R - 根據列和姓名減去df元素

Question

我有兩個dfs--基準測試返回和allreturns（下面的示例），我想創建第三個df，它返回一個減去的值allreturns-benchmarkreturns，匹配一個「 startmonth「值，以及在兩個dfs中都一致的colname（V1：V12）。

此問題類似於Excel中兩個條件的索引匹配，其中我將在行端與startmonth匹配，在列端（此處爲colnames）中的「V month」匹配。因此，舉例來說，如果在全部回覆中我有一個2005年1月的起始月份，並且V3中該行的值爲5，並且2005年1月和V3列的基準返回值爲3，則該行中allreturns的值爲新的DF將是3.等等。

實際的allallurns數據框是相當大的，所以我擔心合併之前減法，並想知道如果這是最可行的方法，或者如果我可以在一步減去元素。

謝謝你的幫助！

所有退貨：

structure(list(startmonth = structure(c(2012, 2012.08333333333, 
2012.16666666667, 2012.25, 2012.33333333333, 2012.41666666667, 
2012.5, 2012.58333333333, 2012.66666666667, 2012.75), class = "yearmon"), 
    V1 = c(0.0284247303, 0.0010087300099999, 0.0022169700300001, 
    -0.01468004942, 0.00102045998000011, 0.00591265976000011, 
    0.0199267303899999, 0.0417483615900001, 0.00335606009, 0.00334482998000007 
    ), V2 = c(0.0294621331884797, 0.00322793636420049, -0.012495624619603, 
    -0.0136745698429375, 0.0069391533726606, 0.0259572101269254, 
    0.0625070003256281, 0.0452445316901551, 0.00671211552040374, 
    0.0314807661806089), V3 = c(0.0317444198847785, -0.0114994993211506, 
    -0.0114879159244523, -0.00784276316178301, 0.0270041584010525, 
    0.0687892427111718, 0.0660728376647666, 0.0487406969361834, 
    0.0349424776135903, 0.0430893809414579), V4 = c(0.0165983608120608, 
    -0.0104907741199978, -0.00564318030266497, 0.0119276866011795, 
    0.0698798993604133, 0.0723761636332563, 0.0696386700530516, 
    0.0781496303938529, 0.0465900515831383, 0.0514300069951692 
    ), V5 = c(0.0176357587550031, -0.00464014273798818, 0.0141710999549016, 
    0.0541740095643377, 0.0734704805917499, 0.0759630795752142, 
    0.0996336273987892, 0.090283471493128, 0.054958669279074, 
    0.0744177901533509), V6 = c(0.0236526927561311, 0.0151941247787009, 
    0.056511081749947, 0.057711880885752, 0.0770610568378784, 
    0.106135386898253, 0.112009256278245, 0.099001465266642, 
    0.0780236008188706, 0.0925232124743112), V7 = c(0.0440507439776798, 
    0.0575768161840056, 0.0600567964260508, 0.0612497472951408, 
    0.107264153793045, 0.118584188660589, 0.120900971163225, 
    0.123029319908411, 0.0961897860250946, 0.0862168299189658 
    ), V8 = c(0.0876381519555687, 0.06112610752891, 0.0636025061792393, 
    0.0910094612943682, 0.119725659059378, 0.127528477230367, 
    0.145407622386291, 0.141953913583335, 0.0898622388709431, 
    0.0799104502736558), V9 = c(0.0912883309497081, 0.0646753939459335, 
    0.0934281965725043, 0.103288031047544, 0.128679074917691, 
    0.152180027943971, 0.164709321337116, 0.135362201702614, 
    0.0835346946365931, 0.076045245502748), V10 = c(0.0949385048758928, 
    0.0945311704081673, 0.105733987546834, 0.11211001031858, 
    0.153355781552244, 0.171595851273483, 0.157986258190939, 
    0.128770492863592, 0.0796565180062141, 0.069524282329458), 
    V11 = c(0.125642923731963, 0.10684937460315, 0.114575524881519, 
    0.136424461680214, 0.172791417952441, 0.164833036942378, 
    0.151263198147072, 0.124730408712938, 0.0731136700886696, 
    0.0680519003357034), V12 = c(0.138311269558968, 0.115699830661878, 
    0.138943880653118, 0.155574781977547, 0.166021702439959, 
    0.158070225731925, 0.147142608328795, 0.117914407614703, 
    0.0716363466924688, 0.086773098425986)), .Names = c("startmonth", 
"V1", "V2", "V3", "V4", "V5", "V6", "V7", "V8", "V9", "V10", 
"V11", "V12"), class = "data.frame", row.names = c(NA, 10L)) 

