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Usage

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

Examples

  • Example 1
  • Example 2
  • Signature
To create a new dataset keeping only those rows where values in the “salary” column are either “low” or “high”.
filter_values(ds, {"column": "salary", "values": ["low", "high"]}) -> (ds_filtered)

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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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ds_in
dataset
required
An input dataset to filter.
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ds_out
dataset
required
A new dataset containing the same columns as the input dataset but only those rows passing the filter condition.

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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

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column
string (ds_in.column)
required
Name of column to be matched against the specified values.
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values
[number, string, array[['number', 'string']]]
required
Only rows matching these values exactly will be included in the resulting dataset. May be a single value or a list of values to be matched.
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Item
[number, string]
Each item in array.
  • the
  • [‘the’, ‘cat’]
  • 2
  • [2, 3]
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exclude
boolean
default:"false"
if true, only rows not matching the specified values will be included in the resulting dataset.
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