R Summary based on column name length - r

Question

I have the following problem:
I have a matrix with 80 columns which names have either 10/11, 21/22,31/32 or 42/43 characters. The names are totally different but the lenth fits always in one of the four groups. Now I would like to add four columns were I get the sum of all the values of columns corresponding to one group. Here is a little example of what I mean
a<-rnorm(1:100)
b<-rnorm(1:100)
cc<-rnorm(1:100)
dd<-rnorm(1:100)
eee<-rnorm(1:100)
fff<-rnorm(1:100)
g<-data.frame(a,b,cc,dd,eee,fff)
g$group1<-"sum of all columns of with headers of length 1 (in this case a+b)"
g$group2<-"sum of all columns of with headers of length 2 (in this case cc+dd)"
g$group3<-"sum of all columns of with headers of length 3 (in this case eee+fff)"
I was able to transfer the matrix to a dataframe using melt() and carrying out the operation using stringr::str_length(). However, I could not transform this back to a matrix which I really need as final output. The columns are not in order and ordering would not help me much, since the number of columns depends on the outcome of the previous calculation and it would be too tedious to define dataframe ranges every time again.
Hope you can help.

Answer 1

You want this:
tmp <- nchar(names(g))
chargroups <- split(1:dim(g)[2], tmp)
# `chargroups` is a list of groups of columns with same number of letters in name
sapply(chargroups, function(x) {
if(length(x)>1) # rowSums can only accept 2+-dimensional object
rowSums(g[,x])
else
g[,x]
})
# `x` is, for each number of letters, a vector of column indices of `g`
The key part of this is that nchar is going to determine how long the column names are. The rest is pretty straightforward.
EDIT: In your actual code, though you should deal with the ranges of name lengths by just doing something like the following after you define tmp but before the sapply statement:
tmp[tmp==10] <- 11
tmp[tmp==21] <- 22
tmp[tmp==31] <- 32
tmp[tmp==32] <- 43

Answer 2

Another approach
set.seed(123)
a <- rnorm(1:100)
b <- rnorm(1:100)
cc <- rnorm(1:100)
dd <- rnorm(1:100)
eee <- rnorm(1:100)
fff <- rnorm(1:100)
g <- data.frame(a,b,cc,dd,eee,fff)
for ( i in 1:3 )
eval(parse(text = sprintf("g$group%s <- rowSums(g[nchar(names(g)) == %s])", i, i)))
## 'data.frame': 100 obs. of 9 variables:
## $ a : num -0.5605 -0.2302 1.5587 0.0705 0.1293 ...
## $ b : num -0.71 0.257 -0.247 -0.348 -0.952 ...
## $ cc : num 2.199 1.312 -0.265 0.543 -0.414 ...
## $ dd : num -0.715 -0.753 -0.939 -1.053 -0.437 ...
## $ eee : num -0.0736 -1.1687 -0.6347 -0.0288 0.6707 ...
## $ fff : num -0.602 -0.994 1.027 0.751 -1.509 ...
## $ group1: num -1.2709 0.0267 1.312 -0.277 -0.8223 ...
## $ group2: num 1.484 0.56 -1.204 -0.509 -0.851 ...
## $ group3: num -0.675 -2.162 0.392 0.722 -0.838 ...