Actxps

- `expose_split()` bug fixes:

- `ExposedDF.expose_split()` was updated to respect the values of `start_date`
and `end_date` originally passed to the `ExposedDF()` class.
- Future policy anniversary dates falling on February 29th leap days are now
consistent with `ExposedDF()`
- New tests were added to verify that the sum of policy year exposures
(`exposure_pol`) after calling `.expose_split()` match exposures produced by
`ExposedDF.expose_py()`.

- `ExposedDF()` bug fix - quarterly and monthly calendar exposures periods now
strictly calculate exposures based on month-end dates. In the prior version,
months ending on the 28-30 would use that same day of month for subsequent
exposure periods.

- `ExposedDF()` and `ExposedDF.add_transactions()` now allow date columns to be
passed as strings in YYYY-MM-DD format. Any strings are converted to date
behind-the-scenes, and any missing values will results in an error message.

- Small correction to the final policy year exposure for leap years

- To improve speed and efficiency, the data frame backend was changed from Pandas to Polars.
- The `data` property of `ExposedDF`, `ExpStats`, and `TrxStats` is now a Polars data frame.
- `ExposedDF`, `ExpStats.from_DataFrame`, and `TrxStats.from_DataFrame` will accept both Polars and Pandas data frames. However, Pandas data frames are immediately converted to Polars.
- Removed all add_* date functions which are no longer needed under Polars
- `ExposedDF`'s `groupby` method was renamed to `group_by`.

- Several updates to align with the R version of actxps

- Added optional confidence interval outputs to `ExpStats` and `TrxStats` objects
- Added an `expose_split()` method to `ExposedDF` classes, which divides calendar period exposures into pre- and post-policy anniversary segments. This creates a `SplitExposedDF` object, which is a subclass of `ExposedDF`.
- Added special plotting functions `ExpStats.plot_termination_rates()`, `ExpStats.plot_actual_to_expected()`, and `TrxStats.plot_utilization_rates()`
- Added `from_DataFrame` class methods to ExpStats and TrxStats objects that enables the creation of experience summary objects pre-aggregated data sets.
- Added the `great_tables` package as the backend for table() methods
- Shiny UI updates
- Added a 'points' geom, log 10 y-axis, and confidence interval options to plot methods
- Added sample data for pre-aggregated exposures (`load_agg_sim_dat()`)
- Bug fix - the target status wasn't being fully exposed when using calendar period exposures
- The assumed default status on `ExposedDF` objects is now the most common status instead of the first observed status.
- Added helper background functions for column selection
- Added several articles to the package's website

- Current differences from the R version are:

- No support for plotting a second variable on the y-axis for `.plot()` methods
- No predictive modeling support function (`add_predictions()`, `step_expose()`)
- Table output cannot be saved to a png directly in the shiny app
- functions like `pol_interval()` don't accept arbitrary durations. Only 'year', 'quarter', 'month', or 'week' are allowed.

- Development version of `actxps`