The output, if transformation is successful, will always be an ordinal (ordered category) column, even if the input was an unordered category or not a Category at all. I.e. it is supposed that re-ordering the categories means the order is important. If the input column is already a category:
  • If unordered (non-ordinal): categories will be ordered in the given order (converted to ordinal)
  • If ordered (ordinal): categories will be re-ordered only
In both cases, the specified categories have to match the ones already existing. I.e. only re-ordering is allowed, but not deletion or addition of new categories. If the column is not already a category:
  • the column will be converted if the param force_categorical is true, and ordered as desired. Otherwise the new column will be identical to the input (no ordering performed).

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Usage

The following examples show how the step can be used in a recipe.

Examples

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Inputs & Outputs

The following are the inputs expected by the step and the outputs it produces. These are generally columns (ds.first_name), datasets (ds or ds[["first_name", "last_name"]]) or models (referenced by name e.g. "churn-clf").

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Configuration

The following parameters can be used to configure the behaviour of the step by including them in a json object as the last “input” to the step, i.e. step(..., {"param": "value", ...}) -> (output).

Parameters