Loop through and mutate multiple columns using an incrementing variable - r

Question

My goal is to perform multiple column operations in one line of code without hard coding the variable names.
structure(list(Subject = 1:6, Congruent_1 = c(359, 391, 384,
316, 287, 403), Congruent_2 = c(361, 378, 322, 286, 276, 363),
Congruent_3 = c(342, 355, 334, 274, 297, 335), Congruent_4 = c(365,
503, 324, 256, 266, 388), Congruent_5 = c(335, 354, 320,
272, 260, 337), Incongruent_1 = c(336, 390, 402, 305, 310,
400), Incongruent_2 = c(366, 407, 386, 280, 243, 393), Incongruent_3 = c(323,
455, 317, 308, 259, 325), Incongruent_4 = c(361, 392, 357,
274, 342, 350), Incongruent_5 = c(300, 366, 378, 263, 258,
349)), row.names = c(NA, 6L), class = "data.frame")
My data looks like this.
I want need to do column subtraction and save those new values into new columns. For example, a new column by the name of selhist_1 should be computed as Incongruent_1 - Congruent_1. I tried to write a for loop that indexes the existing columns by their names and creates new columns using the same indexing variable:
for(i in 1:5)(
DP4 = mutate(DP4, as.name(paste("selhistB_",i,sep="")) = as.name(paste("Incongruent_",i,sep="")) - as.name(paste("Congruent_",i,sep="")))
)
but I received this error:
Error: unexpected '=' in: "for(i in 1:5)( DP4 = mutate(DP4, as.name(paste("selhistB_",i,sep="")) ="
I rather use this modular approach, as opposed to hard coding and writing out "selhistB = incongruent_1 - congruent_1" five times, using the mutate() function.
I also wonder if i could achieve the same goal on the long version of this data, and maybe it would make more sense.

Answer 1

library(dplyr)
d %>%
pivot_longer(-Subject,
names_to = c(".value", "id"),
names_sep = "_") %>%
mutate(selhistB = Incongruent - Congruent) %>%
pivot_wider(names_from = id, values_from = c(Congruent, Incongruent, selhistB))
Or just skip the last pivot, and keep everything long.

Answer 2

As long as you are already using tidyverse packages, the following code will do exactly what you need:
library(dplyr)
for(i in 1:5){
DP4 <- DP4 %>% mutate(UQ(sym(paste0("selhistB_",i))) :=
UQ(sym(paste0("Incongruent_",i))) - UQ(sym(paste0("Congruent_",i))))
}
DP4
Subject Congruent_1 Congruent_2 Congruent_3 Congruent_4 Congruent_5
1 1 359 361 342 365 335
2 2 391 378 355 503 354
3 3 384 322 334 324 320
4 4 316 286 274 256 272
5 5 287 276 297 266 260
6 6 403 363 335 388 337
Incongruent_1 Incongruent_2 Incongruent_3 Incongruent_4 Incongruent_5
1 336 366 323 361 300
2 390 407 455 392 366
3 402 386 317 357 378
4 305 280 308 274 263
5 310 243 259 342 258
6 400 393 325 350 349
selhistB_1 selhistB_2 selhistB_3 selhistB_4 selhistB_5
1 23 -5 19 4 35
2 1 -29 -100 111 -12
3 -18 -64 17 -33 -58
4 11 6 -34 -18 9
5 -23 33 38 -76 2
6 3 -30 10 38 -12

Answer 3

You can use split.default and split on column names suffix, then loop over the list and subtract column 2 from column 1, i.e.
lapply(split.default(df[-1], sub('.*_', '', names(df[-1]))), function(i) i[1] - i[2])

Answer 4

Using subtract over all matching columns, then cbind, try:
x <- df1[, grepl("^C", colnames(df1)) ] - df1[, grepl("^I", colnames(df1)) ]
names(x) <- paste0("selhistB_", seq_along(names(x)))
res <- cbind(df1, x)
res
Subject Congruent_1 Congruent_2 Congruent_3 Congruent_4 Congruent_5
1 1 359 361 342 365 335
2 2 391 378 355 503 354
3 3 384 322 334 324 320
4 4 316 286 274 256 272
5 5 287 276 297 266 260
6 6 403 363 335 388 337
Incongruent_1 Incongruent_2 Incongruent_3 Incongruent_4 Incongruent_5
1 336 366 323 361 300
2 390 407 455 392 366
3 402 386 317 357 378
4 305 280 308 274 263
5 310 243 259 342 258
6 400 393 325 350 349
selhistB_1 selhistB_2 selhistB_3 selhistB_4 selhistB_5
1 23 -5 19 4 35
2 1 -29 -100 111 -12
3 -18 -64 17 -33 -58
4 11 6 -34 -18 9
5 -23 33 38 -76 2
6 3 -30 10 38 -12