Rating Step¶

You have a set of rating factors - area, age band, NCD level - and a table of relativities for each. The Rating Step looks up the right factor for each row and combines them into a single multiplier (or sum). This is how you build a traditional multiplicative or additive rating structure.

When to use

Building a traditional multiplicative or additive rating structure.
Recreating factor tables from another rating tool.
Looking up relativities based on one, two, or three dimensions.
Use Banding first if your tables expect banded inputs rather than raw values.

A Rating Step takes a single input and outputs it with one new column per rating table, plus any combined columns. The panel has three tabs: CONFIG, POLARS and COLUMNS.

The CONFIG tab¶

The INPUT chip at the top names the node's connection; its × removes the connection. When a table rates on a column of the input, a line says where the column's levels come from: Levels from all rows · and the row count once the node's input data is cached, Levels from a sample · and the number of preview rows until then, or "Cached data is out of date".

If a Banding node's output has no labelled rule, a warning names it: "Banding outputs … have no valid levels. Add a labelled Banding rule before using them as rating factors."

RATING SECTION switches the tab between Tables, the rating tables, and Combined, the columns that combine them (it reads Combined set once a combined output is named). The first time you open a node that already has combined outputs, the tab opens on Combined; after that it remembers your choice.

Tables¶

A banner counts the tables ("Rating Tables · 2 tables"). The list shows one row per table, named by its output column, with a dot (green when healthy, amber when not), the number of factors (2f) and the number of entries, and a bin to remove it (when there is more than one). Hover a row for its problems, such as "Output column is required", "Add at least one factor" or "Add at least one rating entry".

The search box finds a table by its output column or factors; All and Issues filter the list.
The + button beside the filter adds a table, with DEFAULT 1.0.

Click a table in the list to edit it below:

Field	What it does
FACTORS (N/3)	The columns the table looks up, up to three. + Add factor... adds one, and the × beside a factor removes it. The lists offer the columns with known levels, each with its number of levels: the band names of every Banding node's outputs, and the text columns of the input. A factor that is not among them shows as "(not a banding factor)". Adding or removing a factor rebuilds the entries for every combination of levels, keeping the values already entered.
OUTPUT COLUMN	The name of the column the looked-up value goes into. Errors and logs identify the table by it. It is required and must be unique: the box turns red with "Output column is required" or "Output column name must be unique".
DEFAULT	The value given to a row whose factor values have no entry in the table (e.g. an area code you haven't mapped). A new table starts with `1.0`. Clear it to make a miss stop the run instead (see What happens on a miss).
↻ Rebuild from factor levels	Rebuilds the entries from the factors' current levels - after a Banding node gains a band, for example - keeping the values already entered.

Under the fields, the table itself:

One factor: one row per level, with its RELATIVITY and a bar showing its size.
Two factors: a grid, with the first factor's levels as rows and the second's as columns. Copy visible table as TSV copies it; pasting tab-separated values into a cell fills the grid from that cell.
Three factors: a list for the third factor chooses which level's grid to show; the grid is the first factor by the second, as for two factors.

Type a relativity into a cell; it is saved when you leave the cell, and an empty or non-numeric cell takes the table's DEFAULT (1 when DEFAULT is empty). Drag across cells to select several, and Ctrl+C copies their values. A line under the table gives the number of entries and the range of values.

A factor with many levels can make a table too large to edit: past 20,000 cells the editor says how big it would be, for example "area (2000) × vehicle_model (400) would be 800,000 cells - too many to edit here. Band the column first, or rate it in a table of its own."

A band's DEFAULT (unmatched rows) on the Banding node is not a level of the table, so rows that fall to it are rated with the table's DEFAULT.

Combined¶

Each combined output is a tab, named by its column (with a dot, green when complete); the + button after the tabs adds one, named combined_1, combined_2 and so on, and the × on a tab removes it. With none, the section says "No combined output".

Field	What it does
COMBINED OUTPUT COLUMN	The name of the combined column. It is required and must differ from every table's output column and every other combined column.
OPERATION	How the tables' values are combined: × Multiply, + Add, Min or Max.
BASE VALUE	The value the combination starts from. Choosing an operation sets it to `1.0` (or `0.0` for + Add); change it if you need to.

A line under the fields shows the formula, such as location_age_factor = 1.0 × area_factor × age_factor. Every table takes part. With no combined output, the individual factor columns are still created but no combined column is produced.

The POLARS tab¶

See Polars.

