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 inc1
- inc100
, 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!
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)
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))
Since you can use dplyr on data.tables, you could also do:
library(dplyr)
DT %>% mutate_each(funs(.*deflator), starts_with("inc"))
Which will multiply each column of DT that starts with "inc" by the "deflator" column.
This approach is also quite convenient, but likely slower than using set()
:
library(data.table); library(magrittr)
set.seed(42)
DT <- data.table(id=1:1000,year=round(runif(1000)*10),
inc1 = runif(1000), inc2 = runif(1000), inc3 = runif(1000),
deflator = rnorm(1000))
vars <- names(DT) %>% .[grepl("inc", .)]
DT[, (vars) := .SD * deflator, .SDcols = vars]
DT[]
id year inc1 inc2 inc3 deflator
1: 1 9 0.212563676 0.24806366 0.06860638 0.2505781
2: 2 9 -0.017438715 -0.12186792 -0.26241497 -0.2779240
3: 3 3 -1.414016119 -1.20714809 -0.76920337 -1.7247357
4: 4 8 -1.082336969 -1.78411512 -1.08720698 -2.0067049
5: 5 6 -0.644638321 -1.07757416 -0.20895576 -1.2918083
---
996: 996 1 -0.573551720 -1.93996157 -0.50171303 -2.1569621
997: 997 5 -0.007899417 -0.01561619 -0.05708009 -0.0920275
998: 998 1 -0.090975121 -0.30475714 -0.27291825 -0.3974001
999: 999 5 -0.045984079 -0.01563942 -0.07868934 -0.1383273
1000: 1000 0 -0.785962308 -0.63266975 -0.29247974 -0.8257650
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