.. _auto_dataset_remove_na:

*DATASET REMOVE NA*
===================

Scans a dataset and removes any rows or columns that contain null (NA) values. Optionally restrict the null-check to a specific subset of columns. Use this worker to clean incomplete data before downstream analysis or model training.

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

Classification: **process**.

Tagged: ``data_cleaning``, ``dataset``, ``dropna``, ``missing_values``, ``null``, ``process``, ``remove_na``.

Inputs
------

.. list-table::
   :header-rows: 1
   :widths: 20 20 20 20 20 20

   * - Label
     - ID
     - Type
     - Default
     - Required
     - Description
   * - Dataset
     - dataset
     - dataset
     - —
     - 
     - Input dataset to be scanned for null values; accepts any tabular dataset connected from an upstream worker.
   * - Columns To Check
     - columnstocheck
     - scalar
     - —
     - 
     - One or more column names to restrict the null-check to; if left empty, all columns are evaluated for null values.
   * - Remove Rows Or Columns
     - remove_rows_columns
     - scalar
     - row
     - 
     - Axis to drop when a null value is found — 'row' (default) removes the entire row containing the null, 'column' removes the entire column.

Outputs
-------

.. list-table::
   :header-rows: 1
   :widths: 20 20 20 20

   * - Label
     - ID
     - Type
     - Description
   * - dataset_remove_na_output_1
     - dataset_remove_na_output_1
     - dataset
     - Cleaned dataset with all rows or columns that contained null values removed, ready for downstream processing.

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

- 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_remove_na <https://www.d3view.com/api/workflow/example?id=dataset_remove_na>`_

.. raw:: html

   <hr style="margin-top:2em">
   <p style="font-size:11px;color:#888">
   Auto-generated from <code>transformation</code> schema. Worker id: <code>dataset_remove_na</code>. Schema hash: <code>fbf13f1075b1</code>. Hand-curated docs in <code>workerexamples/</code> override this page when present.
   </p>