Efficiently sum across multiple columns in R

Question

I have the following condensed data set:

a<-as.data.frame(c(2000:2005))
a$Col1<-c(1:6)
a$Col2<-seq(2,12,2)

colnames(a)<-c("year","Col1","Col2")

for (i in 1:2){
  a[[paste("Var_", i, sep="")]]<-i*a[[paste("Col", i, sep="")]]
}

I would like to sum the columns Var1 and Var2, which I use:

a$sum<-a$Var_1 + a$Var_2

In reality my data set is much larger - I would like to sum from Var_1 to Var_n (n can be upto 20). There must be a more efficient way to do this than:

 a$sum<-a$Var_1 + ... + a$Var_n

Answer 1

Here's a solution using the tidyverse. You can extend it to as many columns as you like using the select() function to select the appropriate columns within a mutate().

library(tidyverse)

a<-as.data.frame(c(2000:2005))
a$Col1<-c(1:6)
a$Col2<-seq(2,12,2)

colnames(a)<-c("year","Col1","Col2")

for (i in 1:2){
    a[[paste("Var_", i, sep="")]]<-i*a[[paste("Col", i, sep="")]]
}
a
#>   year Col1 Col2 Var_1 Var_2
#> 1 2000    1    2     1     4
#> 2 2001    2    4     2     8
#> 3 2002    3    6     3    12
#> 4 2003    4    8     4    16
#> 5 2004    5   10     5    20
#> 6 2005    6   12     6    24

# Tidyverse solution
a %>%
    mutate(Total = select(., Var_1:Var_2) %>% rowSums(na.rm = TRUE))
#>   year Col1 Col2 Var_1 Var_2 Total
#> 1 2000    1    2     1     4     5
#> 2 2001    2    4     2     8    10
#> 3 2002    3    6     3    12    15
#> 4 2003    4    8     4    16    20
#> 5 2004    5   10     5    20    25
#> 6 2005    6   12     6    24    30

^{Created on 2019-01-01 by the reprex package (v0.2.1)}