input: Write a function to create a transformed timeseries within the TimeseriesForecaster class.
  assert isinstance(TimeseriesForecaster(data).create_transformed_timeseries(), pd.DataFrame)
  assert not TimeseriesForecaster(data).create_transformed_timeseries().empty
output: def create_transformed_timeseries(self):
      transformed_data = self.data.copy()
      # Perform transformation logic here
      transformed_data = transformed_data.apply(lambda x: (x - x.mean()) / x.std())
      return transformed_data