我正在尝试计算如何根据多个条件对行求和，但将所有行保留在数据框中，因此只有满足条件的行才具有求和值，所有其他行都具有原始值（来自名为iresult_posPPP的列）。我有多个国家/地区，不同年份，部门等的数据。在我的ISO列为“ ALL”的情况下，我需要此值是iresult_posPPP中所有行的总和，这些行的DataYear，Division，MoreDetails1和ExtraDetails2具有相同的值。
我在下面附加了我的数据框的内容：
Data <- structure(list(ID.x = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Indicator = c("Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre", "Gym and Leisure Centre",
"Gym and Leisure Centre", "Gym and Leisure Centre"), IndicatorID = c(98L,
98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L,
98L, 98L, 98L, 98L, 98L, 98L, 98L), InputA = c(3762.134507, 4447.309316,
4293.110921, 3862.76676, 4071.175351, 4323.016371, 4036.130293,
4450.854575, 4224.807119, 4563, 4888.173223, 4473.037451, 4136.032594,
4429.615323, 4972.768468, 4910.636192, 4947.585664, 4119.657378,
4809.477176, 4135.606089, 4935.381334), InputAName = c("Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym",
"Total number of people using the gym", "Total number of people using the gym"
), InputAUnit = c("#", "#", "#", "#", "#", "#", "#", "#", "#",
"#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#", "#"),
OutputCode = c("GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP"), DataYear = c(2016L,
2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L), Country.x = c("Uzbekistan", "Vanuatu", "Venezuela, RB",
"Vietnam", "Virgin Islands (U.S.)", "West Bank and Gaza",
"Yemen, Rep.", "Zambia", "Zimbabwe", "ALL", "Afghanistan",
"Albania", "Algeria", "American Samoa", "Andorra", "Angola",
"Antigua and Barbuda", "Argentina", "Armenia", "Aruba", "Australia"
), ISO = c("UZB", "VUT", "VEN", "VNM", "VIR", "PSE", "YEM",
"ZMB", "ZWE", "ALL", "AFG", "ALB", "DZA", "ASM", "AND", "AGO",
"ATG", "ARG", "ARM", "ABW", "AUS"), Division = c("Two", "Two",
"Two", "Two", "Two", "Two", "Two", "Two", "Two", "One", "One",
"One", "One", "One", "One", "One", "One", "One", "One", "One",
"One"), FurtherDetails1 = c("fd1b", "fd1b", "fd1b", "fd1b",
"fd1b", "fd1b", "fd1b", "fd1b", "fd1b", "fd1a", "fd1a", "fd1a",
"fd1a", "fd1a", "fd1a", "fd1a", "fd1a", "fd1a", "fd1a", "fd1a",
"fd1a"), FurtherDetails2 = c("fd2b", "fd2b", "fd2b", "fd2b",
"fd2b", "fd2b", "fd2b", "fd2b", "fd2b", "fd2a", "fd2a", "fd2a",
"fd2a", "fd2a", "fd2a", "fd2a", "fd2a", "fd2a", "fd2a", "fd2a",
"fd2a"), ID.y = c(168L, 168L, 168L, 168L, 168L, 168L, 168L,
168L, 168L, 189L, 189L, 189L, 189L, 189L, 189L, 189L, 189L,
189L, 189L, 189L, 189L), Code.x = c("GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP"
), CoefficientYear = c(2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L), Percent = c(-2.69,
-2.69, -2.69, -2.69, -2.69, -2.69, -2.69, -2.69, -2.69, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), CoeffqInflation = c(-0.0269,
-0.0269, -0.0269, -0.0269, -0.0269, -0.0269, -0.0269, -0.0269,
-0.0269, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Method = c("",
"", "", "", "", "", "", "", "", "", "", "", "", "", "", "",
"", "", "", "", ""), ID.x.x = c(248L, 248L, 248L, 248L, 248L,
248L, 248L, 248L, 248L, 248L, 248L, 248L, 248L, 248L, 248L,
248L, 248L, 248L, 248L, 248L, 248L), InputCode = c("GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP"), CoeffqFactor = c(1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), Year = c(2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L, 2017L,
2017L), Type = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), ID.y.y = c(212L,
213L, 214L, 215L, 216L, 217L, 218L, 219L, 220L, 221L, 1L,
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L), Country.y = c("Uzbekistan",
"Vanuatu", "Venezuela, RB", "Vietnam", "Virgin Islands (U.S.)",
"West Bank and Gaza", "Yemen, Rep.", "Zambia", "Zimbabwe",
"ALL", "Afghanistan", "Albania", "Algeria", "American Samoa",
"Andorra", "Angola", "Antigua and Barbuda", "Argentina",
"Armenia", "Aruba", "Australia"), Currency = c("GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP"), CoeffqPPP = c(0.184436278, 0.184436278, 0.367527677,
0.184436278, 0.994525717, 0.184436278, 0.184436278, 0.184436278,
0.112411792, 0, 0.112411792, 0.347344672, 0.367527677, 0.367527677,
0.994525717, 0.264750217, 0.994525717, 0.389806873, 0.188019865,
0.994525717, 0.994525717), Step = c(3, 3, 3, 3, 3, 3, 3,
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3), Coeffq = c(2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717,
2756.10980649717, 2756.10980649717, 2756.10980649717, 2756.10980649717
), CoeffqYear = c("2017", "2017", "2017", "2017", "2017",
"2017", "2017", "2017", "2017", "2017", "2017", "2017", "2017",
"2017", "2017", "2017", "2017", "2017", "2017", "2017", "2017"
), CoeffqUnit = c("GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP", "GBP",
"GBP", "GBP", "GBP", "GBP", "GBP", "GBP"), Step2iresult = c(1.32904727554592,
1.57109861939866, 1.51662503362256, 1.36459757855418, 1.43822197171544,
