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, *, max_points_per_group: int | None = DEFAULT_PLOT_POINTS_PER_GROUP) -> pdstools.utils.plot_utils.Figure

      Plot the propensity distribution for each stage.

      :param sample_size: Number of rows per stage used to estimate the density.
      :type sample_size: int, default 10000
      :param max_points_per_group: Maximum number of box-plot values per stage. ``None`` plots all
                                   sampled values.
      :type max_points_per_group: int or None, default 250

      :returns: Propensity density and box plots.
      :rtype: Figure



   .. py:method:: propensity_threshold(sample_size: int = 10000, stage: str = 'Eligibility', *, max_points_per_group: int | None = DEFAULT_PLOT_POINTS_PER_GROUP) -> pdstools.utils.plot_utils.Figure

      Plot propensity distributions against the configured threshold.

      :param sample_size: Number of rows used to estimate the density.
      :type sample_size: int, default 10000
      :param stage: Stage whose propensity values are plotted.
      :type stage: str, default "Eligibility"
      :param max_points_per_group: Maximum number of histogram values per propensity type. ``None``
                                   plots all sampled values.
      :type max_points_per_group: int or None, default 250

      :returns: Propensity density and histogram plots.
      :rtype: Figure



   .. 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.