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)}

Answer 2

You can use colSums(a[,c("Var1", "Var2")]) or rowSums(a[,c("Var_1", "Var_2")]). In your case you want the latter.