我的数据类似于以下示例：
[[1]]
KRW.LOW.1 KRW.LOW.1.1 KRW.50D KRW.LOW.1.2
2014-08-11 -1 1 1 5
2014-08-12 -1 1 1 10
[[2]]]
EUR.CLOSE EUR.CLOSE.1 EUR.50D EUR.CLOSE.2
2014-08-29 -1 -1 1 3
2014-09-01 -1 1 1 1
2014-09-02 0 -1 0 2
这是一个数据框列表。我想根据前三列的条件对第4行（VAR.CLOSE.2）中的元素求和。条件是：
换句话说，作为一个说明性示例，如果我只是检查单个数据帧，我想要sum(x[which(x[,1]!=0 | x[,2]>0 | x[,3]!=0]), 4)
所以在上面给出的例子中，我想得到以下计算：
[[1]]
KRW
ReturnSum 15
[[2]]
EUR
ReturnSum 5
我们从总和前两行得到5欧元，因为最后一行不满足3个条件中的任何一个。特别是条件Data[[2]][3,1] != 0 Data[[2]][3,3] != 0都失败了Data[[2]][3,2]>0
我尝试用
实现这个目标i <- 1:length(FlaggingTrend)
SumReturns <- lapply(FlaggingTrend[[i]], function(x) sum(x[which(x[,2]!=0|x[,3]>0|x[,4]!=0),4]))
其中FlaggingTrend对应于上面发布的数据。但是，这会返回一个零列表。
我将附上以下数据的样本输入：
list(structure(list(EUR.CLOSE = c(-1, -1, -1, 0, 1, 0, 0, -1,
0, 1), EUR.CLOSE.1 = c(1, -1, -1, 1, 1, 1, 1, -1, -1, -1), EUR.50D = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), EUR.CLOSE.2 = c(-0.0011268664916733,
-0.00423709498833686, -0.00188893142678216, 0.00217196364717242,
0.00686254162079234, -0.00544858088184653, -0.000188412624203348,
-0.00737591996472312, 0.00208590196044455, 0.00227057808051545
)), .Names = c("EUR.CLOSE", "EUR.CLOSE.1", "EUR.50D", "EUR.CLOSE.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14", "2017-02-15",
"2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21", "2017-02-22",
"2017-02-23"), class = "data.frame"), structure(list(JPY.CLOSE = c(0,
0, 1, 0, -1, -1, 0, 1, 0, -1), JPY.CLOSE.1 = c(-1, -1, -1, -1,
-1, -1, -1, -1, -1, -1), JPY.50D = c(1, 1, 1, 1, 1, 1, 1, 1,
1, 1), JPY.CLOSE.2 = c(-0.000264935754629825, 0.00458231327013969,
0.00456141141766331, -0.000875580127735809, -0.00809151292488242,
-0.00353857410990255, 0.00230149698827908, 0.00511510066677001,
-0.00326005839636956, -0.00619690368354142)), .Names = c("JPY.CLOSE",
"JPY.CLOSE.1", "JPY.50D", "JPY.CLOSE.2"), row.names = c("2017-02-10",
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17",
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(GBP.CLOSE = c(0, 1, 0, 0, 1, -1, 0, 0, 0,
1), GBP.CLOSE.1 = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), GBP.50D = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), GBP.CLOSE.2 = c(-0.00048023051987453,
0.00279809911944895, -0.00464112219813048, -0.000561594944360089,
0.0022444899202175, -0.00618451029481418, 0.00410050825810596,
0.000802053299332334, -0.00184568523285542, 0.00847801606899046
)), .Names = c("GBP.CLOSE", "GBP.CLOSE.1", "GBP.50D", "GBP.CLOSE.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
CHF.OPEN = c(1, 0, 0, 0, -1, 0, 0, 1, 0, -1), CHF.OPEN.1 = c(-1,
-1, -1, -1, -1, -1, -1, -1, 1, -1), CHF50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), CHF.OPEN.2 = c(0.000698567964139939,
0.00328669186857626, 0.00049704260678339, -0.000695928844511353,
-0.00838914337795957, 0.00550083899465574, 0.000199461454735274,
0.00685716972613716, 0.000594059423411153, -0.00396707849439904
)), .Names = c("CHF.OPEN", "CHF.OPEN.1", "CHF50D", "CHF.OPEN.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
AUD.CLOSE = c(1, 0, 0, 1, 0, -1, 0, 0, 1, 0), AUD.CLOSE.1 = c(1,
1, 1, 1, 1, 1, 1, 1, 1, 1), AUD.50D = c(-1, -1, -1, -1,
-1, -1, -1, -1, -1, -1), AUD.CLOSE.2 = c(0.00640566933128534,
-0.00444038864633145, 0.00300594880983807, 0.0061146355869709,
-0.00207738324513479, -0.00390676366154397, 0.00312663099943206,
-0.00169237819473061, 0.00364156989756792, 0.00155662244429539
)), .Names = c("AUD.CLOSE", "AUD.CLOSE.1", "AUD.50D",
"AUD.CLOSE.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(CAD.CLOSE = c(-1, 0, 0, 0, 0, 1, 0, 1, 0,
-1), CAD.CLOSE.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1,
-1), CAD.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), CAD.CLOSE.2 = c(-0.00472778065310547,
