将每列中的值乘以另一数据中的权重。R中的框 [英] Multiply values across each column by weight in another data.frame in R

问题描述

我有两个data.frames：df和weights(代码如下)。

df如下所示：

    id             a           b           d           EE           f
 1  this           0.23421153  -0.02324956 0.5457353   0.73068586   0.5642554
 2  is             0.28378641  0.36346241  1.0190496   1.97715019   -1.190179
 3  an             -0.04372133  0.07412557  -0.4510299  1.8442713   -0.5301328
 4  example        -0.18139887  0.10404329  -1.0871962  1.46920108  0.4685703
 5  data.frame     0.24235498   -0.1501064  -1.1183967  0.22884407  0.4272259
 6  for             -0.72718239 0.16337997  1.2635683   0.44206945  0.7303647
 7  stackoverflow  0.25203942   -0.1772715  -0.3371532  -0.29167792 -0.7065494
 8  please         -0.11047364  -0.06631552 0.4342659   -1.49584522 0.2837016
 9  help           -0.1136639   0.22414253  0.4284864   1.59096047  0.2915938
 10 me             -0.3677288   0.05974474  -0.1136177  0.02322094  -0.6533994

如何将每列中的值乘以weightsdata.frame中的相应权重？

预期结果：

    id            a             b           d            EE   f
 1  this          0.749476896   -0.1743717  5.29363241   NA   4.17548996
 2  is            0.908116512   2.725968075 9.88478112   NA   -8.8073246
 3  an            -0.139908256  0.555941775 -4.37499003  NA   -3.92298272
 4  example       -0.580476384  0.780324675 -10.54580314 NA   3.46742022
 5  data.frame    0.775535936   -1.125798   -10.84844799 NA   3.16147166
 6  for           -2.326983648  1.225349775 12.25661251  NA   5.40469878
 7  stackoverflow 0.806526144   -1.32953625 -3.27038604  NA   -5.22846556
 8  please        -0.353515648  -0.4973664  4.21237923   NA   2.09939184
 9  help          -0.36372448   1.681068975 4.15631808   NA   2.15779412
 10 me            -1.17673216   0.44808555  -1.10209169  NA   -4.83515556

编码：

 set.seed(12345)
 df <- data.frame(id=c("this", "is", "an", "example", "data.frame", "for", 
      "stackoverflow", "please", "help", "me"), a=rnorm(10,0,0.4), b=rnorm(10,0,0.2), 
      d=rnorm(10,0,0.7), EE=rnorm(10,0,0.9), f=rnorm(10,0,0.5))
 weights <- data.frame(V1=as.numeric(c("3.2", "7.5", "2.2", "9.7", "5.4", "7.4", "2.1", 
      "5.0", "3.3", "7.6", "3.6", "7.7", "7.1", "3.3", "9.8", "9.2", "2.5", "6.2", "4.1", "8.7", 
      "3.3", "9.3", "8.3")))
 rownames(weights) <- paste(letters[1:23])

推荐答案

可以使用sweep和match-

df[-1] <- sweep(df[-1],2, weights$V1[match(names(df[-1]),rownames(weights))],`*`)

df
#              id          a          b          d EE         f
#1           this  0.7494769 -0.1743717   5.293633 NA  4.175490
#2             is  0.9081165  2.7259681   9.884781 NA -8.807325
#3             an -0.1399082  0.5559418  -4.374990 NA -3.922983
#4        example -0.5804764  0.7803247 -10.545803 NA  3.467420
#5     data.frame  0.7755359 -1.1257980 -10.848448 NA  3.161471
#6            for -2.3269836  1.2253498  12.256612 NA  5.404699
#7  stackoverflow  0.8065261 -1.3295363  -3.270386 NA -5.228465
#8         please -0.3535157 -0.4973664   4.212379 NA  2.099392
#9           help -0.3637245  1.6810690   4.156319 NA  2.157794
#10            me -1.1767322  0.4480855  -1.102092 NA -4.835156

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