基準回報：

structure(list(startmonth = structure(c(2005, 2005.08333333333, 
2005.16666666667, 2005.25, 2005.33333333333, 2005.41666666667, 
2005.5, 2005.58333333333, 2005.66666666667, 2005.75, 2005.83333333333, 
2005.91666666667, 2006, 2006.08333333333, 2006.16666666667, 2006.25, 
2006.33333333333, 2006.41666666667, 2006.5, 2006.58333333333, 
2006.66666666667, 2006.75, 2006.83333333333, 2006.91666666667, 
2007, 2007.08333333333, 2007.16666666667, 2007.25, 2007.33333333333, 
2007.41666666667, 2007.5, 2007.58333333333, 2007.66666666667, 
2007.75, 2007.83333333333, 2007.91666666667, 2008, 2008.08333333333, 
2008.16666666667, 2008.25, 2008.33333333333, 2008.41666666667, 
2008.5, 2008.58333333333, 2008.66666666667, 2008.75, 2008.83333333333, 
2008.91666666667, 2009, 2009.08333333333, 2009.16666666667, 2009.25, 
2009.33333333333, 2009.41666666667, 2009.5, 2009.58333333333, 
2009.66666666667, 2009.75, 2009.83333333333, 2009.91666666667, 
2010, 2010.08333333333, 2010.16666666667, 2010.25, 2010.33333333333, 
2010.41666666667, 2010.5, 2010.58333333333, 2010.66666666667, 
2010.75, 2010.83333333333, 2010.91666666667, 2011, 2011.08333333333, 
2011.16666666667, 2011.25, 2011.33333333333, 2011.41666666667, 
2011.5, 2011.58333333333, 2011.66666666667, 2011.75, 2011.83333333333, 
2011.91666666667, 2012, 2012.08333333333, 2012.16666666667, 2012.25, 
2012.33333333333, 2012.41666666667, 2012.5, 2012.58333333333, 
2012.66666666667, 2012.75, 2012.83333333333, 2012.91666666667, 
2013, 2013.08333333333, 2013.16666666667, 2013.25, 2013.33333333333, 
2013.41666666667, 2013.5, 2013.58333333333, 2013.66666666667, 
2013.75, 2013.83333333333, 2013.91666666667, 2014, 2014.08333333333, 
2014.16666666667, 2014.25, 2014.33333333333, 2014.41666666667, 
2014.5, 2014.58333333333, 2014.66666666667, 2014.75, 2014.83333333333 
), class = "yearmon"), V1 = c(0.83740290789865, 0.175849379040301, 
0.115745179820806, 0.588703967630863, 0.663440374424681, 0.122854199260473, 
0.329111734172329, 0.386456901207566, 0.328031520592049, 0.91476626554504, 
0.838957223575562, 0.482753940392286, 0.203118846053258, 0.832898694789037, 
0.569874424720183, 0.85476457583718, 0.873173910891637, 0.599100088467821, 
0.990275882417336, 0.360726963961497, 0.366468257969245, 0.213221889222041, 
0.736634878907353, 0.770827260101214, 0.78438491653651, 0.443004491971806, 
0.0431681957561523, 0.362984816078097, 0.933778994018212, 0.890268561197445, 
0.0288882539607584, 0.704298130935058, 0.0533608365803957, 0.965311451349407, 
0.797033908311278, 0.702818523859605, 0.615030416054651, 0.783928481163457, 
0.0931849081534892, 0.693762929877266, 0.709550492931157, 0.527024435112253, 
0.463098735082895, 0.975416449131444, 0.418448116164654, 0.716492718551308, 
0.900618054671213, 0.937315494287759, 0.371745373355225, 0.876447483897209, 
0.638362225377932, 0.230460224673152, 0.84510417538695, 0.709547182312235, 
0.135460949270055, 0.86736886552535, 0.0408105747774243, 0.59634031355381, 
0.378888477338478, 0.400274467887357, 0.73448179056868, 0.0201477019581944, 
0.786700234282762, 0.145882265642285, 0.722347423899919, 0.495645943330601, 
0.8204965388868, 0.944398637628183, 0.920839294558391, 0.244003586936742, 
0.770501866471022, 0.608119423966855, 0.599260926479474, 0.316019677789882, 
0.594015010166913, 0.862004647962749, 0.248981321696192, 0.251351157668978, 
0.86709617683664, 0.477806584443897, 0.308428246993572, 0.930116105359048, 
0.820579398889095, 0.407806032337248, 0.00576947652734816, 0.07, 
0.503058285918087, 0.421452875249088, 0.171408428112045, 0.927357386332005, 
0.736080843256786, 0.0634949475061148, 0.628076422959566, 0.825837341602892, 
0.860992948058993, 0.637153514893726, 0.496678973315284, 0.532001776387915, 
0.742080342955887, 0.279888727236539, 0.702802252722904, 0.20291490922682, 
0.761654698755592, 0.413414426380768, 0.0555722850840539, 0.125917585333809, 
0.545490033458918, 0.19256273820065, 0.242046363884583, 0.0174444266594946, 
