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This is a Transform type Snap that converts categorical fields into numeric fields. There are two available encoding options: Integer Encoding and One Hot Encoding.
Expected input
Expected output: A document containing numeric field.
Expected upstream Snaps
Expected downstream Snaps: A Snap that has a document input view. For example, Mapper, JSON Formatter, or Type Converter.
None.
Accounts are not used with this Snap.
Input | This Snap has exactly two document input views, the Data input view and the Profile input view. |
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Output | This Snap has exactly one document output view. |
Error | This Snap has at most one document error view. |
None
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Label | Required. The name for the Snap. Modify this to be more specific, especially if there are more than one of the same Snap in the pipeline. |
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Policy | The preferences for fields and encoding methods. For each policy, select the input field with categorical values, the encoding method, and the result field. |
Field | Required. The field that must be transformed. This is a suggestible property that lists all available fields in the input documents. Default value: None. |
Rule | Required. The type of transformation to be performed on the selected field. Two options are available:
Default value: Integer Encoding |
Result field | Required. The result field that is used in the output map. If the variable in the Result field property is the same as the one in the Field property, the values are overwritten. If the Result field does not exist in the original input document, a new field is added. Default value: None. |
We recommend you use the Sort Snap before the Categorical to Numeric Snap to prevent the pipeline from stalling when handling large datasets.
We recommend you use the Profile Snap in another (child/parent pipeline) pipeline and process the results to use with Categorical to Numeric Snap when handling large datasets.
This pipeline demonstrates how you can use the Categorical to Numeric Snap to assign team number for employees (numeric) based on their position (categorical).
Download this pipeline.
In this example, the CSV Generator Snap contains employee data with categorical fields. The Copy Snap duplicates the data flow and feeds it into the Categorical to Numeric and Profile Snaps. The Profile Snap computes data statistics and sends them to the Categorical to Numeric Snap. The Categorical to Numeric Snap then converts the position values (categorical) into team numbers (numeric), based on the selected encoding methods. The CSV Generator Snap contains employee data as shown below.
The Profile Snap computes the value distribution of the input data, which is required by Integer Encoding and One Hot Encoding. As you can see, the value distribution of $position contains "technical_writer" and "instructional_designer". Integer Encoding assigns values 1 and 2 to these, while One Hot Encoding creates a field for each of them.
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The following use case demonstrates a real-world scenario for using this Snap: