Counts the number of unique elements in each list/array of the input column.
The following example shows how the step can be used in a recipe.
Examples
This step has no configuration parameters, so it’s simply:
This step has no configuration parameters, so it’s simply:
General syntax for using the step in a recipe. Shows the inputs and outputs the step is expected to receive and will produce respectively. For futher details see sections below.
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"
).
Inputs
A column containing lists.
Outputs
The count of unique elements for each input list.
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
This step doesn’t expect any configuration.
Counts the number of unique elements in each list/array of the input column.
The following example shows how the step can be used in a recipe.
Examples
This step has no configuration parameters, so it’s simply:
This step has no configuration parameters, so it’s simply:
General syntax for using the step in a recipe. Shows the inputs and outputs the step is expected to receive and will produce respectively. For futher details see sections below.
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"
).
Inputs
A column containing lists.
Outputs
The count of unique elements for each input list.
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
This step doesn’t expect any configuration.