etna.datasets.generate_ar_df#

generate_ar_df(periods: int, start_time: Timestamp | int | str | None = None, ar_coef: list | None = None, sigma: float = 1, n_segments: int = 1, freq: str | None = 'D', random_seed: int = 1) → DataFrame[source]#

Create DataFrame with AR process data.

Parameters:

  • periods (int) – number of timestamps

  • start_time (Timestamp | int | str | None) – start timestamp

  • ar_coef (list | None) – AR coefficients

  • sigma (float) – scale of AR noise

  • n_segments (int) – number of segments

  • freq (str | None) – pandas frequency string for pandas.date_range() that is used to generate timestamp

  • random_seed (int) – random seed

Raises:

ValueError: – Incorrect type of start_time is used according to freq

Return type:

DataFrame