使用lapply超過data.frames

的名單上有數據，看起來像下面的示例創建列值的條件的總和：使用lapply超過data.frames

[[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

這是dataframes的列表。我想根據前三列的條件對第4行（VAR.CLOSE.2）中的元素進行求和。的條件是：

柱1具有非負值OR
列2是3是非負

換句話說大於零OR

柱嚴格地，作爲一個說明性的例子，如果我只是在檢查一個數據幀，我想要類似sum(x[which(x[,1]!=0 | x[,2]>0 | x[,3]!=0]), 4)

所以在上面給出的例子中，我想要得到以下計算結果：

[[1]] 
       KRW 
ReturnSum  15 


[[2]] 
       EUR 
ReturnSum  5

我們得到5歐元是因爲總計前兩行，因爲最後一行不符合3個條件中的任何一個。特別是，條件Data[[2]][3,1] != 0Data[[2]][3,3] != 0都失敗也是如此Data[[2]][3,2]>0

我試着

i <- 1:length(FlaggingTrend) 
SumReturns <- lapply(FlaggingTrend[[i]], function(x) sum(x[which(x[,2]!=0|x[,3]>0|x[,4]!=0),4]))

實現這一目標在哪裏FlaggingTrend相當於上面貼的數據。但是，這會返回一個零列表。

我會附加數據低於樣品dput：

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"))

來源

2017-03-10 Nikitau

很難說的一種想要的。（x [1：3,1]！= 0 | x [1：3,2]> 0 | x [1：3,3]）可能是這樣的：'lapply ！= 0），4]））' – count

@count對不起，是的。我可能會嘗試使用更簡單的數據來編輯我的示例，以便它不是一個難看的東西。我不知道是否x [[（x [1：3,1]！= 0 | x [1：3,2]> 0 | x [1：3,3]！= 0），4]'將工作，因爲我正在處理跨越大約200多行的更大的數據集。我會編輯我的帖子，以便更清楚。 – Nikitau

@count另外對不起，我試過使用你的'lapply'函數，但是我得到了一個'NA'的列表 – Nikitau

你可以嘗試用purrr工作：

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)) 
})

列表中的每個數據幀都有它的列重命名爲第一。這不會返回您的示例中的值，但篩選應該可以正常工作。

來源

2017-03-10 23:06:57 detroyejr

我並不熟悉purr，但是非常感謝！但是，當我嘗試它時，我收到一個錯誤，說foo沒有找到。當我用FlaggingTrend替換foo時，我最終在'[[<。data.frame'（'* tmp *'，col，value =「CZK」）得到錯誤：替換有1行，數據有0 – Nikitau

只是我的錯誤。 Map_df與lapply非常相似，因此您可以將列表中的每個元素定義爲x的函數。我只是沒有修復從我修補的變量。 – detroyejr

對不起，我再次困擾你，但改變到X後，我得到'錯誤：每個變量必須命名。問題變量：1，2，3，4'。我很抱歉，如果這是一個相當愚蠢的問題，但這可能是因爲'filter（EUR.CLOSE！= 0 ...）'，因爲我有更多變量（結構類似），分別命名爲JPY，GBP，CHF， NOK ...等？ – Nikitau

使用lapply超過data.frames

回答

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