pdstools.valuefinder.Plots
==========================

.. py:module:: pdstools.valuefinder.Plots


Attributes
----------

.. autoapisummary::

   pdstools.valuefinder.Plots.logger
   pdstools.valuefinder.Plots.COLORSCALE_TYPES
   pdstools.valuefinder.Plots.T
   pdstools.valuefinder.Plots.P


Classes
-------

.. autoapisummary::

   pdstools.valuefinder.Plots.Plots


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

.. py:data:: logger

.. py:data:: COLORSCALE_TYPES

.. py:data:: T

.. py:data:: P

.. py:class:: Plots(vf: pdstools.valuefinder.ValueFinder.ValueFinder)

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


   Plots.


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



   .. py:attribute:: dependency_group
      :value: 'adm'



   .. py:attribute:: vf


   .. py:method:: funnel_chart(by: str, query: pdstools.utils.types.QUERY | None = None, return_df: Literal[False] = False) -> pdstools.utils.plot_utils.Figure
                  funnel_chart(by: str, query: pdstools.utils.types.QUERY | None = None, return_df: Literal[True] = True) -> polars.LazyFrame

      Funnel chart.



   .. py:method:: propensity_distribution(sample_size: int = 10000) -> pdstools.utils.plot_utils.Figure

      Propensity distribution.



   .. py:method:: propensity_threshold(sample_size: int = 10000, stage='Eligibility') -> pdstools.utils.plot_utils.Figure

      Propensity threshold.



   .. py:method:: pie_charts(*, thresholds: collections.abc.Iterable[float] | None = None, quantiles: collections.abc.Iterable[float] | None = None, rounding: int = 3)

      Pie charts.



   .. py:method:: distribution_per_threshold(*, thresholds: collections.abc.Iterable[float] | None = None, quantiles: collections.abc.Iterable[float] | None = None, rounding: int = 3)

      Distribution per threshold.