`lazy_dt` not support `dplyr/across`?

Question

The code show error message as below

This tidyselect interface doesn't support predicates.

It means lazy_dt not support across ? Thanks !

library(tidyverse)
library(dtplyr)
diamonds %>% lazy_dt() %>% group_by(color) %>% 
  summarise(across(where(is.numeric), ~ sum(.)))

Answer 1

The issue is that dtplyr does not support where(). See this closed issue on GH.

Instead one possible workaround would be to use a vector of the names of numeric columns with all_of:

library(tidyverse)
library(dtplyr)

num_cols <- names(diamonds)[
  sapply(diamonds, is.numeric)
]

diamonds %>%
  lazy_dt() %>%
  group_by(color) %>%
  summarise(across(all_of(num_cols), ~ sum(.)))
#> Source: local data table [7 x 8]
#> Call:   `_DT1`[, .(carat = sum(carat), depth = sum(depth), table = sum(table), 
#>     price = sum(price), x = sum(x), y = sum(y), z = sum(z)), 
#>     keyby = .(color)]
#> 
#>   color carat   depth   table    price      x      y      z
#>   <ord> <dbl>   <dbl>   <dbl>    <int>  <dbl>  <dbl>  <dbl>
#> 1 D     4457. 418005. 388916. 21476439 36701. 36728. 22648.
#> 2 E     6445. 604104. 563241. 30142944 53017. 53090. 32729.
#> 3 F     7028. 588690. 548031. 35542866 53578. 53621. 33058.
#> 4 G     8708. 697361. 646903. 45158240 64111. 64141. 39579.
#> 5 H     7572. 513493. 477628. 37257301 49686. 49698. 30691.
#> 6 I     5568. 335331. 312184  27608146 33740. 33740. 20850.
#> # ℹ 1 more row
#> 
#> # Use as.data.table()/as.data.frame()/as_tibble() to access results

or use summarise_if (however, be aware that summarise_if is superseded):

diamonds %>%
  lazy_dt() %>%
  group_by(color) %>%
  summarise_if(~ is.numeric(.x), sum)
#> Source: local data table [7 x 8]
#> Call:   `_DT3`[, .(carat = sum(carat), depth = sum(depth), table = sum(table), 
#>     price = sum(price), x = sum(x), y = sum(y), z = sum(z)), 
#>     keyby = .(color)]
#> 
#>   color carat   depth   table    price      x      y      z
#>   <ord> <dbl>   <dbl>   <dbl>    <int>  <dbl>  <dbl>  <dbl>
#> 1 D     4457. 418005. 388916. 21476439 36701. 36728. 22648.
#> 2 E     6445. 604104. 563241. 30142944 53017. 53090. 32729.
#> 3 F     7028. 588690. 548031. 35542866 53578. 53621. 33058.
#> 4 G     8708. 697361. 646903. 45158240 64111. 64141. 39579.
#> 5 H     7572. 513493. 477628. 37257301 49686. 49698. 30691.
#> 6 I     5568. 335331. 312184  27608146 33740. 33740. 20850.
#> # ℹ 1 more row
#> 
#> # Use as.data.table()/as.data.frame()/as_tibble() to access results