fig_leg_forecasts¶

passengersim.contrast.fig_leg_forecasts(summaries: dict[str, SimulationTables], raw_df: bool = False, by_leg_id: int | None = None, by_class: bool | str = True, of: 'mu' | 'sigma' | list['mu' | 'sigma'] = 'mu', agg_booking_classes: bool = False, also_df: bool = False) → Chart | DataFrame | tuple[Chart, DataFrame][source]¶

Generate a figure contrasting leg demand forecasts for one or more runs.

Parameters:

summaries : dict[str, SimulationTables]¶

One or more SimulationTables to compare.

raw_df : bool, default False¶

If True, return the raw DataFrame instead of the chart.

by_leg_id : int, optional¶

If provided, show forecasts only for this specific leg ID. If None, the chart is faceted by flight number.

by_class : bool or str, default True¶

If True, differentiate booking classes by color. If a string, filter to only that booking class and color by source instead.

of : {'mu', 'sigma'} or list thereof, default 'mu'¶

Which forecast statistic to display: 'mu' for mean demand forecast, 'sigma' for standard deviation. Pass a list to display multiple statistics side-by-side.

agg_booking_classes : bool, default False¶

If True, aggregate (sum) across all booking classes before plotting, coloring by source rather than booking class.

also_df : bool, default False¶

If True, return a tuple of (figure, dataframe) instead of just the figure.

Returns:

alt.Chart or pd.DataFrame or tuple[alt.Chart, pd.DataFrame] – The Altair chart, or the raw DataFrame if raw_df is True, or a (chart, dataframe) tuple if also_df is True.