tw.endpoints.forecast.rca
tw.endpoints.forecast.rca(configuration=dict,dataset=pandas.DataFrame,model=dict)
Submit a root-cause analysis job.
POST ``/forecast/rca``
Parameters
configuration : dict
RCA configuration payload.
dataset : pandas.DataFrame
Data associated with the period to analyse.
model: dict
A trained forecast model.
Returns
dict
API response containing at least ``"id"`` (the new job identifier).
Example Configuration
forecast_rca_configuration = {
"model_indexes": [
1
]
}
Example Usage
forecast_rca_response = tw.endpoints.forecast.rca(
configuration = forecast_rca_configuration,
dataset = dataset,
model = model
)
Example Output
forecast_rca_id = forecast_rca_response['id']