Should data_frame() forbid POSIXlt? #813
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What about coercing |
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What should we do for the linear model case? I'd rather be consistent, and I think |
hadley
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- 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.
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I don't think I like this decision. I agree that POSIXct is the target structure, but, when you get POSIXlt data from another package (e.g., weatherData::getSummarizedData), it's nice to be able to convert it with mutate (i.e., inside the dplyr environment), rather than having to flip back to older ways. It's just a simple dataframe %>% mutate(Date = as.POSIXct(Date)), and dataframe is just a data frame, not a tbl_df (or tibble, I guess now). |
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or in general, any list with a class? Unless it's been specifically designed to work as a list column, it will only have the right number of elements by chance:
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