Conditionally sum columns in R

Question

I'm working on converting Stata code to R. There's a snippet of code that creates a new variable and adds the column value if it meets specific parameters. For example, if a cell is greater than 0 and less than or equal to 3, that value would be added to newvar

gen newvar=0
 
local list a b c
foreach x of local list{
    qui replace newvar=newvar+`x' if `x'>0 & `x'<=3 
}

set.seed(5)
dat <- data.frame(a = rnorm(5), b = rnorm(5), c = rnorm(5))

Desired Output

Answer 1

A tidyverse approach

library(dplyr)
set.seed(5)
dat <- data.frame(a = rnorm(5), b = rnorm(5), c = rnorm(5))

conditional_sum <- function(x,a = 0,b = 3){
  sum(x[x > a & x <= b],na.rm = TRUE)
}

dat %>% 
  rowwise() %>% 
  mutate(newvar = conditional_sum(c_across()))

# A tibble: 5 x 4
# Rowwise: 
        a      b      c newvar
    <dbl>  <dbl>  <dbl>  <dbl>
1 -0.841  -0.603  1.23  1.23  
2  1.38   -0.472 -0.802 1.38  
3 -1.26   -0.635 -1.08  0     
4  0.0701 -0.286 -0.158 0.0701
5  1.71    0.138 -1.07  1.85 

Answer 2

Replace the elements that are not satisfying the condition to NA and get the rowSums on the rest of the elements to create the 'newvar'

dat$newvar <-  rowSums(NA^(dat <=0|dat >=3)*dat, na.rm = TRUE)

-output

> dat
            a          b          c     newvar
1 -0.84085548 -0.6029080  1.2276303 1.22763034
2  1.38435934 -0.4721664 -0.8017795 1.38435934
3 -1.25549186 -0.6353713 -1.0803926 0.00000000
4  0.07014277 -0.2857736 -0.1575344 0.07014277
5  1.71144087  0.1381082 -1.0717600 1.84954910

Answer 3

A common way to perform rowwise operations is using the apply function. Eg:

dat$newvar <- apply(dat, 1, \(r) sum(r[r > 0 & r <= 3]))

Read as: Apply a function to every row of dat . The function takes a vector r , and sums the elements of r which satisfy the criterio.

Results in

            a          b          c     newvar
1 -0.84085548 -0.6029080  1.2276303 1.22763034
2  1.38435934 -0.4721664 -0.8017795 1.38435934
3 -1.25549186 -0.6353713 -1.0803926 0.00000000
4  0.07014277 -0.2857736 -0.1575344 0.07014277
5  1.71144087  0.1381082 -1.0717600 1.84954910