utilsforecast.data
generate_series
n_series
(int): Number of series for synthetic panel.freq
(str, optional): Frequency of the data (pandas alias). Seasonalities are implemented for hourly, daily and monthly. Defaults to ‘D’.min_length
(int, optional): Minimum length of synthetic panel’s series. Defaults to 50.max_length
(int, optional): Maximum length of synthetic panel’s series. Defaults to 500.n_static_features
(int, optional): Number of static exogenous variables for synthetic panel’s series. Defaults to 0.equal_ends
(bool, optional): Series should end in the same timestamp. Defaults to False.with_trend
(bool, optional): Series should have a (positive) trend. Defaults to False.static_as_categorical
(bool, optional): Static features should have a categorical data type. Defaults to True.n_models
(int, optional): Number of models predictions to simulate. Defaults to 0.level
(list of float, optional): Confidence level for intervals to simulate for each model. Defaults to None.engine
(str, optional): Output Dataframe type. Defaults to ‘pandas’.seed
(int, optional): Random seed used for generating the data. Defaults to 0.pandas or polars DataFrame
: Synthetic panel with columns [unique_id
, ds
, y
] and exogenous features.