PPA book schema

Generated from the PPA book schema. ppa.SCHEMA.to_pandas() returns the core columns as a DataFrame.

`households`

Key: household_id. Required table. Each column is yours.

`submissions`

Key: submission_id. Required table.

Column	Type	Unit	Values	Required	Meaning
`household_id`	id			Yes	The household the submission prices.
`effective_date`	date			Yes	The date the rated term starts.
`transaction`	enum		`new_business`, `renewal`		Whether the term is new business or a renewal.
`term_months`	int	months			The length of the rated term.

`household_facts`

Key: submission_id. Optional table. Each column is yours.

`drivers`

Key: submission_id, driver_id. Required table.

Column	Type	Values	Meaning
`relationship`	enum	`applicant`, `spouse`, `child`, `other`	The driver’s relationship to the applicant.
`rated`	enum	`rated`, `excluded`, `listed`	Whether the policy rates the driver, excludes them, or only lists them.
`birth_date`	date		The driver’s date of birth.
`gender`	enum	`female`, `male`, `nonbinary`	The driver’s gender.
`marital_status`	enum	`single`, `married`, `divorced`, `widowed`, `separated`, `domestic_partner`	The driver’s marital status.
`first_licensed_date`	date		The date the driver was first licensed to drive.
`defensive_course_date`	date		The date the driver completed an approved driver improvement course.

`vehicles`

Key: submission_id, vehicle_id. Required table.

Column	Type	Unit	Values	Meaning
`model_year`	int			The vehicle’s model year.
`make`	text			The vehicle’s make, such as Honda.
`model`	text			The vehicle’s model, such as HR-V.
`garaging_postal_code`	text			The postal code where the vehicle is garaged.
`use`	enum		`pleasure`, `commute`, `business`, `farm`	How the vehicle is mainly used.
`annual_mileage`	int	miles		Distance the vehicle is driven in a year.

`incidents`

Key: submission_id, incident_id. Optional table.

Column	Type	Unit	Values	Meaning
`driver_id`	id			The driver the incident is charged to, if any.
`vehicle_id`	id			The vehicle the incident or claim is on, if any.
`kind`	enum		`violation`, `accident`, `claim`	What happened.
`occurrence_date`	date			The date the violation, accident or loss occurred.
`conviction_date`	date			The date of a violation’s conviction.
`description`	text			The incident as reported, such as a violation or a statute section.
`at_fault`	bool			Whether the driver was principally at fault (51% or more).
`injury`	bool			Whether the incident caused bodily injury or death.
`damage_amount`	number	USD		Property damage from the incident.
`dmv_points`	int			Points the motor vehicle record assigns the incident.
`disposition`	enum		`convicted`, `nolo_contendere`, `bail_forfeited`, `dismissed`	How a violation was resolved.

`policy_coverages`

Key: submission_id, coverage_id. Optional table.

Column	Type	Unit	Meaning
`limit_per_person`	number	USD	A split limit’s amount per person.
`limit_per_accident`	number	USD	A split limit’s amount per accident.
`limit`	number	USD	A single or combined limit.

`vehicle_coverages`

Key: submission_id, vehicle_id, coverage_id. Optional table.

Column	Type	Unit	Values	Required	Meaning
`deductible`	number	USD			The deductible.
`limit`	number	USD			The limit, for a coverage that has one.

Get started

Comparative pricing

Prepare and validate

Concepts

Rater development

Python reference

Data reference

`households`

`submissions`

`household_facts`

`drivers`

`vehicles`

`incidents`

`policy_coverages`

`vehicle_coverages`

​households

​submissions

​household_facts

​drivers

​vehicles

​incidents

​policy_coverages

​vehicle_coverages

`households`

`submissions`

`household_facts`

`drivers`

`vehicles`

`incidents`

`policy_coverages`

`vehicle_coverages`