GET SCHEMA FOR THE COLUMNS

Inspects a dataset and returns a schema table describing each column’s name, data type, and basic properties. Optionally restrict schema generation to a specific subset of columns. Use this worker whenever you need to programmatically discover or validate the structure of a dataset before downstream processing.

When to use

Classification: process.

Tagged: column_types, dataset_structure, introspection, metadata, schema.

Inputs

Label ID Type Default Required Description
Dataset dataset dataset   Input dataset whose column schema will be extracted; accepts any tabular dataset available on the platform — leave unconnected only if the schema is to be derived at runtime.
Choose Columns columns scalar   Optional comma-separated or multi-select list of column names to restrict schema output to; when left blank the schema is generated for all columns in the dataset.

Outputs

Label ID Type Description
dataset_get_schema_output_1 dataset_get_schema_output_1 dataset Tabular dataset where each row describes one column from the input dataset, including at minimum the column name and inferred data type (e.g., string, integer, float, boolean).

Disciplines

  • data.dataset.transform
  • data.statistics

Runnable example

A runnable example is registered for this worker. Open the example workflow on the d3VIEW canvas: /api/workflow/example?id=dataset_get_schema


Auto-generated from transformation schema. Worker id: dataset_get_schema. Schema hash: 9f405b5bc9a2. Hand-curated docs in workerexamples/ override this page when present.