How do I substract a value from a column in a dataframe, with unique rows

Question

Hard to explain the question in a title. But here I have a data frame, and you can see I have 3 stream names. I have a 3 unique values associated with each stream name. I would like these unique values to be subtracted from the value for the corresponding stream found in the value column and then appended to the data frame in a new column titled error

    stream  n  rates   means     column     value
1    Brooks 3   3.0  0.9629152      1    0.42707006
2   Siouxon 3   3.0  0.5831929      1    0.90503736
3  Speelyai 3   3.0  0.6199235      1    0.08554021
4    Brooks 4   7.5  0.9722707      1    1.43338843
5   Siouxon 4   7.5  0.5865031      1    0.50574543
6  Speelyai 4   7.5  0.6118634      1    0.32252396
7    Brooks 5  10.0  0.9637475      1    0.88984211
8   Siouxon 5  10.0  0.5804420      1    0.47501800
9  Speelyai 5  10.0  0.5959238      1    0.15079491
10   Brooks 6  13.0  0.9486575      1    1.32422105
11  Siouxon 6  13.0  0.5846854      1    0.39479684
12 Speelyai 6  13.0  0.5597146      1    0.37005941

Here are the "unique" values I want subtracted from the value column

> true.lwd.sp <- 0.583984402 (speelyai)
> true.lwd.sx <- 0.585852702 (souixon)
> true.lwd.br <- 0.944062036 (brooks)

Thanks for any help. One day I may know how to do all these simple tasks!

Answer 1

We could create a new dataset and match the 'stream' column with the corresponding column in the new dataset, get the numeric index to get corresponding 'value' from 'df2', and subtract from the 'df1' or original dataset.

 df1$error <- df1$value-df2$value[match(df1$stream, df2$stream)]
 df1
 #    stream n rates     means column      value       error
 #1    Brooks 3   3.0 0.9629152      1 0.42707006 -0.51699198
 #2   Siouxon 3   3.0 0.5831929      1 0.90503736  0.31918466
 #3  Speelyai 3   3.0 0.6199235      1 0.08554021 -0.49844419
 #4    Brooks 4   7.5 0.9722707      1 1.43338843  0.48932639
 #5   Siouxon 4   7.5 0.5865031      1 0.50574543 -0.08010727
 #6  Speelyai 4   7.5 0.6118634      1 0.32252396 -0.26146044
 #7    Brooks 5  10.0 0.9637475      1 0.88984211 -0.05421993
 #8   Siouxon 5  10.0 0.5804420      1 0.47501800 -0.11083470
 #9  Speelyai 5  10.0 0.5959238      1 0.15079491 -0.43318949
 #10   Brooks 6  13.0 0.9486575      1 1.32422105  0.38015901
 #11  Siouxon 6  13.0 0.5846854      1 0.39479684 -0.19105586
 #12 Speelyai 6  13.0 0.5597146      1 0.37005941 -0.21392499

data

 df1 <- structure(list(stream = c("Brooks", "Siouxon", "Speelyai", 
 "Brooks", 
 "Siouxon", "Speelyai", "Brooks", "Siouxon", "Speelyai", "Brooks", 
 "Siouxon", "Speelyai"), n = c(3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 
 5L, 6L, 6L, 6L), rates = c(3, 3, 3, 7.5, 7.5, 7.5, 10, 10, 10, 
 13, 13, 13), means = c(0.9629152, 0.5831929, 0.6199235, 0.9722707, 
 0.5865031, 0.6118634, 0.9637475, 0.580442, 0.5959238, 0.9486575, 
 0.5846854, 0.5597146), column = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
 1L, 1L, 1L, 1L, 1L), value = c(0.42707006, 0.90503736, 0.08554021, 
 1.43338843, 0.50574543, 0.32252396, 0.88984211, 0.475018, 0.15079491, 
 1.32422105, 0.39479684, 0.37005941)), .Names = c("stream", "n", 
 "rates", "means", "column", "value"), class = "data.frame", 
 row.names = c("1", 
 "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12"))

 df2 <- data.frame(stream=c('Brooks', 'Siouxon', 'Speelyai'), 
      value=c(0.944062036, 0.585852702, 0.583984402), stringsAsFactors=FALSE)