# 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`mutate(across())` perform as well as the superseded colwise equivalents (#5697).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 https://github.com/hadley/cubelyr/pull/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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