0.380734569625929, 0.735217718640342, 0.346396475099027, 0.997578310314566, 
0.544119880301878, 0.610004446236417, 0.643721028929576, 0.0819557739887387, 
0.666767429094762), V2 = c(0.325795059790835, 0.0280552506446838, 
0.563847373938188, 0.968374367104843, 0.0397681496106088, 0.409115779446438, 
0.568448322825134, 0.498488057404757, 0.725102471420541, 0.745882571907714, 
0.956671225838363, 0.732607456855476, 0.723114193649963, 0.715586860431358, 
0.740428047254682, 0.447626604698598, 0.136078626848757, 0.343137193005532, 
0.994878244586289, 0.569102957844734, 0.264083825284615, 0.0172849236987531, 
0.902412769151852, 0.237230452476069, 0.342157111503184, 0.940635218983516, 
0.355561858741567, 0.0913543966598809, 0.730372012127191, 0.424820594489574, 
0.862009244738147, 0.673514985479414, 0.0558020728640258, 0.769041493767872, 
0.429111589910462, 0.814037810778245, 0.485316230216995, 0.407698386581615, 
0.0245183343067765, 0.38149883877486, 0.939248957671225, 0.206260631326586, 
0.773903579683974, 0.955869939411059, 0.930366629268974, 0.497170565184206, 
0.232823575846851, 0.119068749016151, 0.188956700265408, 0.769491335609928, 
0.487886165967211, 0.249603169038892, 0.61157290590927, 0.967520525446162, 
0.669223197968677, 0.0509379308205098, 0.630447809584439, 0.93567297863774, 
0.296445045853034, 0.231306056724861, 0.664361900882795, 0.570044811815023, 
0.988849612651393, 0.96225642086938, 0.567738547222689, 0.562166472664103, 
0.382391084451228, 0.87047664122656, 0.553916300181299, 0.348980325739831, 
0.861658359179273, 0.824328954331577, 0.602889677742496, 0.108061951119453, 
0.510826006531715, 0.787226195679978, 0.209260584786534, 0.467020642245188, 
0.916463258676231, 0.810527657391503, 0.259206298971549, 0.383183149620891, 
0.399636579910293, 0.517378240358084, 0.277383098145947, 0.0540329110808671, 
0.334274391178042, 0.762725146021694, 0.624413190409541, 0.664978531654924, 
0.877504705451429, 0.133810454979539, 0.303127287654206, 0.401904000202194, 
0.333468962227926, 0.880315525457263, 0.693340804660693, 0.104616170749068, 
0.726646555587649, 0.787352371029556, 0.805738570401445, 0.842183391330764, 
0.203002500347793, 0.4008568006102, 0.764609909849241, 0.68458701716736, 
0.826388106215745, 0.458343503531069, 0.681572974193841, 0.816049969289452, 
0.99422895279713, 0.586194961098954, 0.106009811395779, 0.564460329711437, 
0.763485615840182, 0.641962635098025, 0.556110577424988, 0.624630474718288, 
0.0865604616701603), V3 = c(0.103272917214781, 0.145110326353461, 
0.139097063103691, 0.704820184968412, 0.499401112552732, 0.183894460555166, 
0.142426387872547, 0.654179619625211, 0.231400778284296, 0.07779724849388, 
0.639861593721434, 0.329660887364298, 0.207785484148189, 0.349164958344772, 
0.918049042113125, 0.561889169970527, 0.801518984371796, 0.374053293140605, 
0.279966498259455, 0.211821462959051, 0.988277795957401, 0.208132355008274, 
0.358667319407687, 0.489217024296522, 0.235113901318982, 0.0665953925345093, 
0.682081600185484, 0.923956993501633, 0.951206840341911, 0.153028624830768, 
0.457171397982165, 0.497927478514612, 0.464426794555038, 0.700641778064892, 
0.350401868345216, 0.239867100957781, 0.495585883036256, 0.659481293288991, 
0.121178397443146, 0.966434765374288, 0.781230272026733, 0.191542416810989, 
0.144150232896209, 0.649679786758497, 0.990280882688239, 0.182715938193724, 
0.990455492865294, 0.0560185567010194, 0.258451806847006, 0.745103346649557, 
0.389899141388014, 0.0482800761237741, 0.0293514989316463, 0.393075271975249, 
0.53582366858609, 0.522070667007938, 0.802251521963626, 0.292497304268181, 
0.523711683694273, 0.606568831950426, 0.198962268885225, 0.391696797916666, 
0.059201990487054, 0.0645288161467761, 0.808837213553488, 0.0917617143131793, 
0.698996715713292, 0.330968038411811, 0.843029006384313, 0.9479373190552, 
0.514315341366455, 0.325804576743394, 0.3519700136967, 0.537765094777569, 