The COLUMNS tab¶

The COLUMNS tab chooses which columns the node passes on (see Working with any node).

Example¶

An area factor and an age factor, multiplied together, where age_band comes from an upstream Banding node:

Connect your data to a Rating Step. In the first table, choose area under + Add factor..., type area_factor as the OUTPUT COLUMN and leave DEFAULT at 1.0.
Fill in the relativities: London 1.25, Manchester 1.10, Rural 0.85.
Click the + button beside the table list to add a second table. Choose age_band as its factor, type age_factor as the OUTPUT COLUMN, and fill in 18-25 → 1.40, 26-65 → 1.00, 65+ → 1.15.
Switch RATING SECTION to Combined, click the + button, and change the COMBINED OUTPUT COLUMN to location_age_factor. Leave OPERATION on × Multiply and BASE VALUE at 1.0.

Before and after:

BEFORE                                AFTER
| area       | age_band |            | area   | age_band | area_factor | age_factor | location_age_factor |
|------------|----------|            |--------|----------|-------------|------------|---------------------|
| London     | 18-25    |      →     | London | 18-25    | 1.25        | 1.40       | 1.75                |
| Rural      | 26-65    |            | Rural  | 26-65    | 0.85        | 1.00       | 0.85                |
| Manchester | 65+      |            | Man... | 65+      | 1.10        | 1.15       | 1.265               |

What happens on a miss¶

A row whose factor value has no entry in the table is an unpriceable row. A table with a numeric DEFAULT prices it at that value without an error. Tables start with DEFAULT 1.0, so a miss is priced at 1.0 unless you clear DEFAULT.

With DEFAULT cleared, the run fails with a RatingTableMissError naming the table's output column, the missing keys and the number of rows affected - a renamed band label cannot silently price at base rate.

How entries match

Each entry's factor values are first converted to the type of the input column, then matched. On a numeric column the value counts, not how it was typed: on a float column, entries 25, "25" and "25.0" are the same key and all match 25.0. An entry that cannot be converted to the column's type fails the run rather than silently never matching, for example "25.0" on an integer column or a malformed date on a date column.

On a text column, entries are matched exactly as written, and matching is case-sensitive: if your data has "London" but your table has "london", it won't match. Use a Polars node upstream to normalise casing if needed.

In the pipeline file

The node's settings are stored in a JSON sidecar, config/rating_step/<node name>.json, which the node's decorator in the pipeline's .py file names: @pipeline.rating_step(config="config/rating_step/<node name>.json"). Steps on the POLARS tab are stored in the sidecar as steps, and the code they generate is the body of the node's function, which takes the rated data as df; after Switch to code, the body is your code.

Setting in the editor	Stored as
The tables	`tables`: a list with one object per table
FACTORS	`tables[].factors`: the input columns to match on, at most 3
OUTPUT COLUMN	`tables[].outputColumn`
DEFAULT	`tables[].defaultValue`, as text such as `"1.0"` (empty when cleared)
The relativities	`tables[].entries`: one object per combination of levels, holding a value for each factor and the looked-up `value`
The combined outputs	`combinedOutputs`: a list with one object per combined output
COMBINED OUTPUT COLUMN	`combinedOutputs[].outputColumn`
OPERATION	`combinedOutputs[].operation`: `"multiply"`, `"add"`, `"min"` or `"max"`
BASE VALUE	`combinedOutputs[].baseValue`, a number
POLARS tab	`steps`, or the function body after Switch to code
COLUMNS tab	`selected_columns`

With no editor control:

tables[].onMissing: what to do when a lookup misses and no usable defaultValue is set. "error" (the default) fails the run as described above; "neutral" leaves the table output null - combined outputs treat it as the operation's neutral element (×1.0 / +0.0) - and logs a warning with the miss count. Set it by hand in the sidecar, and note that any edit to the node's tables in the editor removes it; misses are still counted and logged.
tables[].factorDtypes: the data types of the factor columns, which Haute records.

A table whose sidecar has no defaultValue shows DEFAULT 1.0 in the editor, and editing the node's tables saves it with 1.0.

A one-way area factor, as stored:

{
  "factors": ["area"],
  "outputColumn": "area_factor",
  "defaultValue": "1.0",
  "entries": [
    { "area": "London", "value": 1.25 },
    { "area": "Manchester", "value": 1.10 },
    { "area": "Rural", "value": 0.85 }
  ]
}

See also:

Banding - create the bands the tables look up
Polars (Getting Started) - how rating tables work under the hood