tw.forecast.rca

tw.forecast.rca(configuration=dict,dataset=pandas.DataFrame,model=dict)

Run root-cause analysis (RCA) on forecast results. Submits an RCA job, polls until it completes, and returns the RCA table together with job metadata.

Parameters

configuration : dict

RCA configuration payload as expected by the API.

dataset : pandas.DataFrame

Time-series data associated with the period to analyse.

model: dict

A trained forecast model (as returned by method: “build_model”).

Returns

dict

A dictionary with keys:

"id" – job identifier (str).

"rca_table" – root-cause analysis table (dict).

"status"`` – final job status response (dict).

Example Configuration

CODE

forecast_rca_configuration = {
    "model_indexes": [
        1
    ]
}

Example Usage

CODE

forecast_rca_response = tw.forecast.rca(
    configuration = forecast_rca_configuration,
    dataset = dataset,
    model = model
)

Example Output

CODE

forecast_rca_id = forecast_rca_response['id']
forecast_rca_results = forecast_rca_response['rca_table']
forecast_rca_status = forecast_rca_response['status']