0.871437344467267, 0.667971923248842, 0.0599088978487998, 0.560071154031903, 
0.902071484364569, 0.193852530093864, 0.629741749959067, 0.0646166354417801, 
0.238403898198158, 0.737684201914817, 0.0984734564553946, 0.314926577033475, 
0.667433348251507, 0.200710391392931, 0.510746134677902, 0.0941306182648987, 
0.408070910954848, 0.349233734188601, 0.0384121341630816, 0.469132867408916, 
0.968564240029082, 0.250593126285821, 0.0388190811499953, 0.301829227479175, 
0.62604419933632, 0.981997888535261, 0.699610964162275, 0.319871086394414, 
0.0948076455388218, 0.0173410377465189, 0.733540053712204, 0.304378144675866, 
0.593588132876903, 0.85377266141586, 0.272565411170945, 0.151829193811864, 
0.951305341674015, 0.21787527250126, 0.728856807108968, 0.932554795406759, 
0.530237913830206, 0.146221859846264, 0.220554714323953, 0.133143884129822, 
0.845931079704314), V4 = c(0.828090658877045, 0.244675925467163, 
0.617208154639229, 0.675795117858797, 0.921914914855734, 0.777150499867275, 
0.841221024747938, 0.492060288786888, 0.326705329120159, 0.686669388087466, 
0.121503615053371, 0.367948720930144, 0.106932319700718, 0.363004767335951, 
0.350841429783031, 0.204824617831036, 0.233977065887302, 0.7365177560132, 
0.0454314323142171, 0.865328938700259, 0.328468273859471, 0.187198075000197, 
0.0820242392364889, 0.516697632148862, 0.481362534221262, 0.620970563730225, 
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0.536431754939258, 0.976550402119756, 0.40865416219458, 0.890750366030261, 
0.662430537166074, 0.388162778690457, 0.959246737649664, 0.931342099327594, 
0.770709854317829, 0.279344801558182, 0.305849055293947, 0.370182184502482, 
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0.481090292567387, 0.0106754100415856, 0.684031964046881, 0.815850237151608, 
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0.0494276131503284, 0.526557822246104, 0.0758368712849915, 0.269769576610997, 
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0.557413443457335, 0.464988547144458, 0.552185143576935, 0.0831529255956411, 
0.333197562023997, 0.574352362193167, 0.4974719658494, 0.190328923054039, 
0.82773098279722, 0.356611662777141, 0.803166383411735, 0.320444498909637, 
0.366018867818639, 0.809054122306406, 0.553693874971941, 0.293376821791753, 
0.97094266442582, 0.879881211323664, 0.308937143767253, 0.579827836947516, 
0.496185180498287), V5 = c(0.923095905454829, 0.762332424288616, 
0.972339176572859, 0.422411200823262, 0.940925979521126, 0.540574067272246, 
0.985336700454354, 0.8358859855216, 0.452674505067989, 0.919172912370414, 
0.177077513653785, 0.484894159948453, 0.228302743285894, 0.588133673649281, 
0.120827580103651, 0.320581880165264, 0.132633685600013, 0.244240331463516, 
0.0881568337790668, 0.0182364885695279, 0.619532398879528, 0.763255036668852, 
0.360307943308726, 0.291531737195328, 0.637159892357886, 0.423571469495073, 
0.144552590325475, 0.232900225091726, 0.431558183860034, 0.624517237534747, 
0.660041945520788, 0.0605304769705981, 0.894808513810858, 0.766446133842692, 
0.708146936027333, 0.980518834665418, 0.831859190016985, 0.63390138419345, 
0.0906804192345589, 0.863758355844766, 0.81235816469416, 0.754735963186249, 
0.96086330129765, 0.379362520063296, 0.86472422350198, 0.434156836709008, 
0.921033434569836, 0.930532508296892, 0.919923858484253, 0.0185073432512581, 
0.190673178527504, 0.389489938504994, 0.251335079083219, 0.398261951981112, 
0.323421294335276, 0.0406879091169685, 0.0622786141466349, 0.511600321624428, 
0.761615104507655, 0.267784109571949, 0.593046235619113, 0.923055295599625, 
0.481184788281098, 0.539936339249834, 0.71660251962021, 0.525291009107605, 
0.878714059945196, 0.127967000938952, 0.616779315285385, 0.174148306716233, 
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0.921317730797455)), .Names = c("startmonth", "V1", "V2", "V3", 
"V4", "V5", "V6", "V7", "V8", "V9"), class = "data.frame", row.names = c(NA, 
119L)) 

