I looked for solutions here: Multiply columns in a data frame by a vector and here: What is the right way to multiply data frame by vector?, but it doesn't really work.
What I want to do is a more or less clean tidyverse way where I multiply columns by a vector and then add these as new columns to the existing data frame. Taking teh data example from the first link:
c1 <- c(1,2,3)
c2 <- c(4,5,6)
c3 <- c(7,8,9)
d1 <- data.frame(c1,c2,c3)
c1 c2 c3
1 1 4 7
2 2 5 8
3 3 6 9
v1 <- c(1,2,3)
my desired result would be:
c1 c2 c3 pro_c1 pro_c2 pro_c3
1 1 4 7 1 8 21
2 2 5 8 2 10 24
3 3 6 9 3 12 27
I tried:
library(tidyverse)
d1 |>
mutate(pro = sweep(across(everything()), 2, v1, "*"))
But here the problem is the new columns are actually a data frame within my data frame. And I'm struggling with turning this data frame-in-data frame into regular columns. I assume, I could probably first setNames on this inner data frame and then unnest, but wondering if there's a more direct way by looping over each column with across and feed it with the first/second/third element of v1?
(I know I could probably also first create a standalone data frame with the three new multiplied columns, give them a unique name and then bind_cols on both, d1 and the df with the products.)
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