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generate_series

generate_series(
    n_series,
    freq="D",
    min_length=50,
    max_length=500,
    n_static_features=0,
    equal_ends=False,
    with_trend=False,
    static_as_categorical=True,
    n_models=0,
    level=None,
    engine="pandas",
    seed=0,
)
Generate Synthetic Panel Series. Parameters:
NameTypeDescriptionDefault
n_seriesintNumber of series for synthetic panel.required
freqstrFrequency of the data (pandas alias). Seasonalities are implemented for hourly, daily and monthly. Defaults to ‘D’.‘D’
min_lengthintMinimum length of synthetic panel’s series. Defaults to 50.50
max_lengthintMaximum length of synthetic panel’s series. Defaults to 500.500
n_static_featuresintNumber of static exogenous variables for synthetic panel’s series. Defaults to 0.0
equal_endsboolSeries should end in the same timestamp. Defaults to False.False
with_trendboolSeries should have a (positive) trend. Defaults to False.False
static_as_categoricalboolStatic features should have a categorical data type. Defaults to True.True
n_modelsintNumber of models predictions to simulate. Defaults to 0.0
levellist of floatConfidence level for intervals to simulate for each model. Defaults to None.None
enginestrOutput Dataframe type. Defaults to ‘pandas’.‘pandas’
seedintRandom seed used for generating the data. Defaults to 0.0
Returns:
TypeDescription
DataFramepandas or polars DataFrame: Synthetic panel with columns [unique_id, ds, y] and exogenous features.