# tibble 1.4.2 (2018-01-22)

Bug fixes
---------

- Fix OS X builds.
- The `tibble.width` option is honored again (#369).
- `tbl[1, , drop = TRUE]` now behaves identically to data frames (#367).
- Fix error message when accessing columns using a logical index vector (#337, @mundl).
- `glimpse()` returns its input for zero-column data frames.

Features
--------

- `enframe(NULL)` now returns the same as `enframe(logical())` (#352).
- `tribble()` now ignores trailing commas (#342, @LaDilettante).
- Updated vignettes and website documentation.

Performance
-----------

- Faster printing of very wide tibbles (#360).
- Faster construction and subsetting for tibbles (#353).
- Only call `nrow()` and `head()` in `glimpse()`, not `ncol()`.


# tibble 1.4.1 (2017-12-24)

## New formatting

The new pillar package is now responsible for formatting tibbles. Pillar will try to display as many columns as possible, if necessary truncating or shortening the output. Colored output highlights important information and guides the eye. The vignette in the tibble package describes how to adapt custom data types for optimal display in a tibble.

## New features

- Make `add_case()` an alias for `add_row()` (#324, @LaDilettante).
- `as_tibble()` gains `rownames` argument (#288, #289).
- `as_tibble.matrix()` repairs column names.
- Tibbles now support character subsetting (#312).
- ``` `[.tbl_df`() ``` supports `drop = TRUE` and omits the warning if `j` is passed. The calls `df[i, j, drop = TRUE]` and `df[j, drop = TRUE]` are now compatible with data frames again (#307, #311).

## Bug fixes

- Improved compatibility with remote data sources for `glimpse()` (#328).
- Logical indexes are supported, a warning is raised if the length does not match the number of rows or 1 (#318).
- Fixed width for word wrapping of the extra information (#301).
- Prevent `add_column()` from dropping classes and attributes by removing the use of `cbind()`. Additionally this ensures that `add_column()` can be used with grouped data frames (#303, @DavisVaughan).
- `add_column()` to an empty zero-row tibble with a variable of nonzero length now produces a correct error message (#319).

## Internal changes

- Reexporting `has_name()` from rlang, instead of forwarding, to avoid warning when importing both rlang and tibble.
- Compatible with R 3.1 (#323).
- Remove Rcpp dependency (#313, @patperry).


# tibble 1.3.4 (2017-08-21)

## Bug fixes

- Values of length 1 in a `tibble()` call are recycled prior to evaluating subsequent arguments, improving consistency with `mutate()` (#213).
- Recycling of values of length 1 in a `tibble()` call maintains their class (#284).
- `add_row()` now always preserves the column data types of the input data frame the same way as `rbind()` does (#296).
- `lst()` now again handles duplicate names, the value defined last is used in case of a clash.
- Adding columns to zero-row data frames now also works when mixing lengths 1 and 0 in the new columns (#167).
- The `validate` argument is now also supported in `as_tibble.tbl_df()`, with default to `FALSE` (#278).  It must be passed as named argument, as in `as_tibble(validate = TRUE)`.

## Formatting

- `format_v()` now always surrounds lists with `[]` brackets, even if their length is one. This affects `glimpse()` output for list columns (#106).
- Factor levels are escaped when printing (#277).
- Non-syntactic names are now also escaped in `glimpse()` (#280).
- `tibble()` gives a consistent error message in the case of duplicate column names (#291).


# tibble 1.3.3 (2017-05-27)

## Bug fixes

- Added `format()` and `print()` methods for both `tbl` and `tbl_df` classes, to protect against malformed tibbles that inherit from `"tbl_df"` but not `"tbl"`, as created e.g. by `ungroup()` in dplyr 0.5.0 and earlier (#256, #263).
- The column width for non-syntactic columns is computed correctly again (#258).
- Printing a tibble doesn't apply quote escaping to list columns.
- Fix error in `tidy_names(syntactic = TRUE, quiet = FALSE)` if not all names are fixed (#260, @imanuelcostigan).
- Remove unused import declaration for assertthat.


# tibble 1.3.1 (2017-05-16)

## Bug fixes

- Subsetting zero columns no longer returns wrong number of rows (#241, @echasnovski).


## Interface changes

- New `set_tidy_names()` and `tidy_names()`, a simpler version of `repair_names()` which works unchanged for now (#217).
- New `rowid_to_column()` that adds a `rowid` column as first column and removes row names (#243, @barnettjacob).
- The `all.equal.tbl_df()` method has been removed, calling `all.equal()` now forwards to `base::all.equal.data.frame()`. To compare tibbles ignoring row and column order, please use `dplyr::all_equal()` (#247).


## Formatting

- Printing now uses `x` again instead of the Unicode multiplication sign, to avoid encoding issues (#216).
- String values are now quoted when printing if they contain non-printable characters or quotes (#253).
