Visualization¶

`plot_multiple_timeseries(datasets, variable='ntl', indexers=None, start_date=None, end_date=None, titles=None, y_max=None, title=None, font_scale=1.0, moving_average=None)` ¶

Plots one or multiple aggregated time-series datasets as vertically stacked subplots.

All subplots will share the same y-axis boundaries for direct comparability.

Parameters:

Name	Type	Description	Default
`datasets`	`List[Dataset]`	A list of spatially aggregated xarray Datasets.	required
`variable`	`str`	The variable name to plot (e.g. "ntl").	`'ntl'`
`indexers`	`Optional[dict]`	Optional dictionary of dimension coordinates to select specific data (e.g. `{"geonameid": "Region_A"}` or `{"x": 10.5, "y": 20.1}`).	`None`
`start_date`	`Optional[str]`	Optional start date string (e.g., '2022-01-01') to slice the data.	`None`
`end_date`	`Optional[str]`	Optional end date string (e.g., '2022-12-31') to slice the data.	`None`
`titles`	`Optional[List[str]]`	Optional list of titles corresponding to each subplot. If not provided, will attempt to use the `.attrs['step']` from each dataset.	`None`
`y_max`	`Optional[float]`	Optional maximum limit for the y-axis.	`None`
`title`	`Optional[str]`	Optional string for the overall figure title.	`None`
`font_scale`	`float`	The scaling factor for the plot's font sizes.	`1.0`
`moving_average`	`Optional[int]`	Optional moving average window size (days).	`None`

Returns:

Type	Description
`Figure`	The generated matplotlib Figure.