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Asked: 2026-06-10T23:35:28+00:00

df av bv tv u l value s 30 120 360 330 210 6600

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df

av  bv  tv   u   l value           s
30 120 360 330 210  6600 0.005238424 
35 125 360 325 200  6875 0.005028887
40 130 360 320 190  7150 0.004835468
45 135 360 315 180  7425 0.004656377
50 140 360 310 170  7700 0.004490078
55 145 360 305 160  7975 0.004335247
60 150 360 300 150  8250 0.004190739
65 155 360 295 140  8525 0.004055554
70 160 360 290 130  8800 0.003928818
75 165 360 285 120  9075 0.003809763
80 170 360 280 110  9350 0.003697711

dput(df)

df<-structure(list(av = c(30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 
80), bv = c(120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 
170), tv = c(360, 360, 360, 360, 360, 360, 360, 360, 360, 360, 
360), u = c(330, 325, 320, 315, 310, 305, 300, 295, 290, 285, 
280), l = c(210, 200, 190, 180, 170, 160, 150, 140, 130, 120, 
110), value = c(6600, 6875, 7150, 7425, 7700, 7975, 8250, 8525, 
8800, 9075, 9350), s = c(0.005238424, 0.00502888704, 0.00483546830769231, 
0.00465637688888889, 0.00449007771428572, 0.00433524744827586, 
0.0041907392, 0.00405555406451613, 0.003928818, 0.00380976290909091, 
0.00369771105882353)), .Names = c("av", "bv", "tv", "u", "l", 
"value", "s"), row.names = c(1L, 13L, 25L, 37L, 49L, 61L, 73L, 
85L, 97L, 109L, 121L), class = "data.frame")

df2

  av  bv  tv   u  l value
  30 120   0   0  0     0
  30 120  20   0  0     0
  30 120  40  10  0   550
  30 120  60  30  0  1650
  30 120 120  90  0  4950
  30 120 180 150 30  6600

dput(df2)

df2<-structure(list(av = c(30, 30, 30, 30, 30, 30), bv = c(120, 120, 
120, 120, 120, 120), tv = c(0, 20, 40, 60, 120, 180), u = c(0, 
0, 10, 30, 90, 150), l = c(0, 0, 0, 0, 0, 30), value = c(0, 0,
550, 1650, 4950, 6600)), .Names = c("av", "bv", "tv", "u", "l", 
"value"), row.names = c(1L, 2602L, 5203L, 7804L, 10405L, 13006L
), class = "data.frame")

All I want to do is add the df$s values in df to df2 where df$bv == df2$bv. df2 will have a lot more of the same bv values in df, so there will be some repetitive s values.

I was trying the following

     newDF <- ddply(df2, .(bv,tv), summarise, s = df[df$bv %in% df2$bv,]$s)

Although this is not working for me, maybe it’s because I don’t really understand the variable arguments in this function.

Really all other columns are arbitrary at this point, but I would like to keep the entire dataframe intact.

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1 Answer

  1. Editorial Team

    This will pull the corresponding ‘s’-items in ‘df’ into the matched rows of ‘df2’:

    df2$s <- df$s[ match(df2$bv, df$bv)]
df2
#-----------------------
      av  bv  tv   u  l value           s
1     30 120   0   0  0     0 0.005238424
2602  30 120  20   0  0     0 0.005238424
5203  30 120  40  10  0   550 0.005238424
7804  30 120  60  30  0  1650 0.005238424
10405 30 120 120  90  0  4950 0.005238424
13006 30 120 180 150 30  6600 0.005238424

    This is going to be a lot more efficient than ‘subset()’-ting and ‘merge()’-ing. Oooops. I didn’t see the plyr part. It’s going to be a lot faster than any plyr method, too, but that’s cuz’ I’m a base-R guy. If you want to do it with plyr then this delivers what I think you asked for:

    > newDF <- ddply(df2, .(bv), summarise, s = df$s[match(df2$bv , df$bv)])
> newDF
   bv           s
1 120 0.005238424
2 120 0.005238424
3 120 0.005238424
4 120 0.005238424
5 120 0.005238424
6 120 0.005238424
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