user235852 - 1 month ago 3x
R Question

# Row sums over columns with a certain pattern in their name

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, 0.155732, 0.873416,
0.648545), i3 = c(0.000824, 0.533939, 0.838542, 0.990648), i4 = c(0.044495,
0.82244, 0.322291, 0.393595)), .Names = c("ref", "nb", "i1",
"i2", "i3", "i4"), row.names = c(NA, -4L), class = c("data.table",
"data.frame"), .internal.selfref = <pointer: 0x0000000000320788>)

DT
#    ref nb       i1       i2       i3       i4
# 1:   3 12 0.000031 0.000183 0.000824 0.044495
# 2:   3 13 0.044495 0.155732 0.533939 0.822440
# 3:   3 14 0.822440 0.873416 0.838542 0.322291
# 4:   3 15 0.322291 0.648545 0.990648 0.393595
``````

Now I want to calculate rows sums, but only including columns which start with an "i" ("i1", "i2", etc)

I have used
`grep`
to create a vector of the column names to be summed:

``````listCol <- colnames(DT)[grep("i", colnames(DT))]
listCol
# [1] "i1" "i2" "i3" "i4"
``````

Then I have tried to loop over columns:

``````DT\$sum <- rep.int(0, nrow(DT))
for (i in listCol){
DT\$sum = DT\$sum + DT[ , get(i)]
}
``````

...which gives the desired output:

``````DT
#    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
``````

How can I improve my code? Many thanks!

This sub question include partially the answer to the previous one :

How to avoid this kind of strange notation :

``````myrowMeans = function (x){
rowMeans(x, na.rm = TRUE)
}
DT[ , var := myrowMeans(.SD-myrowMeans(.SD)^2), .SDcols = grep("i", colnames(DT))]
``````

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][]
``````