pdstools.valuefinder.Plots

Attributes

logger
COLORSCALE_TYPES
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Classes

Plots

Module Contents

logger

COLORSCALE_TYPES

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

Bases: pdstools.utils.namespaces.LazyNamespace

Parameters:

vf (pdstools.valuefinder.ValueFinder.ValueFinder)

dependencies = ['plotly']

vf

funnel_chart(by: str, query: pdstools.utils.types.QUERY | None = None, return_df: Literal[False] = False) → Figure

funnel_chart(by: str, query: pdstools.utils.types.QUERY | None = None, return_df: Literal[True] = True) → polars.LazyFrame

propensity_distribution(sample_size: int = 10000) → Figure

Parameters:

sample_size (int)

Return type:

Figure

propensity_threshold(sample_size: int = 10000, stage='Eligibility') → Figure

Parameters:

sample_size (int)

Return type:

Figure

_get_thresholds(thresholds: Iterable[float] | None = None, quantiles: Iterable[float] | None = None, default: Iterable[float] | None = None) → Iterable[float]

Parameters:

• thresholds (Optional[Iterable[float]])

• quantiles (Optional[Iterable[float]])

• default (Optional[Iterable[float]])

Return type:

Iterable[float]

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

Parameters:

• thresholds (Optional[Iterable[float]])

• quantiles (Optional[Iterable[float]])

• rounding (int)

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

Parameters:

• thresholds (Optional[Iterable[float]])

• quantiles (Optional[Iterable[float]])

• rounding (int)