If you first put your dataframes into a list, you can index into each using seq_along()
:
dfs <- list(mtcars1 = mtcars, mtcars2 = mtcars)
for (i in seq_along(dfs)) {
dfs[[i]]$new <- dfs[[i]]$mpg * dfs[[i]]$cyl
}
Or, using lapply()
:
dfs <- lapply(dfs, \(x) {
x$new <- x$mpg * x$cyl
x
})
Result from either approach:
#> head(dfs$mtcars1)
mpg cyl disp hp drat wt qsec vs am gear carb new
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 126.0
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 126.0
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 91.2
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 128.4
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 149.6
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1 108.6
If you really want to leave your dataframes loose in the environment, you could do something like
for (nm in c("mtcars1", "mtcars2")) {
x <- get(nm)
x$new <- x$mpg * x$cyl
assign(nm, x)
}
Result:
#> head(mtcars1)
mpg cyl disp hp drat wt qsec vs am gear carb new
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 126.0
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 126.0
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 91.2
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 128.4
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 149.6
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1 108.6