Changelog
v1.1.0
expose_split()
bug fixes:ExposedDF.expose_split()
was updated to respect the values ofstart_date
andend_date
originally passed to theExposedDF()
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 byExposedDF.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()
andExposedDF.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.
v1.0.2
- Small correction to the final policy year exposure for leap years
v1.0.0
- To improve speed and efficiency, the data frame backend was changed from Pandas to Polars.
- The
data
property ofExposedDF
,ExpStats
, andTrxStats
is now a Polars data frame. ExposedDF
,ExpStats.from_DataFrame
, andTrxStats.from_DataFrame
will accept both Polars and Pandas data frames. However, Pandas data frames are immediately converted to Polars.
- The
- Removed all add_* date functions which are no longer needed under Polars
ExposedDF
’sgroupby
method was renamed togroup_by
.
v0.0.1 (2024-02-18)
Several updates to align with the R version of actxps
- Added optional confidence interval outputs to
ExpStats
andTrxStats
objects - Added an
expose_split()
method toExposedDF
classes, which divides calendar period exposures into pre- and post-policy anniversary segments. This creates aSplitExposedDF
object, which is a subclass ofExposedDF
. - Added special plotting functions
ExpStats.plot_termination_rates()
,ExpStats.plot_actual_to_expected()
, andTrxStats.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
- Added optional confidence interval outputs to
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.
- No support for plotting a second variable on the y-axis for
v0.0.0.9000 (2023-12-14)
- Development version of
actxps