.. _auto_dataset_random_sampler:

*CREATES A RANDOM DATASET*
==========================

Draws a random sample of rows from a source dataset, returning a new dataset of the requested size. Use this worker to reduce large datasets for faster downstream processing or to create randomized subsets for training/testing splits.

When to use
-----------

Classification: **process**.

Tagged: ``dataset``, ``process``, ``random_sampling``, ``row_sample``, ``sampling``, ``transformations``.

Inputs
------

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   * - Label
     - ID
     - Type
     - Default
     - Required
     - Description
   * - Source
     - source_dataset
     - dataset
     - —
     - 
     - The input dataset (tabular) from which rows will be randomly drawn; leave unconnected only if the worker is being used in a context where data is injected programmatically.
   * - Number Of Samples
     - num_samples
     - scalar
     - -1
     - 
     - Integer count of rows to randomly draw from the source dataset; use -1 (default) to sample all rows, effectively shuffling the dataset.
   * - Reset Index
     - reset_index
     - string
     - no
     - 
     - Whether to reset the row index of the sampled output to a continuous 0-based range ('yes') or retain the original source indices ('no', default); set to 'yes' when the downstream worker expects a clean integer index.

Outputs
-------

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   :header-rows: 1
   :widths: 20 20 20 20

   * - Label
     - ID
     - Type
     - Description
   * - dataset_random_sampler_output_1
     - dataset_random_sampler_output_1
     - dataset
     - Randomly sampled subset of the source dataset as a tabular dataset, containing exactly num_samples rows (or all rows if num_samples is -1), with index reset or preserved according to the reset_index parameter.

Disciplines
-----------

- ai_ml.preprocessing
- data.dataset.transform

Runnable example
----------------

A runnable example is registered for this worker. Open the example workflow on the d3VIEW canvas: `/api/workflow/example?id=dataset_random_sampler <https://www.d3view.com/api/workflow/example?id=dataset_random_sampler>`_

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   Auto-generated from <code>transformation</code> schema. Worker id: <code>dataset_random_sampler</code>. Schema hash: <code>2f5424603bbd</code>. Hand-curated docs in <code>workerexamples/</code> override this page when present.
   </p>