2, 7737.212, 658.327, 2512.097,
0.04379642, 0.007626944, 120.1914, 0.8615488, 0.4047151, 38.60637,
1.123844, 0.1297725, 0.09295459, 0.002695269, 0.5615575, 0.7208675,
1.350622, 0.3834361, 6.671941, 2.181208, 0.3419616, 1.298375,
0.6230328, 0.02060596, 0.7954482, 0.1158716, 0.1792077, 0.05296581,
0.9807616, 0.7176638, 0.4338842, 0.4336918, 1.129224, 0.4319445,
0.04283256, 0.1534184, 0.7950113, 0.1193977, 0.1371983, 0.2555027,
0.1975643, 0.1304942, 0.1132505, 1.009906, 0.1040789, 1.761093,
0.02053985, 0.01377083, 54.03197, 0.05894175, 0.06595316, 0.9770419,
0.1309219, 0.09237173, 0.1061737, 0.004385261, 1.031491, 0.6977874,
0.4370498, 0.1476074, 8.667269, 1.531756), Algeria = c(5.240079,
0.02104366, 0.5161704, 1.742304, 0.1884929, 0.638416, 0.3971941,
0.5894792, 0.5243543, 0.09268831, 0.3778295, 0.8218906, 0.3903957,
0.2782294, 1.946016, 0.2005679, 0.4673061, 0.46685, 1.315667,
0.1372425, 5.728609, 14.15439, 0.6593845, 4.430993, 153.2115,
35.62573, 92.96048, 52.28874, 8.492265, 32.08374, 1.774228, 7.498232,
4.302572, 5.717841, 1.817346, 18.18068, 4.45664, 5.554349, 5.279886,
5.870353, 0.4191698, 17.09926, 107132.8, 9887.484, 33714360,
37499.33, 44093.85, 7940498, 117407.7, 9193.506, 4680.662, 2018.159,
152113.8, 25992.47, 691562.8, 151294.7, 2163505, 848482.5, 102530.9,
690073.7, 11346.21, 1308.455, 98.49957, 1.596688, 0.8939674,
0.5979496, 12.63072, 17.78408, 26.27299, 10.60669, 36.0613, 7.210763,
0.8374489, 4.829583, 4.684588, 2.309686, 2.157866, 8.470586,
3.90022, 4.690984, 3.752759, 5.94401, 0.658466, 9.524497, 0.4095283,
0.09161661, 2198.32, 0.6536236, 1.393105, 58.27179, 3.16544,
3.330465, 1.636288, 0.06272295, 31.69208, 1.537006, 6.454557,
2.202606, 287.937, 26.93717), Andorra = c(2.046408, 0.03199265,
0.1913253, 0.6384646, 0.04210553, 0.05989684, 0.08395811, 0.08547009,
0.1640007, 0.02629837, 0.06544481, 0.5198038, 0.0704934, 0.07354977,
0.2318274, 0.05006094, 0.05805839, 0.07343344, 0.8471854, 0.08000277,
3.281725, 1.166039, 0.1937104, 0.5849786, 14.64168, 2.014269,
1.634169, 2.62503, 0.4598703, 3.004348, 0.1156719, 0.3324458,
2.258714, 0.4214368, 0.1890398, 0.6775366, 0.4166179, 0.1967594,
0.2213797, 3.279177, 0.1841389, 18.42281, 0.06572487, 0.0151666,
241.5491, 0.734705, 0.5635472, 68.69543, 3.025981, 0.328492,
0.1079413, 0.004644561, 1.220245, 0.776872, 4.995991, 0.5595545,
22.07305, 5.319428, 0.9709488, 2.607332, 0.4908999, 0.02019178,
0.5850328, 1497.731, 217.3481, 378.3719, 6415.105, 10549.02,
10058.02, 6282.365, 16703.89, 3597.702, 744.6967, 9176.902, 5960.622,
10163.73, 10653.15, 8799.109, 9645.094, 8923.656, 10560.27, 4362.44,
687.0441, 5951.223, 0.01764571, 0.01243527, 41.01675, 0.04743286,
0.05422601, 0.7896524, 0.1068679, 0.07563721, 0.08683252, 0.003704872,
0.8285007, 0.5872343, 0.3658586, 0.1194013, 7.110707, 1.272627
), Angola = c(7.126427, 0.02126276, 0.7013776, 2.584582, 0.2207993,
0.6455885, 0.5102651, 0.673658, 0.7199301, 0.1172209, 0.4537595,
1.497391, 0.4881724, 0.3670951, 2.803086, 0.2650796, 0.6734943,
0.5744068, 2.549689, 0.2411082, 13.97644, 3.896676, 0.5745994,
1.517034, 45.23805, 6.866533, 8.479498, 9.423369, 1.715862, 9.02622,
0.3268822, 1.231526, 4.494482, 1.333423, 0.5345557, 2.800145,
1.197053, 0.8376675, 1.132491, 6.272173, 0.3792077, 28.0768,
1.509137, 0.1199938, 2864.661, 11.52246, 6.664335, 1731.045,
22.18162, 2.835002, 1.308098, 0.05257571, 13.34905, 4.500684,
29.18065, 8.044516, 211.2769, 45.41144, 12.96821, 51.85862, 4.30742,
0.1704663, 3.274468, 0.9248837, 1.163733, 0.4030822, 7.497041,
6.648192, 7.311064, 4.187048, 11.8977, 3.649344, 0.4054804, 1.667877,
5.738257, 1.079308, 1.176356, 3.087699, 1.857479, 1.600233, 1.335246,
7.249851, 0.7536257, 12.16895, 16902.28, 2053.868, 14629320,
2176.549, 7247.814, 167657.8, 12729.29, 8228.971, 5893.646, 1834.933,
348980.5, 21047.25, 182549, 60673.71, 2279856, 421157.8)), class = "data.frame", row.names = c("V2",
"V3", "V4", "V6", "V7", "V8", "V9", "V11", "V12", "V14", "V15",
"V16", "V17", "V18", "V20", "V21", "V23", "V24", "V25", "V26",
"V27", "V28", "V29", "V30", "V32", "V33", "V34", "V35", "V37",
"V38", "V40", "V41", "V42", "V43", "V44", "V46", "V47", "V49",
"V50", "V51", "V52", "V53", "V54", "V55", "V56", "V58", "V59",
"V60", "V61", "V63", "V64", "V66", "V67", "V68", "V69", "V70",
"V72", "V73", "V75", "V76", "V77", "V78", "V79", "V80", "V81",
"V82", "V84", "V85", "V86", "V87", "V89", "V90", "V92", "V93",
"V94", "V95", "V96", "V98", "V99", "V101", "V102", "V103", "V104",
"V105", "V106", "V107", "V108", "V110", "V111", "V112", "V113",
"V115", "V116", "V118", "V119", "V120", "V121", "V122", "V124",
"V125"))
如您所见，一个国家有多行但只有一列。对于每一行，“总计”值是通过将第 5 列到第 194 列的所有值相加计算得出的。
我的目标是计算净总计，从总计中减去相应的国家/地区列。例如，前 26 行分配给阿富汗。我想从他们的“总计”中减去第 5 列的值（对应于同一个国家）。第二个 26 分配给阿尔巴尼亚，因此减法必须发生在“总计”和第 6 列之间。 Etc.Etc.
预期输出应如下所示（示例是暂定的，因为原始 data.frame 很大）：
| 姓名 | 代码 | 集群 | 部门 | 总计 | 净总计 | 阿富汗 | 阿尔巴尼亚 |
|---|---|---|---|---|---|---|---|
| 阿富汗 | AFG | 行业 | 农业 | 100 | 92 | 8 | 1 |
| 阿富汗 | AFG | 行业 | 钓鱼 | 105 | 99 | 6 | 2 |
| 阿富汗 | AFG | 行业 | 采矿 | 98 | 96 | 2 | 3 |
| 阿富汗 | AFG | 行业 | 纺织品 | 101 | 80 | 21 | 4 |
| 阿富汗 | AFG | 行业 | 木材 | 90 | 79 | 11 | 5 |
| 阿富汗 | AFG | 行业 | 石油 | 101 | 100 | 1 | 1 |
| 阿富汗 | AFG | 行业 | 金属 | 50 | 30 | 20 | 3 |
重要的是“净总计”计算为“总计”-“阿富汗”，但仅适用于阿富汗行。事实上，另一个国家行的“净总数”应该计算为“总计”-“另一个国家”列。
如何编写此类操作的代码？我更喜欢将减法链接到国家名称而不是列号的代码，因为我注意到有 190 个国家列，但“名称”列中只有 171 个不同的国家。
非常感谢您的宝贵时间。
你可以试试下面的代码-
df$net_total <- df$Total - as.numeric(df[cbind(1:nrow(df), match(df$name, names(df)))])