dtplyr 1.2.0

New authors

@markfairbanks, @mgirlich, and @eutwt are now dtplyr authors in recognition of their significant and sustained contributions. Along with @eutwt, they supplied the bulk of the improvements in this release!

New features

• dtplyr gains translations for many more tidyr verbs:

  • drop_na() (@markfairbanks, #194)
  • complete() (@markfairbanks, #225)
  • expand() (@markfairbanks, #225)
  • fill() (@markfairbanks, #197)
  • pivot_longer() (@markfairbanks, #204)
  • replace_na() (@markfairbanks, #202)
  • nest() (@mgirlich, #251)
  • separate() (@markfairbanks, #269)

• tally() gains a translation (@mgirlich, #201).

• ifelse() is mapped to fifelse() (@markfairbanks, #220).

Minor improvements and bug fixes

• slice() helpers (slice_head(), slice_tail(), slice_min(), slice_max()
  and slice_sample()) now accept negative values for n and prop.

• across() defaults to everything() when .cols isn't provided
  (@markfairbanks, #231), and handles named selections (@eutwt #293).
  It ˜ow handles .fns arguments in more forms (@eutwt #288):

  • Anonymous functions, such as function(x) x + 1
  • Formulas which don't require a function call, such as ~ 1

• arrange(dt, desc(col)) is translated to dt[order(-col)] in order to
  take advantage of data.table's fast order (@markfairbanks, #227).

• count() applied to data.tables no longer breaks when dtplyr is loaded
  (@mgirlich, #201).

• case_when() supports use of T to specify the default (#272).

• filter() errors for named input, e.g. filter(dt, x = 1)
  (@mgirlich, #267) and works for negated logical columns (@mgirlich, @211).

• group_by() ungroups when no grouping variables are specified
  (@mgirlich, #248), and supports inline mutation like group_by(dt, y = x)
  (@mgirlich, #246).

• if_else() named arguments are translated to the correct arguments in
  data.table::fifelse() (@markfairbanks, #234). if_else()
  supports .data and .env pronouns (@markfairbanks, #220).

• if_any() and if_all() default to everything() when .cols isn't
  provided (@eutwt, #294).

• intersect()/union()/union_all()/setdiff() convert data.table inputs
  to lazy_dt() (#278).

• lag()/lead() are translated to shift().

• lazy_dt() keeps groups (@mgirlich, #206).

• left_join() produces the same column order as dplyr
  (@markfairbanks, #139).

• left_join(), right_join(), full_join(), and inner_join() perform a
  cross join for by = character() (@mgirlich, #242).

• left_join(), right_join(), and inner_join() are always translated to
  the [.data.table equivalent. For simple merges the translation gets a bit
  longer but thanks to the simpler code base it helps to better handle
  names in by and duplicated variables names produced in the data.table join
  (@mgirlich, #222).

• mutate() and transmute() work when called without variables
  (@mgirlich, #248).

• mutate() gains new experimental arguments .before and .after that allow
  you to control where the new columns are placed (to match dplyr 1.0.0)
  (@eutwt #291).

• mutate() can modify grouping columns (instead of creating another
  column with the same name) (@mgirlich, #246).

• n_distinct() is translated to uniqueN().

• tally() and count() follow the dplyr convention of creating a unique
  name if the default output name (n) already exists (@eutwt, #295).

• pivot_wider() names the columns correctly when names_from is a
  numeric column (@mgirlich, #214).

• pull() supports the name argument (@mgirlich, #263).

• slice() no longer returns excess rows (#10).

• slice_*() functions after group_by() are faster (@mgirlich, #216).

• slice_max() works when ordering by a character column (@mgirlich, #218).

• summarise() supports the .groups argument (@mgirlich, #245).

• summarise(), tally(), and count() can change the value of a grouping
  variables (@eutwt, #295).

• transmute() doesn't produce duplicate columns when assigning to the same
  variable (@mgirlich, #249). It correctly flags grouping variables so they
  selected (@mgirlich, #246).

• ungroup() removes variables in ... from grouping (@mgirlich, #253).