tidyverse/dplyr v0.3

dplyr 0.3

on GitHub

New functions

• between() vector function efficiently determines if numeric values fall
  in a range, and is translated to special form for SQL (#503).
• count() makes it even easier to do (weighted) counts (#358).
• data_frame() by @kevinushey is a nicer way of creating data frames.
  It never coerces column types (no more stringsAsFactors = FALSE!),
  never munges column names, and never adds row names. You can use previously
  defined columns to compute new columns (#376).
• distinct() returns distinct (unique) rows of a tbl (#97). Supply
  additional variables to return the first row for each unique combination
  of variables.
• Set operations, intersect(), union() and setdiff() now have methods
  for data frames, data tables and SQL database tables (#93). They pass their
  arguments down to the base functions, which will ensure they raise errors if
  you pass in two many arguments.
• Joins (e.g. left_join(), inner_join(), semi_join(), anti_join())
  now allow you to join on different variables in x and y tables by
  supplying a named vector to by. For example, by = c("a" = "b") joins
  x.a to y.b.
• n_groups() function tells you how many groups in a tbl. It returns
  1 for ungrouped data. (#477)
• transmute() works like mutate() but drops all variables that you didn't
  explicitly refer to (#302).
• rename() makes it easy to rename variables - it works similarly to
  select() but it preserves columns that you didn't otherwise touch.
• slice() allows you to selecting rows by position (#226). It includes
  positive integers, drops negative integers and you can use expression like
  n().

Programming with dplyr (non-standard evaluation)

• You can now program with dplyr - every function that does non-standard
  evaluation (NSE) has a standard evaluation (SE) version ending in _.
  This is powered by the new lazyeval package which provides all the tools
  needed to implement NSE consistently and correctly.
• See vignette("nse") for full details.
• regroup() is deprecated. Please use the more flexible group_by_()
  instead.
• summarise_each_q() and mutate_each_q() are deprecated. Please use
  summarise_each_() and mutate_each_() instead.
• funs_q has been replaced with funs_.

Removed and deprecated features

• %.% has been deprecated: please use %>% instead. chain() is
  defunct. (#518)
• filter.numeric() removed. Need to figure out how to reimplement with
  new lazy eval system.
• The Progress refclass is no longer exported to avoid conflicts with shiny.
  Instead use progress_estimated() (#535).
• src_monetdb() is now implemented in MonetDB.R, not dplyr.
• show_sql() and explain_sql() and matching global options dplyr.show_sql
  and dplyr.explain_sql have been removed. Instead use show_query() and
  explain().

Minor improvements and bug fixes

• Main verbs now have individual documentation pages (#519).
• %>% is simply re-exported from magrittr, instead of creating a local copy
  (#496, thanks to @jimhester)
• Examples now use nycflights13 instead of hflights because it the variables
  have better names and there are a few interlinked tables (#562). Lahman and
  nycflights13 are (once again) suggested packages. This means many examples
  will not work unless you explicitly install them with
  install.packages(c("Lahman", "nycflights13")) (#508). dplyr now depends on
  Lahman 3.0.1. A number of examples have been updated to reflect modified
  field names (#586).
• do() now displays the progress bar only when used in interactive prompts
  and not when knitting (#428, @jimhester).
• glimpse() now prints a trailing new line (#590).
• group_by() has more consistent behaviour when grouping by constants:
  it creates a new column with that value (#410). It renames grouping
  variables (#410). The first argument is now .data so you can create
  new groups with name x (#534).
• Now instead of overriding lag(), dplyr overrides lag.default(),
  which should avoid clobbering lag methods added by other packages.
  (#277).
• mutate(data, a = NULL) removes the variable a from the returned
  dataset (#462).
• trunc_mat() and hence print.tbl_df() and friends gets a width argument
  to control the deafult output width. Set options(dplyr.width = Inf) to
  always show all columns (#589).
• select() gains one_of() selector: this allows you to select variables
  provided by a character vector (#396). It fails immediately if you give an
  empty pattern to starts_with(), ends_with(), contains() or matches()
  (#481, @leondutoit). Fixed buglet in select() so that you can now create
  variables called val (#564).
• Switched from RC to R6.
• tally() and top_n() work consistently: neither accidentally
  evaluates the the wt param. (#426, @mnel)
• rename handles grouped data (#640).

Minor improvements and bug fixes by backend

Databases

• The db backend system has been completely overhauled in order to make
  it possible to add backends in other packages, and to support a much
  wider range of databases. See vignette("new-sql-backend") for instruction
  on how to create your own (#568).
• src_mysql() gains a method for explain().
• When mutate() creates a new variable that uses a window function,
  automatically wrap the result in a subquery (#484).
• Correct SQL generation for first() and last() (#531).
• order_by() now works in conjunction with window functions in databases
  that support them.

Data frames/tbl_df

• All verbs now understand how to work with difftime() (#390) and
  AsIs (#453) objects. They all check that colnames are unique (#483), and
  are more robust when columns are not present (#348, #569, #600).
• Hybrid evaluation bugs fixed:
  • Call substitution stopped too early when a sub expression contained a
    $ (#502).
  • Handle :: and ::: (#412).
  • cumany() and cumall() properly handle NA (#408).
  • nth() now correctly preserve the class when using dates, times and
    factors (#509).
  • no longer substitutes within order_by() because order_by() needs to do
    its own NSE (#169).
• [.tbl_df always returns a tbl_df (i.e. drop = FALSE is the default)
  (#587, #610). [.grouped_df preserves important output attributes (#398).
• arrange() keeps the grouping structure of grouped data (#491, #605),
  and preserves input classes (#563).
• contains() accidentally matched regular expressions, now it passes
  fixed = TRUE to grep() (#608).
• filter() asserts all variables are white listed (#566).
• mutate() makes a rowwise_df when given a rowwise_df (#463).
• rbind_all() creates tbl_df objects instead of raw data.frames.
• If select() doesn't match any variables, it returns a 0-column data frame,
  instead of the original (#498). It no longer fails when if some columns
  are not named (#492)
• sample_n() and sample_frac() methods for data.frames exported.
  (#405, @alyst)
• A grouped data frame may have 0 groups (#486). Grouped df objects
  gain some basic validity checking, which should prevent some crashes
  related to corrupt grouped_df objects made by rbind() (#606).
• More coherence when joining columns of compatible but different types,
  e.g. when joining a character vector and a factor (#455),
  or a numeric and integer (#450)
• mutate() works for on zero-row grouped data frame, and
  with list columns (#555).
• �LazySubset was confused about input data size (#452).
• Internal n_distinct() is stricter about it's inputs: it requires one symbol
  which must be from the data frame (#567).
• rbind_*() handle data frames with 0 rows (#597). They fill character
  vector columns with NA instead of blanks (#595). They work with
  list columns (#463).
• Improved handling of encoding for column names (#636).
• Improved handling of hybrid evaluation re $ and @ (#645).

Data tables

• Fix major omission in tbl_dt() and grouped_dt() methods - I was
  accidentally doing a deep copy on every result :(
• summarise() and group_by() now retain over-allocation when working with
  data.tables (#475, @arunsrinivasan).
• joining two data.tables now correctly dispatches to data table methods,
  and result is a data table (#470)

Cubes

• summarise.tbl_cube() works with single grouping variable (#480).