pdstools.explanations.Plots
===========================

.. py:module:: pdstools.explanations.Plots


Classes
-------

.. autoapisummary::

   pdstools.explanations.Plots.Plots


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

.. py:class:: Plots(explanations: pdstools.explanations.Explanations.Explanations)

   Bases: :py:obj:`pdstools.utils.namespaces.LazyNamespace`


   Plots.


   .. py:attribute:: dependencies
      :type:  ClassVar[list[str]]
      :value: ['numpy', 'plotly']



   .. py:attribute:: dependency_group
      :value: 'explanations'



   .. py:attribute:: explanations


   .. py:attribute:: aggregates


   .. py:method:: contributions_overall(top_n: int = ..., top_k: int = ..., *, return_df: Literal[False] = ..., sort_by: pdstools.explanations._constants.ContributionType = ..., display_by: pdstools.explanations._constants.ContributionType = ..., descending: bool = ..., missing: bool = ..., remaining: bool = ..., include_numeric_single_bin: bool = ...) -> tuple[plotly.graph_objects.Figure, list[plotly.graph_objects.Figure]]
                  contributions_overall(top_n: int = ..., top_k: int = ..., *, return_df: Literal[True], sort_by: pdstools.explanations._constants.ContributionType = ..., display_by: pdstools.explanations._constants.ContributionType = ..., descending: bool = ..., missing: bool = ..., remaining: bool = ..., include_numeric_single_bin: bool = ...) -> tuple[polars.DataFrame, polars.DataFrame]

      Plot contributions for overall.



   .. py:method:: contributions_by_context(context: dict[str, str], top_n: int = ..., top_k: int = ..., *, return_df: Literal[False] = ..., sort_by: pdstools.explanations._constants.ContributionType = ..., display_by: pdstools.explanations._constants.ContributionType = ..., descending: bool = ..., missing: bool = ..., remaining: bool = ..., include_numeric_single_bin: bool = ...) -> tuple[plotly.graph_objects.Figure, plotly.graph_objects.Figure, list[plotly.graph_objects.Figure]]
                  contributions_by_context(context: dict[str, str], top_n: int = ..., top_k: int = ..., *, return_df: Literal[True], sort_by: pdstools.explanations._constants.ContributionType = ..., display_by: pdstools.explanations._constants.ContributionType = ..., descending: bool = ..., missing: bool = ..., remaining: bool = ..., include_numeric_single_bin: bool = ...) -> tuple[polars.DataFrame, polars.DataFrame]

      Plot contributions by context.