forecast

forecast(config_path: pathlib.Path = <typer.models.ArgumentInfo object>, target_path: pathlib.Path = <typer.models.ArgumentInfo object>, freq: str = <typer.models.ArgumentInfo object>, output_path: pathlib.Path = <typer.models.ArgumentInfo object>, exog_path: typing.Optional[pathlib.Path] = <typer.models.ArgumentInfo object>, forecast_config_path: typing.Optional[pathlib.Path] = <typer.models.ArgumentInfo object>, raw_output: bool = <typer.models.ArgumentInfo object>, known_future: typing.Optional[typing.List[str]] = <typer.models.ArgumentInfo object>)

Command to make forecast with etna without coding.

Expected format of csv with target timeseries:

 ============= =========== ==========

timestamp segment target

2020-01-01	segment_1	1
2020-01-02	segment_1	2
2020-01-03	segment_1	3
2020-01-04	segment_1	4
…
2020-01-10	segment_2	10
2020-01-11	segment_2	20

Expected format of csv with exogenous timeseries:

 ============= =========== =============== ===============

timestamp segment regressor_1 regressor_2

2020-01-01	segment_1	11	12
2020-01-02	segment_1	22	13
2020-01-03	segment_1	31	14
2020-01-04	segment_1	42	15
…
2020-02-10	segment_2	101	61
2020-02-11	segment_2	205	54

Parameters

• config_path (pathlib.Path) –

• target_path (pathlib.Path) –

• freq (str) –

• output_path (pathlib.Path) –

• exog_path (Optional[pathlib.Path]) –

• forecast_config_path (Optional[pathlib.Path]) –

• raw_output (bool) –

• known_future (Optional[List[str]]) –