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+ ungroup.tbl_cube() is needed for dplyr 1.0.3 #3

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merged 3 commits into from Nov 20, 2020

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romainfrancois
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Since tidyverse/dplyr#5598 (for upcoming dplyr 1.0.3), the implicit mutate() step that is e.g. used by group_by() operates on ungrouped data there needs a ungroup.tbl_cube.

I believe a grouped cube is just a tbl_cube with a groups item added.

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@hadley
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hadley commented Nov 20, 2020

Since you're in here, can you bump the requirement to 3.3 and update the GHA workflow?

@hadley hadley merged commit bbe2276 into hadley:master Nov 20, 2020
@romainfrancois romainfrancois deleted the dplyr_1_0_3 branch November 20, 2020 15:26
netbsd-srcmastr pushed a commit to NetBSD/pkgsrc that referenced this pull request Jun 12, 2021
# 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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