Below is reprex.

Wondering if #tidyeval gurus out there can find an equivalent solution with `dplyr::mutate_at()`

.

I attempted solutions suggested by @cderv in issue #20562, but no luck this time as there are multiple columns.

Look forward to enlightenment.

Thanks!

```
library(tidyverse)
tibble::tribble(
~wht.x, ~wht.y, ~whp.x, ~whp.y, ~group_id,
NaN, 575, NaN, 478.18, 1L,
NaN, 547.6, NaN, 1021, 2L,
NaN, 547.6, NaN, 1021.24, 3L,
NaN, 547.6, NaN, 948.64, 4L,
NaN, 544.2, NaN, 994.02, 5L,
NaN, 544.7, NaN, 997.24, 6L
) -> data
# desired outcome
data %>%
mutate(whp.x = coalesce(whp.x, whp.y),
wht.x = coalesce(wht.x, wht.y))
#> # A tibble: 6 x 5
#> wht.x wht.y whp.x whp.y group_id
#> <dbl> <dbl> <dbl> <dbl> <int>
#> 1 575 575 478. 478. 1
#> 2 548. 548. 1021 1021 2
#> 3 548. 548. 1021. 1021. 3
#> 4 548. 548. 949. 949. 4
#> 5 544. 544. 994. 994. 5
#> 6 545. 545. 997. 997. 6
```