This has two consequences:
  1. It will allow the resulting column to be used by steps only accepting the new type, e.g. when casting a column of concatenated texts to the "url" type, so that it may be used where Urls are expected (e.g. the step fetch_url_content).
  2. It will change any values not conformant with the new type to the missing value (NaN). E.g., casting a column of mixed data containing numbers to the "number" type, will replace all values that cannot be read as numbers with NaN.
Note that for each possible type a column can be cast to (via the "type" parameter, e.g. "number", "category" etc.), the steps accepts different configuration parameters. See the subsections under Parameters below for further details.

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Usage

The following example shows 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