pdstools.valuefinder.Plots

Attributes

logger

COLORSCALE_TYPES

T

P

Classes

Plots

Plots.

Module Contents

logger
COLORSCALE_TYPES
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class Plots(vf: pdstools.valuefinder.ValueFinder.ValueFinder)

Bases: pdstools.utils.namespaces.LazyNamespace

Plots.

Parameters:

vf (pdstools.valuefinder.ValueFinder.ValueFinder)

dependencies: ClassVar[list[str]] = ['plotly']
dependency_group = 'adm'
vf
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.

propensity_distribution(sample_size: int = 10000) → pdstools.utils.plot_utils.Figure

Propensity distribution.

Parameters:

sample_size (int)

Return type:

pdstools.utils.plot_utils.Figure

propensity_threshold(sample_size: int = 10000, stage='Eligibility') → pdstools.utils.plot_utils.Figure

Propensity threshold.

Parameters:

sample_size (int)

Return type:

pdstools.utils.plot_utils.Figure

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

Pie charts.

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

Distribution per threshold.

Parameters: