计算具有列条件的行的净值

Question

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，通过将第 5 列到第 194 列的所有值相加来计算“总计”值。

我的目标是计算净总数，从总数中减去相应的国家列。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。等等等等。

预期的输出应如下所示（示例是暂定的，因为原始 data.frame 很大）：

name	code	cluster	sector	Total	Net total	Afghanistan	Albania
Afghanistan	AFG	Industries	Agriculture	100	92	8	1
Afghanistan	AFG	Industries	Fishing	105	99	6	2
Afghanistan	AFG	Industries	Mining	98	96	2	3
Afghanistan	AFG	Industries	Textiles	101	80	21	4
Afghanistan	AFG	Industries	Wood	90	79	11	5
Afghanistan	AFG	Industries	Petroleum	101	100	1	1
Afghanistan	AFG	Industries	Metal	50	30	20	3

重要的是“Net Total”计算为“Total” - “Afghanistan”，但仅适用于阿富汗行。实际上，另一个国家/地区的行的“Net total”应该计算为“Total” - “another country” 列。

如何编写这种操作？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“名称”列中有 190 个国家/地区列，但只有 171 个不同的国家/地区。

非常感谢您的宝贵时间。

Answer 1

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)))])