Better error message for empty tidyselect quosure

[sda030]

The following empty tidyselect::all_of() would have given an empty data frame in dplyr::select() but here gives a rather uninformative error. Perhaps a "Selection is empty.".

---

Brief description of the problem

expect_variables <- c()
tidyr::unite(mtcars, col = "merged", tidyselect::all_of(expect_variables))
#> Error in `df_append()`:
#> ! `after` must be a whole number, not an integer `NA`.
#> ℹ This is an internal error that was detected in the tidyr package.
#>   Please report it at <https://github.com/tidyverse/tidyr/issues> with a reprex
#>   (<https://tidyverse.org/help/>) and the full backtrace.
---
Backtrace:
    ▆
 1. ├─mtcars %>% ...
 2. ├─tidyr::unite(...)
 3. └─tidyr:::unite.data.frame(...)
 4.   └─tidyr:::df_append(after = after)
 5.     └─tidyr:::check_number_whole(after, min = 0L, max = n, .internal = TRUE)
 6.       └─tidyr:::.rlang_types_check_number(...)
 7.         └─tidyr (local) .stop(x, what, ...)
 8.           └─tidyr:::stop_input_type(...)
 9.             └─rlang::abort(message, ..., call = call, arg = arg)

^{Created on 2024-04-15 with reprex v2.1.0}

Session info

``` r sessioninfo::session_info() #> ─ Session info ─────────────────────────────────────────────────────────────── #> setting value #> version R version 4.3.2 (2023-10-31 ucrt) #> os Windows 11 x64 (build 22621) #> system x86_64, mingw32 #> ui RTerm #> language (EN) #> collate nb.utf8 #> ctype nb.utf8 #> tz Europe/Oslo #> date 2024-04-15 #> pandoc 3.1.12.3 @ C:/PROGRA~1/Pandoc/ (via rmarkdown) #> #> ─ Packages ─────────────────────────────────────────────────────────────────── #> package * version date (UTC) lib source #> cli 3.6.2 2023-12-11 [1] RSPM (R 4.3.0) #> digest 0.6.35 2024-03-11 [1] CRAN (R 4.3.3) #> dplyr 1.1.4 2023-11-17 [1] RSPM (R 4.3.0) #> evaluate 0.23 2023-11-01 [1] RSPM (R 4.3.0) #> fansi 1.0.6 2023-12-08 [1] CRAN (R 4.3.2) #> fastmap 1.1.1 2023-02-24 [1] CRAN (R 4.2.3) #> fs 1.6.3 2023-07-20 [1] CRAN (R 4.3.1) #> generics 0.1.3 2022-07-05 [1] CRAN (R 4.2.3) #> glue 1.7.0 2024-01-09 [1] CRAN (R 4.3.2) #> htmltools 0.5.8.1 2024-04-04 [1] CRAN (R 4.3.3) #> knitr 1.45 2023-10-30 [1] RSPM (R 4.3.0) #> lifecycle 1.0.4 2023-11-07 [1] RSPM (R 4.3.0) #> magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.2.3) #> pillar 1.9.0 2023-03-22 [1] CRAN (R 4.2.3) #> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.2.3) #> purrr 1.0.2 2023-08-10 [1] CRAN (R 4.3.1) #> R.cache 0.16.0 2022-07-21 [1] CRAN (R 4.2.3) #> R.methodsS3 1.8.2 2022-06-13 [1] CRAN (R 4.2.2) #> R.oo 1.26.0 2024-01-24 [1] CRAN (R 4.3.2) #> R.utils 2.12.3 2023-11-18 [1] RSPM (R 4.3.0) #> R6 2.5.1 2021-08-19 [1] CRAN (R 4.2.3) #> reprex 2.1.0 2024-01-11 [1] CRAN (R 4.3.1) #> rlang 1.1.3 2024-01-10 [1] CRAN (R 4.3.2) #> rmarkdown 2.26 2024-03-05 [1] CRAN (R 4.3.3) #> rstudioapi 0.15.0 2023-07-07 [1] CRAN (R 4.3.1) #> sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.2.3) #> styler 1.10.2 2023-08-29 [1] RSPM (R 4.3.0) #> tibble 3.2.1 2023-03-20 [1] CRAN (R 4.2.3) #> tidyr 1.3.1 2024-01-24 [1] CRAN (R 4.3.2) #> tidyselect 1.2.1 2024-03-11 [1] CRAN (R 4.3.3) #> utf8 1.2.4 2023-10-22 [1] RSPM (R 4.3.0) #> vctrs 0.6.5 2023-12-01 [1] RSPM (R 4.3.0) #> withr 3.0.0 2024-01-16 [1] RSPM (R 4.3.1) #> xfun 0.42 2024-02-08 [1] CRAN (R 4.3.2) #> yaml 2.3.8 2023-12-11 [1] RSPM (R 4.3.0) #> #> [1] C:/Users/py128/AppData/Local/R/win-library #> [2] C:/Program Files/R/R-4.3.2/library #> #> ────────────────────────────────────────────────────────────────────────────── ```

[DavisVaughan]

Thanks for the report!

Note to self:

This occurs because from_vars here is integer(): https://github.com/tidyverse/tidyr/blob/c6c126a61f67a10b5ab9ce6bb1d9dbbb7a380bbd/R/unite.R#L48

Resulting in an NA for first_pos here: https://github.com/tidyverse/tidyr/blob/c6c126a61f67a10b5ab9ce6bb1d9dbbb7a380bbd/R/unite.R#L72

I think we have two options:

• Error if from_vars is empty
• Return a column named using col with each cell filled with "", i.e. the "initial" reduction value that would theoretically be built upon if you would have actually selected columns. It would be positioned at the end of the data frame.

[catalamarti]

hi @DavisVaughan I will work in the second approach if that's fine