Rate a study against a market

from decimal import Decimal

from relativities import Market, Program, Study, scenario

current = Program.load("effective://example-ca-ppa")
book = current.example_book
rates = current.rater.tables["BaseRate"]
collision = rates["coverage"] == "collision"
rates.loc[collision, "rate"] = rates.loc[collision, "rate"] * Decimal("1.05")
market = Market({"current": current, "proposed": current.with_rater(current.rater.with_tables({"BaseRate": rates}))})


@scenario("Collision deductible {deductible}")
def collision_deductible(book, deductible=1_000):
    """Raise each collision deductible below `deductible` to `deductible`."""

    def raised(coverages):
        lower = coverages["coverage_id"].eq("collision") & coverages["deductible"].lt(deductible)
        return coverages.assign(deductible=coverages["deductible"].mask(lower, deductible))

    return book.with_tables(coverages=raised)


study = Study(book, scenarios=[collision_deductible])
results = market.rate(study)
results[["submission_id", "scenario_id", "draw_id", "program", "status", "premium"]].head(4)
#   submission_id scenario_id  draw_id   program     status premium
# 0       S000001    baseline        0   current  succeeded    2636
# 1       S000001    baseline        0  proposed  succeeded    2694
# 2       S000002    baseline        0   current  succeeded    5339
# 3       S000002    baseline        0  proposed  succeeded    5461

premiums = results.pivot(index=["submission_id", "program"], columns="scenario_id", values="premium").astype(float)
saving = premiums["baseline"] - premiums["Collision deductible 1000"]
saving.groupby("program").agg(["count", "mean"]).round(2)
#           count    mean
# program
# current   96671  156.74
# proposed  96671  164.58

totals = premiums.dropna().groupby("program").sum()
(totals.loc["proposed"] / totals.loc["current"] - 1).round(4)
# scenario_id
# Collision deductible 1000    0.0165
# baseline                     0.0181

results.query("status != 'succeeded'").groupby(["reason_code", "scenario_id"]).size().unstack()
# scenario_id  Collision deductible 1000  baseline
# reason_code
# CSL                               2112      2112
# FR-FILING                         2516      2516
# INPUT-TYPE                         788       788
# RIDESHARE                         1242      1242

market.close()