TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-5] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-4] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[TimeXer-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-3] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-2] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-1] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

TestAllPtForecastersV2.test_integration[DLinear-0] AttributeError: DataModule of type TslibDataModule does not support scaler operations. Set save_scalers=False or use a DataModule that implements 'get_scalers_state()' method.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

`isinstance(treespec, LeafSpec)` is deprecated, use `isinstance(treespec, TreeSpec) and treespec.is_leaf()` instead.

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

The behavior of DataFrame.std with axis=None is deprecated, in a future version this will reduce over both axes and return a scalar. To retain the old behavior, pass axis=0 (or do not pass axis)

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning

In a future version, the keys of `groups` will be a tuple with a single element, e.g. (group_id,) , instead of a scalar, e.g. group_id, when grouping by a list with a single element. Use ``df.groupby(by='a').groups`` instead of ``df.groupby(by=['a']).groups`` to avoid this warning