nest().Coercing a grouped tbl_time object to tibble with as_tibble() now drops groups and returns a bare tibble. The previous behavior of returning a grouped tibble was incorrect and let to faulty behavior in other functions.
Fixed an issue related to dplyr::ungroup() in dplyr 1.0.0 where ungrouping would not return an ungrouped tbl_time (#91).
Features
tidyr::nest() and tidyr::unnest() have been updated to be compliant with tidyr 1.0.0. An error will be triggered if you have a version of tidyr installed that is < 1.0.0 and try to use one of these functions on a tbl_time object.Bug fixes
collapse_by() no longer errors when there is a column named start_date in the tbl_time object (#81).Features
tbl_time object through new_tbl_time(). Only to be used by package developers extending tibbletime.Bug fixes
For tibble 2.0.1, an internal bug fix was made to pass along an nrow argument.
For dplyr 0.8.0, an internal fix was made in one of the tests.
A new line was added to inst/include/is_ordered.h to appease CRAN.
The tbl_time time zone for POSIXct indices is now set as the first non NA value of: “tzone” attribute -> Sys.timezone() -> “UTC”. Previously there was no Sys.timezone() step as there were problems with local time zones such as America/New_York interacting with collapsing by day. Those problems have been fixed by using DSTday with all POSIXct indices even if day is specified.
General
collapse_index() and collapse_by() support a clean argument. This will round your index up/down to the next period boundary, allowing for prettier dates that can be used in summaries.
A new helper function, collapse_by(), wraps the common idiom of .tbl_time %>% mutate(date = collapse_index(date, "yearly")) and is the easiest way to use tibbletime with the rest of the tidyverse.
You can now pass an index vector (easily created with create_series()) to the period argument of functions like as_period() or collapse_by() to specify custom periods to collapse at.
Added support for millisecond and microsecond grouping. See ?create_series for examples and ?filter_time Details for more information.
partition_index() (and therefore higher level functions like collapse_by()) now round using the entire period argument to figure out the default start date. Meaning if 2 years is passed, it will round down the start of the series to the lower 2 year boundary, rather than just year. This is a small change, but is technically breaking.
More efficient parsing of periods. Only noticably faster with a large number of groups.
Bug Fixes
tidyr::gather() and tidyr::spread() now work appropriately.This is a major update. It introduces a huge number of breaking changes as we heavily reworked the internals of the package. This should ensure the longevity of the package and provide maximum flexibility for its use with dplyr. As this was still early in package development with minimal usage, and because we had issued a Warning in the README of the last update that we may change things, we have not made any attempt to support backwards compatability. From this point forward, however, we will support backwards compatability as we feel that we have reached a more stable implementation.
With that out of the way, here is a complete list of changes.
General
The period argument no longer supports the ‘period formula’ (e.g. 1~year). It added unnecessary complication with little benefit. Rather, a character should be used like '1 year'. See the documentation of partition_index() for full details.
time_formula arguments still support the from ~ to style syntax, but the left and right hand sides must now be characters, rather than bare date specifications. In English, rather than 2013 ~ 2014, you must use '2013' ~ '2014'. This is easier to program with and also allows you to pass in variables to the time formula, which previously did not work well.
time_filter() has become filter_time(). This naming is easier to remember now that a suite of time_*() functions is not being developed and is easier to find with autocompletion.
time_group() and time_collapse() have become partition_index() and collapse_index(). Both functions accept index vectors and are commonly used inside dplyr::mutate().
partition_index() splits an index by period and returns an integer vector corresponding to the groups.
collapse_index() collapses an index by period so that all observations falling in that interval share the same date. This is most useful when used to then group on the index column.
There is full support for Date and POSIXct classes as the index, and there is experimental support for yearmon, yearqtr, and hms classes.
ceiling_index() and floor_index() are thin wrappers around lubridate functions of similar names, but they also work for yearmon, yearqtr and hms.
create_series() now has an explicit class argument.
as_period() gains an include_endpoints argument for including the last data point if side = "start" is specified or the first data point if side = "end" is used.
There are a number of new “getter” functions for accessing the index and time zone of tbl_time objects. These are useful for package development.
filter_time(), as_period() and other “getter” functions now use .tbl_time as a consistent first argument rather than x. collapse_index() and partition_index() use index as their first arguments.
Exported parse_period() for general use in other related packages.
Warnings are now generated if the user is not using a sorted index.
Bug Fixes
All dplyr functions should now retain the tbl_time class and relevant attributes.
Ensure that tidyr::spread() passes the fill argument through.
Default time zone is now UTC rather than Sys.timezone() to handle a daylight savings issue.
New functionality
time_floor() and time_ceiling() are convenient wrappers to lubridate functions for altering dates to period boundaries.
time_unnest() is used to specifically unnest a tibble object with a list-column of tbl_time objects.
create_series() allows the user to create a tbl_time object with a regularly spaced sequence of dates.
time_group() has become the workhorse function for creating time based groups used in changing periodicity and other grouped time based calculations.
time_summarise() and tmap() now also accept a formula-based period.
as_period() now accepts a formula-based period that provides an incredible amount of flexibility in creating groups. (#9, #14, #15)
rollify() creates a rolling version of any function for use in dplyr::mutate(). (#7)
General
You now have to explicitely load dplyr or tidyr to use any functions from those packages. Previously they were reexported, but this seems unnecessary.
Added vignettes on intro, filtering, and as_period().
Added more extensive dplyr support.
Speed increases for as_period() and create_series().
Internal global utilities moved to utils.R.
Added test coverage. (#2)
Added package documentation page. (#3)
Added versions to all imported packages.
Bug Fixes
Fixed an issue with [ in combination with tibble::add_column(). Use tibble (>= 1.3.4.9001) for correct behavior.
Fixed a bug where using tidyr::nest() would cause the nested tibbles to lose their time attributes.
Fix a bug where filter_time(data, ~yyyy-mm-dd) would be parsed as yyyy-mm-dd 00:00:00 ~ yyyy-mm-dd 00:00:00 instead of yyyy-mm-dd 00:00:00 ~ yyyy-mm-dd 23:59:59.
Fix a bug with as.Date / as.POSIXct operator collision in filter_time().
tibbletime, a package for time aware tibbles.