Answer 1

這就是我得到一個合併，然後將其僅限於每個DF的前兩列的結果：

> merge(Benret, Allret, by=1)[c(1,2,3,11,12)] 
    startmonth  V1.x  V2.x  V1.y   V2.y 
1 Jan 2012 0.005769477 0.27738310 0.02842473 0.029462133 
2 Feb 2012 0.205415812 0.05403291 0.00100873 0.003227936 
3 Mar 2012 0.503058286 0.33427439 0.00221697 -0.012495625 
4 Apr 2012 0.421452875 0.76272515 -0.01468005 -0.013674570 
5 May 2012 0.171408428 0.62441319 0.00102046 0.006939153 
6 Jun 2012 0.927357386 0.66497853 0.00591266 0.025957210 
7 Jul 2012 0.736080843 0.87750471 0.01992673 0.062507000 
8 Aug 2012 0.063494948 0.13381045 0.04174836 0.045244532 
9 Sep 2012 0.628076423 0.30312729 0.00335606 0.006712116 
10 Oct 2012 0.825837342 0.40190400 0.00334483 0.031480766 

計算差異並省略輸入：

res <- merge(Benret, Allret, by=1)[c(1,2,3,11,12)] 
> res$diffV1 <- with(res, V1.x - V1.y) 
> res$diffV2 <- with(res, V2.x - V2.y) 

> res[ -(2:5) ] 
    startmonth  diffV1  diffV2 
1 Jan 2012 -0.02265525 0.24792096 
2 Feb 2012 0.20440708 0.05080497 
3 Mar 2012 0.50084132 0.34677002 
4 Apr 2012 0.43613292 0.77639972 
5 May 2012 0.17038797 0.61747404 
6 Jun 2012 0.92144473 0.63902132 
7 Jul 2012 0.71615411 0.81499771 
8 Aug 2012 0.02174659 0.08856592 
9 Sep 2012 0.62472036 0.29641517 
10 Oct 2012 0.82249251 0.37042323