pdstools.decision_analyzer.plots

Classes

Plot

Functions

offer_quality_piecharts(df, propensityTH, ...[, ...])

getTrendChart(df[, stage, return_df, level])

plot_priority_component_distribution(value_data, ...)

Module Contents

class Plot(decision_data)
_decision_data
threshold_deciles(thresholding_on, thresholding_name, return_df=False)
distribution_as_treemap(df: polars.LazyFrame, stage: str, scope_options: List[str])
Parameters:

  • df (polars.LazyFrame)

  • stage (str)

  • scope_options (List[str])

sensitivity(win_rank: int = 1, hide_priority=True, limit_xaxis_range=True, return_df=False, reference_group=None)
Parameters:

win_rank (int)

global_winloss_distribution(level, win_rank, return_df=False)
propensity_vs_optionality(stage='Arbitration', df=None, return_df=False)
optionality_funnel(df)
action_variation(stage='Final', return_df=False)
trend_chart(stage: str, scope: str, return_df=False) → Tuple[plotly.graph_objects.Figure, str | None]
Parameters:
Return type:

Tuple[plotly.graph_objects.Figure, Optional[str]]

decision_funnel(scope: str, additional_filters: polars.Expr | List[polars.Expr] | None = None, return_df=False)
Parameters:

  • scope (str)

  • additional_filters (Optional[Union[polars.Expr, List[polars.Expr]]])

filtering_components(stages: List[str], top_n, AvailableNBADStages, additional_filters: polars.Expr | List[polars.Expr] | None = None, return_df=False)
Parameters:

  • stages (List[str])

  • additional_filters (Optional[Union[polars.Expr, List[polars.Expr]]])

distribution(df: polars.LazyFrame, scope: str, breakdown: str, metric: str = 'Decisions', horizontal=False)
Parameters:

  • df (polars.LazyFrame)

  • scope (str)

  • breakdown (str)

  • metric (str)

prio_factor_boxplots(reference: polars.Expr | List[polars.Expr] | None = None, sample_size=10000, return_df=False) → Tuple[plotly.graph_objects.Figure, str | None]
Parameters:

reference (Optional[Union[polars.Expr, List[polars.Expr]]])

Return type:

Tuple[plotly.graph_objects.Figure, Optional[str]]

rank_boxplot(reference: polars.Expr | List[polars.Expr] | None = None, return_df=False)
Parameters:

reference (Optional[Union[polars.Expr, List[polars.Expr]]])

optionality_per_stage(return_df=False)
optionality_trend(df: polars.LazyFrame, return_df=False)
Parameters:

df (polars.LazyFrame)

offer_quality_piecharts(df: polars.LazyFrame, propensityTH, AvailableNBADStages, return_df=False, level='StageGroup')
Parameters:

df (polars.LazyFrame)

getTrendChart(df: polars.LazyFrame, stage: str = 'Output', return_df=False, level='StageGroup')
Parameters:

  • df (polars.LazyFrame)

  • stage (str)

plot_priority_component_distribution(value_data: polars.LazyFrame, component: str, granularity: str)
Parameters:

  • value_data (polars.LazyFrame)

  • component (str)

  • granularity (str)