diff --git a/pycaret/internal/PycaretExperiment.py b/pycaret/internal/PycaretExperiment.py
index 9df8d46b4..fdf5c9a20 100644
--- a/pycaret/internal/PycaretExperiment.py
+++ b/pycaret/internal/PycaretExperiment.py
@@ -21,7 +21,7 @@
     get_columns_to_stratify_by,
     get_model_name,
 )
-from pycaret.internal.utils import SeasonalParameter
+from pycaret.internal.utils import SeasonalParameter, id_or_display_name
 import pycaret.internal.patches.sklearn
 import pycaret.internal.patches.yellowbrick
 from pycaret.internal.logging import get_logger, create_logger
@@ -5136,8 +5136,11 @@ def compare_models(
             display.display_monitor()
             display.display_master_display()
 
+        input_ml_usecase = self._ml_usecase
+        target_ml_usecase = MLUsecase.TIME_SERIES
+
         greater_is_worse_columns = {
-            v.display_name
+            id_or_display_name(v, input_ml_usecase, target_ml_usecase)
             for k, v in self._all_metrics.items()
             if not v.greater_is_better
         }
@@ -5151,7 +5154,7 @@ def compare_models(
 
         if not (isinstance(sort, str) and (sort == "TT" or sort == "TT (Sec)")):
             sort_ascending = not sort.greater_is_better
-            sort = sort.display_name
+            sort = id_or_display_name(sort, input_ml_usecase, target_ml_usecase)
         else:
             sort_ascending = True
             sort = "TT (Sec)"
@@ -5171,13 +5174,19 @@ def compare_models(
             model_library = include
         else:
             if turbo:
-                model_library = self._all_models
                 model_library = [k for k, v in self._all_models.items() if v.is_turbo]
             else:
                 model_library = list(self._all_models.keys())
             if exclude:
                 model_library = [x for x in model_library if x not in exclude]
 
+        if self._ml_usecase == MLUsecase.TIME_SERIES:
+            if 'ensemble_forecaster' in model_library:
+                warnings.warn(
+                    'Unsupported estimator `ensemble_forecaster` for method `compare_models()`, removing from model_library'
+                    )
+            model_library.remove('ensemble_forecaster')
+
         display.move_progress()
 
         # create URI (before loop)
@@ -16213,7 +16222,7 @@ def compare_models(
         fold: Optional[Union[int, Any]] = None,
         round: int = 4,
         cross_validation: bool = True,
-        sort: str = "R2",
+        sort: str = "smape",
         n_select: int = 1,
         budget_time: Optional[float] = None,
         turbo: bool = True,
@@ -16234,10 +16243,12 @@ def compare_models(
         Example
         --------
         >>> from pycaret.datasets import get_data
-        >>> boston = get_data('boston')
-        >>> from pycaret.regression import *
-        >>> exp_name = setup(data = boston,  target = 'medv')
-        >>> best_model = compare_models()
+        >>> from pycaret.internal.PycaretExperiment import TimeSeriesExperiment
+        >>> airline = get_data('airline', verbose=False)
+        >>> fh, fold = np.arange(1,13), 3
+        >>> exp = TimeSeriesExperiment()
+        >>> exp.setup(data=airline, fh=fh, fold=fold)
+        >>> master_display_exp = exp.compare_models(fold=fold, sort='mape')
 
 
         include: list of str or scikit-learn compatible object, default = None
@@ -16268,7 +16279,7 @@ def compare_models(
             is ignored when cross_validation is set to False.
 
 
-        sort: str, default = 'R2'
+        sort: str, default = 'smape'
             The sort order of the score grid. It also accepts custom metrics that are
             added through the ``add_metric`` function.
 
@@ -16436,6 +16447,43 @@ def create_model(
             **kwargs,
         )
 
+
+    def _create_model_without_cv(
+        self, model, data_X, data_y, fit_kwargs, predict, system, display
+    ):
+        with estimator_pipeline(self._internal_pipeline, model) as pipeline_with_model:
+
+            self.logger.info("Support for Exogenous variables not yet supported. Switching X, y order")
+            data_X, data_y = data_y, data_X
+
+            fit_kwargs = get_pipeline_fit_kwargs(pipeline_with_model, fit_kwargs)
+            self.logger.info("Cross validation set to False")
+
+            self.logger.info("Fitting Model")
+            model_fit_start = time.time()
+            with io.capture_output():
+                pipeline_with_model.fit(data_X, data_y, **fit_kwargs)
+            model_fit_end = time.time()
+
+            model_fit_time = np.array(model_fit_end - model_fit_start).round(2)
+
+            display.move_progress()
+
+            if predict:
+                self.predict_model(pipeline_with_model, verbose=False)
+                model_results = self.pull(pop=True).drop("Model", axis=1)
+
+                self.display_container.append(model_results)
+
+                display.display(
+                    model_results, clear=system, override=False if not system else None,
+                )
+
+                self.logger.info(f"display_container: {len(self.display_container)}")
+
+        return model, model_fit_time
+
+
     def _create_model_with_cv(
         self,
         model,
diff --git a/pycaret/internal/utils.py b/pycaret/internal/utils.py
index 6d28d5e73..2ea78bb20 100644
--- a/pycaret/internal/utils.py
+++ b/pycaret/internal/utils.py
@@ -30,7 +30,21 @@ class SeasonalParameter(IntEnum):
     A = 1 #year
     Y = 1 #year
 
