is missing from the reprex. See the FAQ. So I can only offer general guidance.
Similar situation
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
mtcars %>% select(.test = MPG)
#> Error in `select()`:
#> ! Can't subset columns that don't exist.
#> ✖ Column `MPG` doesn't exist.
#> Backtrace:
#> ▆
#> 1. ├─mtcars %>% select(.test = MPG)
#> 2. ├─dplyr::select(., .test = MPG)
#> 3. ├─dplyr:::select.data.frame(., .test = MPG)
#> 4. │ └─tidyselect::eval_select(expr(c(...)), data = .data, error_call = error_call)
#> 5. │ └─tidyselect:::eval_select_impl(...)
#> 6. │ ├─tidyselect:::with_subscript_errors(...)
#> 7. │ │ └─rlang::try_fetch(...)
#> 8. │ │ └─base::withCallingHandlers(...)
#> 9. │ └─tidyselect:::vars_select_eval(...)
#> 10. │ └─tidyselect:::walk_data_tree(expr, data_mask, context_mask)
#> 11. │ └─tidyselect:::eval_c(expr, data_mask, context_mask)
#> 12. │ └─tidyselect:::reduce_sels(node, data_mask, context_mask, init = init)
#> 13. │ └─tidyselect:::walk_data_tree(new, data_mask, context_mask)
#> 14. │ └─tidyselect:::as_indices_sel_impl(...)
#> 15. │ └─tidyselect:::as_indices_impl(...)
#> 16. │ └─tidyselect:::chr_as_locations(x, vars, call = call, arg = arg)
#> 17. │ └─vctrs::vec_as_location(...)
#> 18. └─vctrs (local) `<fn>`()
#> 19. └─vctrs:::stop_subscript_oob(...)
#> 20. └─vctrs:::stop_subscript(...)
#> 21. └─rlang::abort(...)
colnames(mtcars)
#> [1] "mpg" "cyl" "disp" "hp" "drat" "wt" "qsec" "vs" "am" "gear"
#> [11] "carb"
mtcars %>% select(.test = mpg)
#> .test
#> Mazda RX4 21.0
#> Mazda RX4 Wag 21.0
#> Datsun 710 22.8
#> Hornet 4 Drive 21.4
#> Hornet Sportabout 18.7
#> Valiant 18.1
#> Duster 360 14.3
#> Merc 240D 24.4
#> Merc 230 22.8
#> Merc 280 19.2
#> Merc 280C 17.8
#> Merc 450SE 16.4
#> Merc 450SL 17.3
#> Merc 450SLC 15.2
#> Cadillac Fleetwood 10.4
#> Lincoln Continental 10.4
#> Chrysler Imperial 14.7
#> Fiat 128 32.4
#> Honda Civic 30.4
#> Toyota Corolla 33.9
#> Toyota Corona 21.5
#> Dodge Challenger 15.5
#> AMC Javelin 15.2
#> Camaro Z28 13.3
#> Pontiac Firebird 19.2
#> Fiat X1-9 27.3
#> Porsche 914-2 26.0
#> Lotus Europa 30.4
#> Ford Pantera L 15.8
#> Ferrari Dino 19.7
#> Maserati Bora 15.0
#> Volvo 142E 21.4
# alternatively to just multiply two columns
mtcars$mpg * mtcars$cyl
#> [1] 126.0 126.0 91.2 128.4 149.6 108.6 114.4 97.6 91.2 115.2 106.8 131.2
#> [13] 138.4 121.6 83.2 83.2 117.6 129.6 121.6 135.6 86.0 124.0 121.6 106.4
#> [25] 153.6 109.2 104.0 121.6 126.4 118.2 120.0 85.6
# or
mtcars[1] * mtcars[2]
#> mpg
#> Mazda RX4 126.0