-0.000917641725324381, 0.000382453058549392, 0.000305857167088586,
-0.000688310225637978, 0.00191080426541917, 0.000763300548471235,
0.00266697304419594, 0.00174871741959248, -0.00449199430572389
)), .Names = c("CAD.CLOSE", "CAD.CLOSE.1", "CAD.50D", "CAD.CLOSE.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
NZD.CLOSE = c(0, 0, 0, 1, 0, -1, 0, -1, 0, 1), NZD.CLOSE.1 = c(1,
1, 1, 1, 1, 1, 1, 1, 1, 1), NZD.50D = c(-1, -1, -1, -1,
-1, -1, -1, -1, -1, -1), NZD.CLOSE.2 = c(0.00041733324664972,
-0.00208841008727045, -0.000836586774949688, 0.00750420419797471,
-0.00180142777185216, -0.00389105549296664, 0.00111327592906424,
-0.00404153570815258, 0.00390244397693174, 0.00568695616893883
)), .Names = c("NZD.CLOSE", "NZD.CLOSE.1", "NZD.50D",
"NZD.CLOSE.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(SEK.OPEN = c(1, 1, 0, 0, -1, 0, 1, 1, 0, 0
), SEK.OPEN.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, 1),
SEK.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), SEK.OPEN.2 = c(0.00163829609003363,
0.0023181988913219, -0.000716164076936199, -0.00145628918509555,
-0.00677152707834994, 0.00582941106111079, 0.00270059947077783,
0.00455540960162004, -0.000256248852460228, 0.00199255363165785
)), .Names = c("SEK.OPEN", "SEK.OPEN.1", "SEK.50D", "SEK.OPEN.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
NOK.CLOSE = c(1, 0, 0, -1, -1, 0, 0, 1, 0, 0), NOK.CLOSE.1 = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), NOK.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), NOK.CLOSE.2 = c(0.00323283885094217,
0.00303175214315887, 0.000941075635438882, -0.00716968871997281,
-0.00617111408142934, 0.00665069589528811, -0.000467589464977269,
0.00246736261239189, 0.000837040274633605, -0.00324444329976892
)), .Names = c("NOK.CLOSE", "NOK.CLOSE.1", "NOK.50D",
"NOK.CLOSE.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(CZK.CLOSE = c(1, 1, 1, 0, -1, 0, 0, 1, 0,
-1), CZK.CLOSE.1 = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0), CZK.50D = c(1,
1, 1, -1, -1, 1, -1, 1, -1, -1), CZK.CLOSE.2 = c(0.00144601789180365,
0.00379617459269976, 0.00202579528819546, -0.00220231606416821,
-0.00688897736863447, 0.00560532297819627, 0.000184602212216056,
0.00710284457208665, -0.00197121312914339, -0.00224919172846905
)), .Names = c("CZK.CLOSE", "CZK.CLOSE.1", "CZK.50D", "CZK.CLOSE.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
HUF.LOW.1 = c(0, 1, 1, 0, -1, 0, 0, 1, 0, 0), HUF.LOW.1.1 = c(-1,
-1, -1, -1, -1, -1, -1, 1, -1, 1), HUF.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), HUF.LOW.1.2 = c(0.0013470806658562,
0.00413351833762921, 0.000927691660614904, -0.00161542594720476,
-0.00908798735735505, 0.00843420139734707, -0.00110208028787984,
0.00632043873779775, -0.00133632598823841, 0.000719782039952932
)), .Names = c("HUF.LOW.1", "HUF.LOW.1.1", "HUF.50D",
"HUF.LOW.1.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(ILS.LOW.1 = c(0, 0, 0, -1, -1, -1, 0, 0, 0,
0), ILS.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1
), ILS.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), ILS.LOW.1.2 = c(0.000933818987030266,
0.000959590648321962, -0.00159982969276018, -0.00296644925366696,
-0.00509821862018822, -0.00393531505179312, 0.00242770943578163,
-0.00285991992901691, -0.000567559913074556, 0.00091874516690349
)), .Names = c("ILS.LOW.1", "ILS.LOW.1.1", "ILS.50D", "ILS.LOW.1.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
PLN.LOW.1 = c(0, 1, 0, 0, -1, 1, 0, 0, 0, 0), PLN.LOW.1.1 = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), PLN.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), PLN.LOW.1.2 = c(-0.00274633685326608,
0.00755279414139087, 0.000417931735706034, -0.000491702529882065,
-0.00490565626173578, 0.00929781633628868, -0.00365469691428677,
