code: def _return_data_seasonal_types_strictly_pos():
      """Returns data with additive and multiplicative seasonal types
      (with strictly positive values only)"""
      # Create base data
      N = 100
      y_trend = np.arange(100, 100 + N)
      y_season = 100 * (
          1 + np.sin(y_trend)
      )  # No negative values when creating final y
  
      y_add = pd.Series(y_trend + y_season)
      y_mul = pd.Series(y_trend * y_season)
  
      datasets = [y_add, y_mul]
  
      return datasets
  
imports: import random
  import numpy
  import pandas
  from pandas.testing import assert_frame_equal
  from sktime.forecasting.base import ForecastingHorizon
  from pycaret.containers.models.time_series import get_all_model_containers
  from pycaret.datasets import get_data
  from pycaret.time_series import TSForecastingExperiment
  from pycaret.utils.time_series import SeasonalPeriod
label_desc: Use image node_id 19 for calling a global function with example usage: _return_data_seasonal_types_strictly_pos() and returns: datasets