#> Mazda RX4 Wag 126.0
#> Datsun 710 91.2
#> Hornet 4 Drive 128.4
#> Hornet Sportabout 149.6
#> Valiant 108.6
#> Duster 360 114.4
#> Merc 240D 97.6
#> Merc 230 91.2
#> Merc 280 115.2
#> Merc 280C 106.8
#> Merc 450SE 131.2
#> Merc 450SL 138.4
#> Merc 450SLC 121.6
#> Cadillac Fleetwood 83.2
#> Lincoln Continental 83.2
#> Chrysler Imperial 117.6
#> Fiat 128 129.6
#> Honda Civic 121.6
#> Toyota Corolla 135.6
#> Toyota Corona 86.0
#> Dodge Challenger 124.0
#> AMC Javelin 121.6
#> Camaro Z28 106.4
#> Pontiac Firebird 153.6
#> Fiat X1-9 109.2
#> Porsche 914-2 104.0
#> Lotus Europa 121.6
#> Ford Pantera L 126.4
#> Ferrari Dino 118.2
#> Maserati Bora 120.0
#> Volvo 142E 85.6
# or add to data frame
(mtcars$.test <- mtcars[1] * mtcars[2])
#> mpg
#> Mazda RX4 126.0
#> Mazda RX4 Wag 126.0
#> Datsun 710 91.2
#> Hornet 4 Drive 128.4
#> Hornet Sportabout 149.6
#> Valiant 108.6
#> Duster 360 114.4
#> Merc 240D 97.6
#> Merc 230 91.2
#> Merc 280 115.2
#> Merc 280C 106.8
#> Merc 450SE 131.2
#> Merc 450SL 138.4
#> Merc 450SLC 121.6
#> Cadillac Fleetwood 83.2
#> Lincoln Continental 83.2
#> Chrysler Imperial 117.6
#> Fiat 128 129.6
#> Honda Civic 121.6
#> Toyota Corolla 135.6
#> Toyota Corona 86.0
#> Dodge Challenger 124.0
#> AMC Javelin 121.6
#> Camaro Z28 106.4
#> Pontiac Firebird 153.6
#> Fiat X1-9 109.2
#> Porsche 914-2 104.0
#> Lotus Europa 121.6
#> Ford Pantera L 126.4
#> Ferrari Dino 118.2
#> Maserati Bora 120.0
#> Volvo 142E 85.6
# create a new data frame
(new <- cbind(mtcars[1:2],mtcars[1] * mtcars[2]))
#> mpg cyl mpg
#> Mazda RX4 21.0 6 126.0
#> Mazda RX4 Wag 21.0 6 126.0
#> Datsun 710 22.8 4 91.2
#> Hornet 4 Drive 21.4 6 128.4
#> Hornet Sportabout 18.7 8 149.6
#> Valiant 18.1 6 108.6
#> Duster 360 14.3 8 114.4
#> Merc 240D 24.4 4 97.6
#> Merc 230 22.8 4 91.2
#> Merc 280 19.2 6 115.2
#> Merc 280C 17.8 6 106.8
#> Merc 450SE 16.4 8 131.2
#> Merc 450SL 17.3 8 138.4
#> Merc 450SLC 15.2 8 121.6
#> Cadillac Fleetwood 10.4 8 83.2
#> Lincoln Continental 10.4 8 83.2
#> Chrysler Imperial 14.7 8 117.6
#> Fiat 128 32.4 4 129.6
#> Honda Civic 30.4 4 121.6
#> Toyota Corolla 33.9 4 135.6
#> Toyota Corona 21.5 4 86.0
#> Dodge Challenger 15.5 8 124.0
#> AMC Javelin 15.2 8 121.6
#> Camaro Z28 13.3 8 106.4
#> Pontiac Firebird 19.2 8 153.6
#> Fiat X1-9 27.3 4 109.2
#> Porsche 914-2 26.0 4 104.0
#> Lotus Europa 30.4 4 121.6
#> Ford Pantera L 15.8 8 126.4
#> Ferrari Dino 19.7 6 118.2
#> Maserati Bora 15.0 8 120.0
#> Volvo 142E 21.4 4 85.6
Created on 2023-03-31 with reprex v2.0.2