pdstools.decision_analyzer.plots

Classes

Plot

Functions

offer_quality_piecharts(df, propensityTH, ...[, return_df])
getTrendChart(df[, stage, return_df])
value_distribution(value_data, scope)

Module Contents

class Plot(decision_data)

_decision_data

threshold_deciles(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', return_df=False)

action_variation(stage='Final', return_df=False)

trend_chart(stage: str, scope: str, return_df=False) → Tuple[plotly.graph_objects.Figure, str | None]

Parameters:

• stage (str)

• scope (str)

Return type:

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

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

Parameters:

• scope (str)

• NBADStages_Mapping (dict)

• 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, NBADStages_Mapping, return_df=False)

Parameters:

df (polars.LazyFrame)

offer_quality_piecharts(df: polars.LazyFrame, propensityTH, NBADStages_FilterView, NBADStages_Mapping, return_df=False)

Parameters:

df (polars.LazyFrame)

getTrendChart(df: polars.LazyFrame, stage: str = 'Final', return_df=False)

Parameters:

• df (polars.LazyFrame)

• stage (str)

value_distribution(value_data: polars.LazyFrame, scope: str)

Parameters:

• value_data (polars.LazyFrame)

• scope (str)