Incorrect translation of data-frame-format dots in `summarise()`

[owenjonesphe]

In the Arguments section of help(dtplyr::summarise.dtplyr_step), the "dots" argument is explained in a similar way to dplyr::summarise():

... \<data-masking> Name-value pairs of summary functions. The name will be the name of the variable in the result. The value can be:

• A vector of length 1, e.g. min(x), n(), or sum(is.na(y)).
• A data frame, to add multiple columns from a single expression.

However, using a data frame within ... fails when summarising lazy_dt objects. The error message suggests that {data.table} is being asked to create a single column containing the entire data frame object, rather than multiple columns based on the columns of the data frame.

# tibble - works as expected
mtcars |> 
  dplyr::summarise(
    stats::quantile(mpg, probs = c(0.5, 0.9)) |> 
      tibble::as_tibble_row(),
    .by = cyl
  )
#>   cyl  50%   90%
#> 1   6 19.7 21.16
#> 2   4 26.0 32.40
#> 3   8 15.2 18.28

# lazy_dt - error when constructing `j`
mtcars |> 
  dtplyr::lazy_dt() |> 
  dplyr::summarise(
    stats::quantile(mpg, probs = c(0.5, 0.9)) |> 
      tibble::as_tibble_row(),
    .by = cyl
  )
#> Error in `[.data.table`(`_DT1`, , .(`tibble::as_tibble_row(stats::quantile(mpg, probs = c(0.5, 0.9)))` = tibble::as_tibble_row(stats::quantile(mpg, : All items in j=list(...) should be atomic vectors or lists. If you are trying something like j=list(.SD,newcol=mean(colA)) then use := by group instead (much quicker), or cbind or merge afterwards.

^{Created on 2023-11-02 with reprex v2.0.2}

Session info

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