Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Implement as_data_frame.table() #23

Merged
merged 5 commits into from
Mar 10, 2016
Merged

Conversation

krlmlr
Copy link
Member

@krlmlr krlmlr commented Jan 15, 2016

@hadley: Like that?

> table(1:2, 2:1) %>% as_data_frame
Source: local data frame [4 x 3]

   Var1  Var2  Freq
  (chr) (chr) (int)
1     1     1     0
2     2     1     1
3     1     2     1
4     2     2     0
> table(a=1:2, 2:1) %>% as_data_frame
Source: local data frame [4 x 3]

      a  Var2  Freq
  (chr) (chr) (int)
1     1     1     0
2     2     1     1
3     1     2     1
4     2     2     0
> table(Var2=1:2, 2:1) %>% as_data_frame
Source: local data frame [4 x 3]

   Var2 Var2.1  Freq
  (chr)  (chr) (int)
1     1      1     0
2     2      1     1
3     1      2     1
4     2      2     0

Fixes #22.

@codecov-io
Copy link

Current coverage is 93.39%

Merging #23 into master will decrease coverage by -0.23% as of e7fde80

@@            master     #23   diff @@
======================================
  Files           13      13       
  Stmts          408     409     +1
  Branches         0       0       
  Methods          0       0       
======================================
  Hit            382     382       
  Partial          0       0       
- Missed          26      27     +1

Review entire Coverage Diff as of e7fde80

Powered by Codecov. Updated on successful CI builds.

@hadley
Copy link
Member

hadley commented Jan 15, 2016

Yes, although I'd prefer to use n instead of Freq, but I don't feel that strongly about. I would prefer that the variable names are all one case.

@hadley hadley closed this Jan 15, 2016
@krlmlr krlmlr reopened this Mar 10, 2016
krlmlr added a commit that referenced this pull request Mar 10, 2016
- New `as_data_frame.table()` with argument `n` to control name of count column (#22, #23).
@krlmlr krlmlr merged commit 512effc into master Mar 10, 2016
@krlmlr krlmlr deleted the feature/22-as_data_frame.table branch March 10, 2016 18:28
krlmlr pushed a commit that referenced this pull request Mar 10, 2016
- Prepare CRAN release, check with win-builder and valgrind.
- New `as_data_frame.table()` with argument `n` to control name of count column (#22, #23).
krlmlr pushed a commit that referenced this pull request Mar 10, 2016
- Features
    - New `as_data_frame.table()` with argument `n` to control name of count column (#22, #23).
    - New function `repair_names()` fixes missing and duplicate names (#10, #15, @r2evans).
    - `frame_data()` now also creates a list column if one of the entries is a list (#32).
    - New `rownames_to_column()` and `column_to_rownames()` functions, replace `add_rownames()` (#11, @zhilongjia).
    - Use `tibble` prefix for options (#13, #36).

- Documentation
    - Add pre-tibble NEWS (#39, #40).
    - Include vignette (#38).
    - Expand README.
    - Fix typos in documentation.
    - Remove use of `src()` from examples.

- Prepare CRAN release
    - Use new-style `.travis.yml`
    - Use AppVeyor for testing.
    - Finer coverage analysis (#37).
    - Check with win-builder and valgrind.
    - Fix NOTE from `R CMD check`.
krlmlr pushed a commit that referenced this pull request Mar 22, 2016
- 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_df`s 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.
@github-actions github-actions bot locked as resolved and limited conversation to collaborators Dec 11, 2020
Sign up for free to subscribe to this conversation on GitHub. Already have an account? Sign in.
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

Provide as_data_frame method for tables
3 participants