pdstools.impactanalyzer.Plots¶

Attributes¶

Classes¶

Module Contents¶

logger¶

class Plots(ia: pdstools.impactanalyzer.ImpactAnalyzer.ImpactAnalyzer)¶

Bases: pdstools.utils.namespaces.LazyNamespace

Parameters:: ia (pdstools.impactanalyzer.ImpactAnalyzer.ImpactAnalyzer)

ia¶

static _get_experiment_color_map()¶: Get consistent color mapping for default experiments.

static _get_facet_config(data, facet)¶

Determine optimal faceting configuration based on number of distinct facet values.

For <= 3 distinct values: use column faceting only For > 3 distinct values: use column wrapping for better layout

Parameters:

data (polars.DataFrame) – The plot data (already collected)
facet (str or None) – The facet column name

Returns:

Dictionary with ‘facet_col’ and ‘facet_col_wrap’ keys

Return type:

overview(*, by: List[str] | None = None, title: str | None = None, query: pdstools.utils.types.QUERY | None = None, metric: str | None = 'CTR_Lift', facet: str | None = None, return_df: bool | None = False)¶

Parameters:

by (Optional[List[str]])
title (Optional[str])
query (Optional[pdstools.utils.types.QUERY])
metric (Optional[str])
facet (Optional[str])
return_df (Optional[bool])

control_groups_trend(*, by: List[str] | None = None, title: str | None = None, query: pdstools.utils.types.QUERY | None = None, metric: str | None = 'CTR', facet: str | None = None, return_df: bool | None = False)¶

Parameters:

by (Optional[List[str]])
title (Optional[str])
query (Optional[pdstools.utils.types.QUERY])
metric (Optional[str])
facet (Optional[str])
return_df (Optional[bool])

trend(*, by: List[str] | None = None, title: str | None = None, query: pdstools.utils.types.QUERY | None = None, metric: str | None = 'CTR_Lift', facet: str | None = None, return_df: bool | None = False)¶

Parameters:

by (Optional[List[str]])
title (Optional[str])
query (Optional[pdstools.utils.types.QUERY])
metric (Optional[str])
facet (Optional[str])
return_df (Optional[bool])