class_docstr: Mock forecaster, returns data frames filled with a constant.
  
  Parameters
  ----------
  prediction_constant : float, optional
      The forecasted value for all steps in the horizon, by default 10
  
  Examples
  --------
  >>> from sktime.datasets import load_airline
  >>> from sktime.utils.estimators import MockUnivariateForecasterLogger
  >>> y = load_airline()
  >>> forecaster = MockUnivariateForecasterLogger()
  >>> forecaster.fit(y)
  MockUnivariateForecasterLogger(...)
  >>> y_pred = forecaster.predict(fh=[1,2,3])
  >>> print(forecaster.log)
  [('_fit', ...), ('_predict', ...)]
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code: def __init__(self, prediction_constant: float = 10):
      self.prediction_constant = prediction_constant
      super().__init__()
  
file_path: sktime/sktime/utils/estimators/_forecasters.py
imports: import pandas
  from sktime.forecasting.base import BaseForecaster
  from sktime.utils.estimators._base import _method_logger, _MockEstimatorMixin
label_desc: Use image node_id 1 to create a new MockForecaster object from inherited base classes: BaseForecaster with example: obj = MockForecaster(prediction_constant)