- The `print()`, `format()`, and `tbl_sum()` methods are now implemented for class `"tbl"` and not for `"tbl_df"`. This allows subclasses to use tibble's formatting facilities. The formatting of the header can be tweaked by implementing `tbl_sum()` for the subclass, which is expected to return a named character vector. The `print.tbl_df()` method is still implemented for compatibility with downstream packages, but only calls `NextMethod()`.
- Own printing routine, not relying on `print.data.frame()` anymore. Now providing `format.tbl_df()` and full support for Unicode characters in names and data, also for `glimpse()` (#235).


## Misc

- Improve formatting of error messages (#223).
- Using `rlang` instead of `lazyeval` (#225, @lionel-), and `rlang` functions (#244).
- `tribble()` now handles values that have a class (#237, @NikNakk).
- Minor efficiency gains by replacing `any(is.na())` with `anyNA()` (#229, @csgillespie).
- The `microbenchmark` package is now used conditionally (#245).
- `pkgdown` website.


# tibble 1.3.0 (2017-01-10)

## Bug fixes

- Time series matrices (objects of class `mts` and `ts`) are now supported in `as_tibble()` (#184).
- The `all_equal()` function (called by `all.equal.tbl_df()`) now forwards to `dplyr` and fails with a helpful message if not installed. Data frames with list columns cannot be compared anymore, and differences in the declared class (`data.frame` vs. `tbl_df`) are ignored. The `all.equal.tbl_df()` method gives a warning and forwards to `NextMethod()` if `dplyr` is not installed; call `all.equal(as.data.frame(...), ...)` to avoid the warning. This ensures consistent behavior of this function, regardless if `dplyr` is loaded or not (#198).

## Interface changes

- Now requiring R 3.1.0 instead of R 3.1.3 (#189).
- Add `as.tibble()` as an alias to `as_tibble()` (#160, @LaDilettante).
- New `frame_matrix()`, similar to `frame_data()` but for matrices (#140, #168, @LaDilettante).
- New `deframe()` as reverse operation to `enframe()` (#146, #214).
- Removed unused dependency on `assertthat`.

## Features

### General

- Keep column classes when adding row to empty tibble (#171, #177, @LaDilettante).
- Singular and plural variants for error messages that mention a list of objects (#116, #138, @LaDilettante).
- `add_column()` can add columns of length 1 (#162, #164, @LaDilettante).

### Input validation

- An attempt to read or update a missing column now throws a clearer warning (#199).
- An attempt to call `add_row()` for a grouped data frame results in a helpful error message (#179).

### Printing

- Render Unicode multiplication sign as `x` if it cannot be represented in the current locale (#192, @ncarchedi).
- Backtick `NA` names in printing (#206, #207, @jennybc).
- `glimpse()` now uses `type_sum()` also for S3 objects (#185, #186, @holstius).
- The `max.print` option is ignored when printing a tibble (#194, #195, @t-kalinowski).

## Documentation

- Fix typo in `obj_sum` documentation (#193, @etiennebr).
- Reword documentation for `tribble()` (#191, @kwstat).
- Now explicitly stating minimum Rcpp version 0.12.3.

## Internal

- Using registration of native routines.


# tibble 1.2 (2016-08-26)

## Bug fixes

- The `tibble.width` option is used for `glimpse()` only if it is finite (#153, @kwstat).
- New `as_tibble.poly()` to support conversion of a `poly` object to a tibble (#110).
- `add_row()` now correctly handles existing columns of type `list` that are not updated (#148).
- `all.equal()` doesn't throw an error anymore if one of the columns is named `na.last`, `decreasing` or `method` (#107, @BillDunlap).

## Interface changes

- New `add_column()`, analogously to `add_row()` (#99).
- `print.tbl_df()` gains `n_extra` method and will have the same interface as `trunc_mat()` from now on.
- `add_row()` and `add_column()` gain `.before` and `.after` arguments which indicate the row (by number) or column (by number or name) before or after which the new data are inserted. Updated or added columns cannot be named `.before` or `.after` (#99).
- Rename `frame_data()` to `tribble()`, stands for "transposed tibble". The former is still available as alias (#132, #143).

## Features

- `add_row()` now can add multiple rows, with recycling (#142, @jennybc).
- Use multiply character `×` instead of `x` when printing dimensions (#126). Output tests had to be disabled for this on Windows.
- Back-tick non-semantic column names on output (#131).
- Use `dttm` instead of `time` for `POSIXt` values (#133), which is now used for columns of the `difftime` class.
- Better output for 0-row results when total number of rows is unknown (e.g., for SQL data sources).

## Documentation

- New object summary vignette that shows which methods to define for custom vector classes to be used as tibble columns (#151).
