sharkpy.explaining
==================

.. py:module:: sharkpy.explaining


Attributes
----------

.. autoapisummary::

   sharkpy.explaining.explain_with_shapash


Functions
---------

.. autoapisummary::

   sharkpy.explaining._create_temp_plot
   sharkpy.explaining._add_table_to_doc
   sharkpy.explaining._add_metrics_table_to_doc
   sharkpy.explaining._export_deep_explanation_docx
   sharkpy.explaining._convert_docx_to_pdf
   sharkpy.explaining._get_data_insights
   sharkpy.explaining.explain_model
   sharkpy.explaining.demo_explanation


Module Contents
---------------

.. py:data:: explain_with_shapash
   :value: None


.. py:function:: _create_temp_plot(model, features, target, kind: str, width: int = 8, height: int = 6) -> str

   Create a temporary plot and return its path


.. py:function:: _add_table_to_doc(doc: docx.Document, df: pandas.DataFrame, title: str)

   Helper function to add a pandas DataFrame as a table to DOCX


.. py:function:: _add_metrics_table_to_doc(doc: docx.Document, cv_results, train_metrics)

   Add performance metrics table to DOCX document


.. py:function:: _export_deep_explanation_docx(docx_path, deep_explanation, model, features, target, feature_df, depth='deep')

   Export explanation to DOCX with specified depth level


.. py:function:: _convert_docx_to_pdf(docx_path, pdf_path)

   Convert DOCX to PDF using docx2pdf


.. py:function:: _get_data_insights(features, target, target_name, data, label_encoder, is_regression)

   Extract dynamic insights from the data


.. py:function:: explain_model(model, features, target, target_name, data=None, label_encoder=None, cv_results=None, train_metrics=None, export_path=None, format='txt', depth='deep')

   Generate model explanation with customizable depth and export options


.. py:function:: demo_explanation()

   Demo the explanation system