+ ungroup.tbl_cube() is needed for dplyr 1.0.3 #3
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The failure on 3.2 is because digest depends on 3.3 now. https://github.com/hadley/cubelyr/pull/3/checks?check_run_id=1430378980#step:9:12 since: eddelbuettel/digest@35ad0b7#diff-9cc358405149db607ff830a16f0b4b21f7366e3c99ec00d52800acebe21b231c |
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Since you're in here, can you bump the requirement to 3.3 and update the GHA workflow? |
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# dplyr 1.0.6 * `add_count()` is now generic (#5837). * `if_any()` and `if_all()` abort when a predicate is mistakingly used as `.cols=` (#5732). * Multiple calls to `if_any()` and/or `if_all()` in the same expression are now properly disambiguated (#5782). * `filter()` now inlines `if_any()` and `if_all()` expressions. This greatly improves performance with grouped data frames. * Fixed behaviour of `...` in top-level `across()` calls (#5813, #5832). * `across()` now inlines lambda-formulas. This is slightly more performant and will allow more optimisations in the future. * Fixed issue in `bind_rows()` causing lists to be incorrectly transformed as data frames (#5417, #5749). * `select()` no longer creates duplicate variables when renaming a variable to the same name as a grouping variable (#5841). * `dplyr_col_select()` keeps attributes for bare data frames (#5294, #5831). * Fixed quosure handling in `dplyr::group_by()` that caused issues with extra arguments (tidyverse/lubridate#959). * Removed the `name` argument from the `compute()` generic (@ianmcook, #5783). * row-wise data frames of 0 rows and list columns are supported again (#5804). # dplyr 1.0.5 * Fixed edge case of `slice_sample()` when `weight_by=` is used and there 0 rows (#5729). * `across()` can again use columns in functions defined inline (#5734). * Using testthat 3rd edition. * Fixed bugs introduced in `across()` in previous version (#5765). * `group_by()` keeps attributes unrelated to the grouping (#5760). * The `.cols=` argument of `if_any()` and `if_all()` defaults to `everything()`. # dplyr 1.0.4 * Improved performance for `across()`. This makes `summarise(across())` and `mutate(across())` perform as well as the superseded colwise equivalents (#5697). * New functions `if_any()` and `if_all()` (#4770, #5713). * `summarise()` silently ignores NULL results (#5708). * Fixed a performance regression in `mutate()` when warnings occur once per group (#5675). We no longer instrument warnings with debugging information when `mutate()` is called within `suppressWarnings()`. # dplyr 1.0.3 * `summarise()` no longer informs when the result is ungrouped (#5633). * `group_by(.drop = FALSE)` preserves ordered factors (@brianrice2, #5545). * `count()` and `tally()` are now generic. * Removed default fallbacks to lazyeval methods; this will yield better error messages when you call a dplyr function with the wrong input, and is part of our long term plan to remove the deprecated lazyeval interface. * `inner_join()` gains a `keep` parameter for consistency with the other mutating joins (@patrickbarks, #5581). * Improved performance with many columns, with a dynamic data mask using active bindings and lazy chops (#5017). * `mutate()` and friends preserves row names in data frames once more (#5418). * `group_by()` uses the ungrouped data for the implicit mutate step (#5598). You might have to define an `ungroup()` method for custom classes. For example, see hadley/cubelyr#3. * `relocate()` can rename columns it relocates (#5569). * `distinct()` and `group_by()` have better error messages when the mutate step fails (#5060). * Clarify that `between()` is not vectorised (#5493). * Fixed `across()` issue where data frame columns would could not be referred to with `all_of()` in the nested case (`mutate()` within `mutate()`) (#5498). * `across()` handles data frames with 0 columns (#5523). * `mutate()` always keeps grouping variables, unconditional to `.keep=` (#5582). * dplyr now depends on R 3.3.0 # dplyr 1.0.2 * Fixed `across()` issue where data frame columns would mask objects referred to from `all_of()` (#5460). * `bind_cols()` gains a `.name_repair` argument, passed to `vctrs::vec_cbind()` (#5451) * `summarise(.groups = "rowwise")` makes a rowwise data frame even if the input data is not grouped (#5422). # dplyr 1.0.1 * New function `cur_data_all()` similar to `cur_data()` but includes the grouping variables (#5342). * `count()` and `tally()` no longer automatically weights by column `n` if present (#5298). dplyr 1.0.0 introduced this behaviour because of Hadley's faulty memory. Historically `tally()` automatically weighted and `count()` did not, but this behaviour was accidentally changed in 0.8.2 (#4408) so that neither automatically weighted by `n`. Since 0.8.2 is almost a year old, and the automatically weighting behaviour was a little confusing anyway, we've removed it from both `count()` and `tally()`. Use of `wt = n()` is now deprecated; now just omit the `wt` argument. * `coalesce()` now supports data frames correctly (#5326). * `cummean()` no longer has off-by-one indexing problem (@Cropgen, #5287). * The call stack is preserved on error. This makes it possible to `recover()` into problematic code called from dplyr verbs (#5308).
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Since tidyverse/dplyr#5598 (for upcoming dplyr 1.0.3), the implicit
mutate()step that is e.g. used bygroup_by()operates on ungrouped data there needs aungroup.tbl_cube.I believe a grouped cube is just a
tbl_cubewith agroupsitem added.