1.52718971619107, 1.42584162253612, 1.57235105117809, 1.49249538546973,
1.61196860639412, 1.72684237959508, 1.58018758409756, 1.46113405578585,
1.56484787181204, 1.75672729723484, 1.73477786082112, 1.74783098133106,
1.45534919185534, 1.69904146852532, 1.46098338458917, 1.74351956410071
), iresult_pos = c(3564.46552325877, 4213.64007550875, 4067.54352800449,
3659.81038551155, 3857.2688325682, 4095.8776944954, 3824.06510187511,
4216.9990605352, 4002.82852462449, 4442.76248384841, 4759.36721667692,
4355.17049663636, 4027.04589975837, 4312.8925651774, 4841.73333125022,
4781.23827430327, 4817.21410774609, 4011.10217955023, 4682.744853048,
4026.63063339563, 4805.33136843763), iresult_posPPP = c(675.590128629298,
798.631273618818, 1536.26022396863, 693.661294511865, 3942.19818248036,
776.311208628047, 724.793273270513, 799.267918050159, 462.403789458181,
0, 535.008997612704, 1512.74526765823, 1480.05082471057,
1585.10738563022, 4815.22831278442, 1265.8338706505, 4790.8433144487,
1563.55519789396, 880.449055099529, 4004.58771777195, 4779.02562461803
), iresult_pos_m = c(0.00356446552325877, 0.00421364007550875,
0.00406754352800449, 0.00365981038551155, 0.0038572688325682,
0.0040958776944954, 0.00382406510187511, 0.0042169990605352,
0.00400282852462449, 0.00444276248384841, 0.00475936721667692,
0.00435517049663636, 0.00402704589975837, 0.0043128925651774,
0.00484173333125022, 0.00478123827430327, 0.00481721410774609,
0.00401110217955023, 0.004682744853048, 0.00402663063339563,
0.00480533136843763), ID = c(NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA),
StepName = c("Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia", "Avoided cost of Dementia", "Avoided cost of Dementia",
"Avoided cost of Dementia"), ImpactID = c(10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L), Allocation = c(1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), Polarity = c("Positive",
"Positive", "Positive", "Positive", "Positive", "Positive",
"Positive", "Positive", "Positive", "Positive", "Positive",
"Positive", "Positive", "Positive", "Positive", "Positive",
"Positive", "Positive", "Positive", "Positive", "Positive"
), Waterfall = c("Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes"), Int_Ext = c("External",
"External", "External", "External", "External", "External",
"External", "External", "External", "External", "External",
"External", "External", "External", "External", "External",
"External", "External", "External", "External", "External"
), ImpactCode = c("GDF", "GDF", "GDF", "GDF", "GDF", "GDF",
"GDF", "GDF", "GDF", "GDF", "GDF", "GDF", "GDF", "GDF", "GDF",
"GDF", "GDF", "GDF", "GDF", "GDF", "GDF"), ImpactName = c("Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial",
"Government // Direct Financial", "Government // Direct Financial"
), Name = c("Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres", "Gym and Leisure Centres", "Gym and Leisure Centres",
"Gym and Leisure Centres"), Capital = c("Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured", "Manufactured",
"Manufactured", "Manufactured", "Manufactured"), Flow = c("TBC",
"TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC",
"TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC", "TBC",
"TBC", "TBC"), iresult = c(3564.46552325877, 4213.64007550875,
4067.54352800449, 3659.81038551155, 3857.2688325682, 4095.8776944954,
3824.06510187511, 4216.9990605352, 4002.82852462449, 4442.76248384841,
4759.36721667692, 4355.17049663636, 4027.04589975837, 4312.8925651774,
4841.73333125022, 4781.23827430327, 4817.21410774609, 4011.10217955023,
4682.744853048, 4026.63063339563, 4805.33136843763), iresult_m = c(0.00356446552325877,
0.00421364007550875, 0.00406754352800449, 0.00365981038551155,
0.0038572688325682, 0.0040958776944954, 0.00382406510187511,
0.0042169990605352, 0.00400282852462449, 0.00444276248384841,
0.00475936721667692, 0.00435517049663636, 0.00402704589975837,
0.0043128925651774, 0.00484173333125022, 0.00478123827430327,
0.00481721410774609, 0.00401110217955023, 0.004682744853048,
0.00402663063339563, 0.00480533136843763)), row.names = 1760:1780, class = "data.frame")
这是我当前试图运行的代码要点，目前正在考虑一种if语句方法：
Data %>%
mutate(iresult_pos = ifelse(ISO= 'ALL', (sum of the rows in iresult_posPPP where DataYear, Division, FurtherDetails1 and FutherDetails2 are the same), iresult_posPPP)
有没有一种整洁的方法来执行此操作，或者可能缺少一个步骤，因为我一直在绞尽脑汁/绕过堆栈溢出线程，无法想到一种好的方法。任何帮助将不胜感激！
谢谢！
答案 0 :(得分：3)
也许我们需要一个按总数分组
library(dplyr)
Data %>%
group_by(DataYear, Division, FurtherDetails1, FurtherDetails2) %>%
mutate(iresult_pos =sum(iresult_posPPP))
答案 1 :(得分：1)
另一个选择，使用虚拟数据集显示其工作方式：
# create dummy data
data <- data.frame(replicate(10,sample(0:1,1000,rep=TRUE)))
# sum X2, X3, X4, X9 where X1 == 1, store as X11
data <- data %>% mutate(
X11 = rowSums(select_(.,'X2','X3','X4','X9')))