- Added more examples for `print.tbl_df()`, now using data from `nycflights13` instead of `Lahman` (#121), with guidance to install `nycflights13` package if necessary (#152).
- Minor changes in vignette (#115, @helix123).


# tibble 1.1 (2016-07-01)

Follow-up release.

## Breaking changes

- `tibble()` is no longer an alias for `frame_data()` (#82).
- Remove `tbl_df()` (#57).
- `$` returns `NULL` if column not found, without partial matching. A warning is given (#109).
- `[[` returns `NULL` if column not found (#109).


## Output

- Reworked output: More concise summary (begins with hash `#` and contains more text (#95)), removed empty line, showing number of hidden rows and columns (#51). The trailing metadata also begins with hash `#` (#101). Presence of row names is indicated by a star in printed output (#72).
- Format `NA` values in character columns as `<NA>`, like `print.data.frame()` does (#69).
- The number of printed extra cols is now an option (#68, @lionel-).
- Computation of column width properly handles wide (e.g., Chinese) characters, tests still fail on Windows (#100).
- `glimpse()` shows nesting structure for lists and uses angle brackets for type (#98).
- Tibbles with `POSIXlt` columns can be printed now, the text `<POSIXlt>` is shown as placeholder to encourage usage of `POSIXct` (#86).
- `type_sum()` shows only topmost class for S3 objects.


## Error reporting

- Strict checking of integer and logical column indexes. For integers, passing a non-integer index or an out-of-bounds index raises an error. For logicals, only vectors of length 1 or `ncol` are supported. Passing a matrix or an array now raises an error in any case (#83).
- Warn if setting non-`NULL` row names (#75).
- Consistently surround variable names with single quotes in error messages.
- Use "Unknown column 'x'" as error message if column not found, like base R (#94).
- `stop()` and `warning()` are now always called with `call. = FALSE`.


## Coercion

- The `.Dim` attribute is silently stripped from columns that are 1d matrices (#84).
- Converting a tibble without row names to a regular data frame does not add explicit row names.
- `as_tibble.data.frame()` preserves attributes, and uses `as_tibble.list()` to calling overriden methods which may lead to endless recursion.


## New features

- New `has_name()` (#102).
- Prefer `tibble()` and `as_tibble()` over `data_frame()` and `as_data_frame()` in code and documentation (#82).
- New `is.tibble()` and `is_tibble()` (#79).
- New `enframe()` that converts vectors to two-column tibbles (#31, #74).
- `obj_sum()` and `type_sum()` show `"tibble"` instead of `"tbl_df"` for tibbles (#82).
- `as_tibble.data.frame()` gains `validate` argument (as in `as_tibble.list()`), if `TRUE` the input is validated.
- Implement `as_tibble.default()` (#71, hadley/dplyr#1752).
- `has_rownames()` supports arguments that are not data frames.


## Bug fixes

- Two-dimensional indexing with `[[` works (#58, #63).
- Subsetting with empty index (e.g., `x[]`) also removes row names.


## Documentation

- Document behavior of `as_tibble.tbl_df()` for subclasses (#60).
- Document and test that subsetting removes row names.


## Internal

- Don't rely on `knitr` internals for testing (#78).
- Fix compatibility with `knitr` 1.13 (#76).
- Enhance `knit_print()` tests.
- Provide default implementation for `tbl_sum.tbl_sql()` and `tbl_sum.tbl_grouped_df()` to allow `dplyr` release before a `tibble` release.
- Explicit tests for `format_v()` (#98).
- Test output for `NULL` value of `tbl_sum()`.
- Test subsetting in all variants (#62).
- Add missing test from dplyr.
- Use new `expect_output_file()` from `testthat`.


# Version 1.0 (2016-03-21)

- 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 (hadley/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
      (hadley/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 (hadley/dplyr#1570). It
      is now a generic, the default method dispatches to `str()`
      (hadley/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) (hadley/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 (hadley/dplyr#1377,
      @kevinushey).

- Minor modifications
    - Uses `setOldClass(c("tbl_df", "tbl", "data.frame"))` to help with S4
      (hadley/dplyr#969).
    - `tbl_df()` automatically generates column names (hadley/dplyr#1606).
    - `tbl_df`s gain `$` and `[[` methods that are ~5x faster than the defaults,
      never do partial matching (hadley/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)
      (hadley/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 (hadley/dplyr#820).  Both functions now check that
      you don't have any `POSIXlt` columns, and tell you to use `POSIXct` if you
      do (hadley/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()` (hadley/dplyr#1161).  The type of list
      columns is printed correctly (hadley/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 (hadley/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.
