I am working on a bootstrapping set-up with many different estimates in `rsample`

based on the solution provided by @Max to one of my prior questions. My basic problem is that I have so many different estimates that I cannot explicitly list them all. The term part was relatively easy, but I cannot figure out what to do with the `estimate =`

part. The following is a simple illustration that works but requires explicitly listing the columns with the estimates.

```
suppressMessages(library(tidyverse))
library(rsample)
compute <- function(split, ...) {
df <- analysis(split) %>%
group_by(am) %>%
summarise(mean = mean(mpg)) %>%
pivot_wider(
names_from = am,
values_from = mean,
names_prefix = "am_"
)
tibble(term = names(df),
estimate = c(df$am_0, df$am_1))
}
set.seed(2)
bt <-
bootstraps(mtcars, times = 200, apparent = TRUE) %>%
mutate(ratio = map(splits, ~ compute(.x)))
int_pctl(bt, ratio)
#> Warning: Recommend at least 1000 non-missing bootstrap resamples for terms:
#> `am_0`, `am_1`.
#> # A tibble: 2 x 6
#> term .lower .estimate .upper .alpha .method
#> <chr> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 am_0 15.6 17.1 18.8 0.05 percentile
#> 2 am_1 20.8 24.3 27.4 0.05 percentile
```

^{Created on 2020-05-20 by the reprex package (v0.3.0)}

Neither `estimate = df`

nor `estimate = c(df)`

works for providing the results columns in the `compute`

function. Any suggestions for how to provide the estimates?