Row sums over columns with a certain pattern in their name

Question

I have a data.table like this

dput(DT)
structure(list(ref = c(3L, 3L, 3L, 3L), nb = 12:15, i1 = c(3.1e-05, 
0.044495, 0.82244, 0.322291), i2 = c(0.000183, 0.1         


        

Answer 1

The dplyr solution would be to use mutate_ together with paste(listCol, collapse = "+"). But I guess the Reduce solution is faster.

DT <- mutate_(DT, sum = paste(listCol, collapse = "+"))

Answer 2

You may also try with Reduce

 DT[, Sum := Reduce(`+`, .SD), .SDcols=listCol][]
 #   ref nb       i1       i2       i3       i4      Sum
 #1:   3 12 0.000031 0.000183 0.000824 0.044495 0.045533
 #2:   3 13 0.044495 0.155732 0.533939 0.822440 1.556606
 #3:   3 14 0.822440 0.873416 0.838542 0.322291 2.856689
 #4:   3 15 0.322291 0.648545 0.990648 0.393595 2.355079

NOTE: If there are "NA" values, it should be replaced with '0' before Reduce i.e.

 DT[, Sum := Reduce(`+`, lapply(.SD, function(x) replace(x, 
                    which(is.na(x)), 0))), .SDcols=listCol][]

**Another solution :**using rowSums

 DT[, Sum := rowSums(.SD, na.rm = TRUE), .SDcols = grep("i", names(DT))] 

Answer 3

Use .SDcols to specify the columns, then take rowSums. Use := to assign new columns:

DT[ ,sum := rowSums(.SD), .SDcols = grep("i", names(DT))]