Result columns and statuses

`Program.rate` and `Market.rate`

One row per submission (a book) or context (a study), in input order. A market’s rows follow context order, then program order.

Column	Present when	Holds
`submission_id`	Always	The submission
`scenario_id`	You rate a study	The scenario; `baseline` is the book as reported
`draw_id`	You rate a study	The draw; 0 is the scenario as reported
`program`	You rate a market	The program’s name in the market
`status`	Always	One of the statuses below
`reason_code`	Always	The code of the first reason for a status other than `succeeded`
`reason`	Always	The message of that reason
`bundle_id`	Always	The rater’s immutable identity; pass it as `revision` to rate again
One per outcome	The rater has it	The rater’s outcome, named by its `RatingOutcomes`, as float64
One per `read` key	The program has `read`	The column that the program’s `read` returns, in place of the outcomes

A row that has a status other than succeeded has NaN in each outcome column. A market’s program has NaN in each outcome column that its rater leaves out.

`RatingResult.to_pandas`

One row per input to Rater.rate, in input order.

Column	Holds
The identity key	The input’s ID: the `Dataset` key, or `id` for a list position
`status`	One of the rater statuses below
`reason_code`	The code of the first reason for a status other than `succeeded`
`reason`	The message of that reason
One per outcome	The outcome’s dotted path after the root record’s name, as float64

RatingResult.rows holds the same rows with exact values: Decimal numbers, and {"$rational": "p/q"} for a value with an infinite decimal expansion.

`Program.explain`

An Explanation of one submission:

Field	Holds
`book`	The submission’s slice of the book, with the columns of the program’s schema
`json_in`	The exact input the rater received; `None` when `prepare` failed for the submission
`trace`	The rater’s trace, as `Rater.explain` returns it; `None` for an unrated submission
`json_out`	The rater’s outcomes; `None` for an unrated submission
`row`	The submission’s row of `Program.rate`

`Rater.explain` and `Explanation.trace`

One row per value, inputs first, then calculations in calculation order.

Column	Holds
`kind`	`input` or `calculation`
`name`	The value’s dotted path, such as `vehicles[0].premium`
`value`	The exact value; a rational value appears as a `Fraction`

Statuses

Status	Meaning	Set by
`succeeded`	The rater rated the input and returned its outcomes	The rater
`invalid_inputs`	The input breaks the rater’s declared input rules, such as a range	The rater
`refused`	The rater declines the risk, with the carrier’s own code	The rater
`rating_failed`	The rating engine stopped with a fault	The rater
`mapping_failed`	`prepare` raised for this submission, or left it out; `reason_code` is `PREPARE_FAILED` or `NOT_PREPARED`	A program
`read_failed`	The program’s `read` raised; `reason_code` is `READ_FAILED`	A program
`prediction_failed`	A loss model rejected the input it predicts for	A loss model

A status describes rating. A carrier’s underwriting appetite needs its own evidence, joined to the results in pandas.

Get started

Comparative pricing

Prepare and validate

Concepts

Rater development

Python reference

Data reference

Result columns and statuses

`Program.rate` and `Market.rate`

`RatingResult.to_pandas`

`Program.explain`

`Rater.explain` and `Explanation.trace`

Statuses

​Program.rate and Market.rate

​RatingResult.to_pandas

​Program.explain

​Rater.explain and Explanation.trace

​Statuses

`Program.rate` and `Market.rate`

`RatingResult.to_pandas`

`Program.explain`

`Rater.explain` and `Explanation.trace`

Statuses