0.00186580959045224, -0.00137446945036213, -0.00149934278232444
)), .Names = c("PLN.LOW.1", "PLN.LOW.1.1", "PLN.50D",
"PLN.LOW.1.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(RUB.LOW.1 = c(-1, -1, -1, -1, 0, 0, 1, 0,
-1, 1), RUB.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1,
-1), RUB.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), RUB.LOW.1.2 = c(-0.00446008580014645,
-0.0121748200414373, -0.00422818336649922, -0.0153488129381678,
0.0022241309795028, 0.00590173583792808, 0.014758577509606,
-0.00824954514944221, -0.00941636498473652, 0.0111898627811513
)), .Names = c("RUB.LOW.1", "RUB.LOW.1.1", "RUB.50D", "RUB.LOW.1.2"
), row.names = c("2017-02-09", "2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22"), class = "data.frame"), structure(list(
TRY.HIGH.1 = c(0, 0, -1, 0, 0, -1, -1, 0, -1, -1), TRY.HIGH.1.1 = c(1,
1, 1, 1, 1, -1, -1, -1, -1, -1), TRY.50D = c(-1, -1,
-1, -1, -1, -1, -1, -1, -1, -1), TRY.HIGH.1.2 = c(0.00417356089701015,
-0.00686579177053992, -0.00568012668941198, 0.00229778255761226,
0.00204713949728741, -0.0100024127023963, -0.00176420367173535,
-0.00113183078791668, -0.011249649909296, -0.00307744199905646
)), .Names = c("TRY.HIGH.1", "TRY.HIGH.1.1", "TRY.50D",
"TRY.HIGH.1.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(ZAR.LOW.1 = c(-1, 0, -1, -1, 0, 0, 0, 0, -1,
-1), ZAR.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1,
-1), ZAR.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), ZAR.LOW.1.2 = c(-0.0050112296343281,
-0.000119978703923884, -0.0173679300039469, -0.0145343910929765,
0.00897924634581271, 0.000421926368602055, 0.000521408427958114,
0.00716476609655059, -0.0126608692527035, -0.00785440574245699
)), .Names = c("ZAR.LOW.1", "ZAR.LOW.1.1", "ZAR.50D", "ZAR.LOW.1.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
BRL.LOW.1 = c(0, 0, -1, -1, 0, 1, 0, 0, -1, -1), BRL.LOW.1.1 = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), BRL.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), BRL.LOW.1.2 = c(-0.00371652356533581,
-0.00160621962638552, -0.00832934597660584, -0.00902065874268554,
0.010543197464703, 0.00316721872930192, -0.00362049854021018,
0.00278119317749237, -0.0100617531753731, -0.0006199931673041
)), .Names = c("BRL.LOW.1", "BRL.LOW.1.1", "BRL.50D",
"BRL.LOW.1.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(CLP.LOW.1 = c(-1, 0, 0, 0, 0, 1, 0, 0, 0,
0), CLP.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1
), CLP.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), CLP.LOW.1.2 = c(-0.00993671434599985,
0.00456853190734918, -0.00172828592427443, -0.00404432121904819,
-0.00048516719656444, 0.00933326604643625, -0.00561445365426927,
0.00353409520664982, -0.00208469536279665, -0.00105956972687871
)), .Names = c("CLP.LOW.1", "CLP.LOW.1.1", "CLP.50D", "CLP.LOW.1.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
COP.CLOSE = c(-1, 1, 0, 0, 0, 1, 0, 1, 0, -1), COP.CLOSE.1 = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), COP.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), COP.CLOSE.2 = c(-0.00197341552292052,
0.00662211307234362, 0.000580874632634121, -0.00202234392720335,
0.00204668459925017, 0.00543743450560008, -0.00266994190200176,
0.00607751193077277, -0.00217715796204931, -0.00905605289811184
)), .Names = c("COP.CLOSE", "COP.CLOSE.1", "COP.50D",
"COP.CLOSE.2"), row.names = c("2017-02-10", "2017-02-13",
"2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(MXN.LOW.1 = c(0, 0, -1, 0, 0, 1, -1, -1, -1,
-1), MXN.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1,
-1), MXN.50D = c(-1, -1, 1, 1, 1, 1, 1, 1, 1, 1), MXN.LOW.1.2 = c(-0.000211320384603475,
-0.00314066280938086, -0.00107540683430729, 0.000705557901050646,
0.00518510570127306, 0.00240140867288519, -0.00281365838425973,
