v1.0

• Initial CRAN release
• Extracted from dplyr 0.4.3
• Exported functions:
  • tbl_df()
  • as_data_frame()
  • data_frame(), data_frame_()
  • frame_data(), tibble()
  • glimpse()
  • trunc_mat(), knit_print.trunc_mat()
  • type_sum()
  • New lst() and lst_() create lists in the same way that
    data_frame() and data_frame_() create data frames (tidyverse/dplyr#1290).
    lst(NULL) doesn't raise an error (#17, @jennybc), but always
    uses deparsed expression as name (even for NULL).
  • New add_row() makes it easy to add a new row to data frame
    (tidyverse/dplyr#1021).
  • New rownames_to_column() and column_to_rownames() (#11, @zhilongjia).
  • New has_rownames() and remove_rownames() (#44).
  • New repair_names() fixes missing and duplicate names (#10, #15,
    @r2evans).
  • New is_vector_s3().
• Features
  • New as_data_frame.table() with argument n to control name of count
    column (#22, #23).
  • Use tibble prefix for options (#13, #36).
  • glimpse() now (invisibly) returns its argument (tidyverse/dplyr#1570). It
    is now a generic, the default method dispatches to str()
    (tidyverse/dplyr#1325). The default width is obtained from the
    tibble.width option (#35, #56).
  • as_data_frame() is now an S3 generic with methods for lists (the old
    as_data_frame()), data frames (trivial), matrices (with efficient
    C++ implementation) (tidyverse/dplyr#876), and NULL (returns a 0-row
    0-column data frame) (#17, @jennybc).
  • Non-scalar input to frame_data() and tibble() (including lists)
    creates list-valued columns (#7). These functions return 0-row but n-col
    data frame if no data.
• Bug fixes
  • frame_data() properly constructs rectangular tables (tidyverse/dplyr#1377,
    @kevinushey).
• Minor modifications
  • Uses setOldClass(c("tbl_df", "tbl", "data.frame")) to help with S4
    (tidyverse/dplyr#969).
  • tbl_df() automatically generates column names (tidyverse/dplyr#1606).
  • tbl_dfs gain $ and [[ methods that are ~5x faster than the defaults,
    never do partial matching (tidyverse/dplyr#1504), and throw an error if the
    variable does not exist. [[.tbl_df() falls back to regular subsetting
    when used with anything other than a single string (#29).
    base::getElement() now works with tibbles (#9).
  • all_equal() allows to compare data frames ignoring row and column order,
    and optionally ignoring minor differences in type (e.g. int vs. double)
    (tidyverse/dplyr#821). Used by all.equal() for tibbles. (This package
    contains a pure R implementation of all_equal(), the dplyr code has
    identical behavior but is written in C++ and thus faster.)
  • The internals of data_frame() and as_data_frame() have been aligned,
    so as_data_frame() will now automatically recycle length-1 vectors.
    Both functions give more informative error messages if you are attempting
    to create an invalid data frame. You can no longer create a data frame
    with duplicated names (tidyverse/dplyr#820). Both functions now check that
    you don't have any POSIXlt columns, and tell you to use POSIXct if you
    do (tidyverse/dplyr#813). data_frame(NULL) raises error "must be a 1d
    atomic vector or list".
  • trunc_mat() and print.tbl_df() are considerably faster if you have
    very wide data frames. They will now also only list the first 100
    additional variables not already on screen - control this with the new
    n_extra parameter to print() (tidyverse/dplyr#1161). The type of list
    columns is printed correctly (tidyverse/dplyr#1379). The width argument is
    used also for 0-row or 0-column data frames (#18).
  • When used in list-columns, S4 objects only print the class name rather
    than the full class hierarchy (#33).
  • Add test that [.tbl_df() does not change class (#41, @jennybc). Improve
    [.tbl_df() error message.
• Documentation
  • Update README, with edits (#52, @bhive01) and enhancements (#54,
    @jennybc).
  • vignette("tibble") describes the difference between tbl_dfs and
    regular data frames (tidyverse/dplyr#1468).
• Code quality
  • Test using new-style Travis-CI and AppVeyor. Full test coverage (#24,
    #53). Regression tests load known output from file (#49).
  • Renamed obj_type() to obj_sum(), improvements, better integration with
    type_sum().
  • Internal cleanup.