R – Multiply many columns by a specific other column in R with data.table

data.tabler

I have a large data.table in R with several columns with dollar values. In a different column I have an inflation adjustment number. I am trying to figure out how to update each of my monetary columns with it multiplied by the inflation adjustment column. Suppose I have the data:

   DT <- data.table(id=1:1000,year=round(runif(1000)*10), 
          inc1 = runif(1000), inc2 = runif(1000), inc3 = runif(1000),    
          deflator = rnorm(1000))

which gives output:

             id year      inc1      inc2       inc3    deflator
   1:    1    8 0.4754808 0.6678110 0.41533976 -0.64126988
   2:    2    2 0.6568746 0.7765634 0.70616373  0.39687915
   3:    3    6 0.8192947 0.9236281 0.90002534 -0.69545700
   4:    4    4 0.7781929 0.1624902 0.17565790  0.05263055
   5:    5    7 0.6232520 0.8024975 0.86449836  0.70781887
  ---                                                     
 996:  996    2 0.9676383 0.2238746 0.19822000  0.78564836
 997:  997    9 0.9877410 0.5783748 0.57497438 -1.63365223
 998:  998    8 0.2220570 0.6500632 0.19814932  1.00260174
 999:  999    3 0.4793767 0.2830457 0.54835581  1.04168818
1000: 1000    8 0.2003476 0.6121637 0.02921505  0.34933690

in reality I have inc1inc100, rather than just three variables and I want to figure out a way to perform this action:

DT[, inc1 := inc1 * deflator]

for each of my 100 income columns (inc1, inc2, inc3 in the fake data above). I will have more than 100 columns in the future, so I would like to figure out a way to loop the action over the columns. Is there a way to do this for all the income columns at once?

I would like to do something like:

inc_cols = c(inc1, inc2, inc3)

DT[, inc_cols := lapply(inc_cols,function(x)= x * deflator),]

or

DT[, inc_cols := lapply(.SD,function(x)= x * deflator),.SDcols = inc_cols]

but neither of these seem to work. I also tried using the get() function to make it clear deflator is a referencing a column, like:

DT[, inc_cols := lapply(.SD,function(x)= x * get(deflator)),.SDcols = inc_cols]

but had no luck. I also tried to loop through the variables with something like:

for (var in inc_cols) {
  print(var)
  DT[, get(var) := get(var) *infAdj2010_mult] 
}

which returns

[1] "inc1"
 Error in get(var) : object 'inc1' not found 

I realize this is probably a straight forward question and I have tried to search the other questions here and various online guides and tutorials, but I cannot find an example matching my specific problem. It is similar to this question, but not exactly.

Thanks for your help!

Best Solution

You could try

DT[, (inc_cols) := lapply(.SD, function(x) 
        x * DT[['deflator']] ), .SDcols = inc_cols]
head(DT1,2)
#   id year         inc1         inc2       inc3   deflator
#1:  1    3  0.614838304  0.009796974  0.3236051  0.7735552
#2:  2    2 -0.001583579 -0.082289606 -0.1365115 -0.6644330

Or if you need a loop

for(inc in inc_cols){
  nm1 <- as.symbol(inc)
  DT[,(inc):= eval(nm1)*deflator]
}

 head(DT,2)
 #  id year         inc1         inc2       inc3   deflator
 #1:  1    3  0.614838304  0.009796974  0.3236051  0.7735552
 #2:  2    2 -0.001583579 -0.082289606 -0.1365115 -0.6644330

Or a possible option using set which should be very fast as the overhead of [.data.table is avoided (suggested by @Arun)

indx <- grep('inc', colnames(DT))

for(j in indx){
 set(DT, i=NULL, j=j, value=DT[[j]]*DT[['deflator']])
}
head(DT,2)
#  id year         inc1         inc2       inc3   deflator
#1:  1    3  0.614838304  0.009796974  0.3236051  0.7735552
#2:  2    2 -0.001583579 -0.082289606 -0.1365115 -0.6644330

where

inc_cols <-  grep('^inc', colnames(DT), value=TRUE)

data

set.seed(24)
DT <- data.table(id=1:1000,year=round(runif(1000)*10), 
      inc1 = runif(1000), inc2 = runif(1000), inc3 = runif(1000),    
      deflator = rnorm(1000)) 
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