-0.0177295559643031, -0.00536567713104841, -0.0121193389083811
)), .Names = c("MXN.LOW.1", "MXN.LOW.1.1", "MXN.50D", "MXN.LOW.1.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
PEN.HIGH.1 = c(-1, 0, -1, -1, 0, 1, -1, 0, -1, 0), PEN.HIGH.1.1 = c(-1,
-1, -1, -1, -1, -1, -1, -1, -1, -1), PEN.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), PEN.HIGH.1.2 = c(-0.00429316820091041,
0.00214888801033619, -0.000859001157250239, -0.0038438522704316,
0.00101621330746293, 0.00460618041489735, -0.00522194398115183,
0, -0.000462071629322658, -0.000154071335332739)), .Names = c("PEN.HIGH.1",
"PEN.HIGH.1.1", "PEN.50D", "PEN.HIGH.1.2"), row.names = c("2017-02-10",
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17",
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(CNY.CLOSE = c(1, 0, -1, 0, -1, 1, 1, 1, 0,
-1), CNY.CLOSE.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1,
-1), CNY.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), CNY.CLOSE.2 = c(0.00135295379134326,
0.000247116371263401, -0.00184758230288495, 0.000524070878021865,
-0.0026376972616271, 0.001968002384513, 0.00174608993071379,
0.000799273430379666, -0.00090104498241117, -0.00170257391661588
)), .Names = c("CNY.CLOSE", "CNY.CLOSE.1", "CNY.50D", "CNY.CLOSE.2"
), row.names = c("2017-02-10", "2017-02-13", "2017-02-14",
"2017-02-15", "2017-02-16", "2017-02-17", "2017-02-20", "2017-02-21",
"2017-02-22", "2017-02-23"), class = "data.frame"), structure(list(
IDR.LOW.1 = c(-1, 0, 0, 0, 0, 0, 1, 1, 0, 0), IDR.LOW.1.1 = c(-1,
-1, -1, -1, -1, -1, -1, 1, -1, -1), IDR.50D = c(1, 1,
1, 1, 1, 1, 1, 1, 1, 1), IDR.LOW.1.2 = c(-0.00225360672301989,
0.00142787383820853, 0.000750694427567922, 0.000375135991193432,
-0.000825485019296579, 0.000975500021079156, 0.00157380030235466,
0.00142178345498323, -0.000448765901323256, -0.00119769458137853
)), .Names = c("IDR.LOW.1", "IDR.LOW.1.1", "IDR.50D",
"IDR.LOW.1.2"), row.names = c("2017-02-09", "2017-02-10",
"2017-02-13", "2017-02-14", "2017-02-16", "2017-02-17", "2017-02-20",
"2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"),
structure(list(INR.LOW.1 = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1
), INR.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1
), INR.50D = c(-1, -1, -1, -1, -1, -1, 0, -1, 0, -1), INR.LOW.1.2 = c(-0.000466530150061928,
-0.000531550320954643, -0.000443420116883253, -0.000392023361358795,
-0.000386278564721287, -0.000386427833512393, -0.000244913256195467,
-0.000181510566847898, -0.000126929400856568, -0.000132850348706803
)), .Names = c("INR.LOW.1", "INR.LOW.1.1", "INR.50D", "INR.LOW.1.2"
), row.names = c("2017-02-08", "2017-02-09", "2017-02-10",
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17",
"2017-02-20", "2017-02-22"), class = "data.frame"), structure(list(
KRW.LOW.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1),
KRW.LOW.1.1 = c(-1, -1, -1, -1, -1, -1, -1, 1, -1, -1
), KRW.50D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), KRW.LOW.1.2 = c(0.000517860571988438,
0.000112542907102053, 0.00134952787013343, 0, -0.000337211266051574,
0.00112359562382647, 0.000449084996881899, 0.000785413785115541,
-0.00085276367906495, -0.000718681250895026)), .Names = c("KRW.LOW.1",
"KRW.LOW.1.1", "KRW.50D", "KRW.LOW.1.2"), row.names = c("2017-02-10",
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17",
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"))
答案 0 :(得分：0)
您可以尝试使用purrr：
map_df(FlaggingTrend, function(x) {
co <- stringr::str_extract(names(x)[1], "\\w+")
names(x) <- c(names(x[[1]]))
x %>%
filter(EUR.CLOSE != 0, EUR.50D > 0, EUR.CLOSE.1 != 0) %>%
mutate(co = co) %>%
group_by(co) %>%
summarize(Sum_Var = sum(EUR.CLOSE.2))
})
列表中的每个数据框都将其列重命名为第一个。这不会返回示例中的值，但过滤应该可以正常工作。