3

Sample data:

sampdat <- data.frame(grp=rep(c("a","b","c"),c(2,3,5)), x1=seq(0,.9,0.1),x2=seq(.3,.75,0.05), y1=c(1:10), y2=c(11:20))

I would like to have the following data, but i have 100+ variables for which i'd like to apply a function with two variables:

myfun <- function(x,y) {
  z=x*y
}
needdat <- sampdat %>% mutate(z1=x1*y1, z2=x2*y2)

What is the most efficient approach to doing this using dplyr's across and summarise?

Thanks in advance for your suggestions/solutions!

Best, SaM

Sam
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1 Answers1

3

Easier would be to use two across

library(dplyr)
library(stringr)
sampdat %>% 
   mutate(across(starts_with('x'),
   .names = "{str_replace(.col, 'x', 'z')}") * 
        across(starts_with('y')))

-output

   grp  x1   x2 y1 y2  z1   z2
1    a 0.0 0.30  1 11 0.0  3.3
2    a 0.1 0.35  2 12 0.2  4.2
3    b 0.2 0.40  3 13 0.6  5.2
4    b 0.3 0.45  4 14 1.2  6.3
5    b 0.4 0.50  5 15 2.0  7.5
6    c 0.5 0.55  6 16 3.0  8.8
7    c 0.6 0.60  7 17 4.2 10.2
8    c 0.7 0.65  8 18 5.6 11.7
9    c 0.8 0.70  9 19 7.2 13.3
10   c 0.9 0.75 10 20 9.0 15.0

Or with dplyover

library(dplyover)
sampdat %>% 
  mutate(across2(starts_with('x'), starts_with('y'),
   ~ .x * .y, .names = "z{xcol}"))
akrun
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