-    
+
+def id_or_display_name(metric, input_ml_usecase, target_ml_usecase):
+    """
+    Get id or display_name attribute from metric. In time series experiment
+    the pull() method retrieves the metrics idto name the columns of the results
+    """
+
+    if input_ml_usecase == target_ml_usecase:
+        output = metric.id
+    else:
+        output = metric.display_name
+
+    return output
+
+
 def get_config(variable: str, globals_d: dict):
 
     """
diff --git a/pycaret/time_series.py b/pycaret/time_series.py
index 0d02eb8de..e3913713d 100644
--- a/pycaret/time_series.py
+++ b/pycaret/time_series.py
@@ -257,7 +257,7 @@ def compare_models(
     fold: Optional[Union[int, Any]] = None,
     round: int = 4,
     cross_validation: bool = True,
-    sort: str = "R2",
+    sort: str = "smape",
     n_select: int = 1,
     budget_time: Optional[float] = None,
     turbo: bool = True,
@@ -278,10 +278,12 @@ def compare_models(
     Example
     --------
     >>> from pycaret.datasets import get_data
-    >>> boston = get_data('boston')
-    >>> from pycaret.regression import *
-    >>> exp_name = setup(data = boston,  target = 'medv')
-    >>> best_model = compare_models()
+    >>> from pycaret.internal.PycaretExperiment import TimeSeriesExperiment
+    >>> airline = get_data('airline', verbose=False)
+    >>> fh, fold = np.arange(1,13), 3
+    >>> exp = TimeSeriesExperiment()
+    >>> exp.setup(data=airline, fh=fh, fold=fold)
+    >>> master_display_exp = exp.compare_models(fold=fold, sort='mape')
 
 
     include: list of str or scikit-learn compatible object, default = None
@@ -312,7 +314,7 @@ def compare_models(
         is ignored when cross_validation is set to False.
 
 
-    sort: str, default = 'R2'
+    sort: str, default = 'smape'
         The sort order of the score grid. It also accepts custom metrics that are
         added through the ``add_metric`` function.
 
diff --git a/requirements-ts.txt b/requirements-ts.txt
index 50b06d6ed..045474921 100644
--- a/requirements-ts.txt
+++ b/requirements-ts.txt
@@ -1,2 +1,2 @@
 sktime==0.5.3
-pmdarima>=1.8.0
+pmdarima==1.8.0
diff --git a/test_time_series.ipynb b/test_time_series.ipynb
index 71a427f71..b5c1bcd0b 100644
--- a/test_time_series.ipynb
+++ b/test_time_series.ipynb
@@ -22,26 +22,27 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
        "(<Figure size 1152x288 with 1 Axes>,\n",
-       " <AxesSubplot:ylabel='Number of airline passengers'>)"
+       " <matplotlib.axes._subplots.AxesSubplot at 0x7fe1aa2d2f90>)"
       ]
      },
+     "execution_count": 2,
      "metadata": {},
-     "execution_count": 2
+     "output_type": "execute_result"
     },
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<Figure size 1152x288 with 1 Axes>",
-      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\r\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n<!-- Created with matplotlib (https://matplotlib.org/) -->\r\n<svg height=\"248.518125pt\" version=\"1.1\" viewBox=\"0 0 946.965625 248.518125\" width=\"946.965625pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n <metadata>\r\n  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\r\n   <cc:Work>\r\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\r\n    <dc:date>2021-04-17T10:50:11.935248</dc:date>\r\n    <dc:format>image/svg+xml</dc:format>\r\n    <dc:creator>\r\n     <cc:Agent>\r\n      <dc:title>Matplotlib v3.3.4, https://matplotlib.org/</dc:title>\r\n     </cc:Agent>\r\n    </dc:creator>\r\n   </cc:Work>\r\n  </rdf:RDF>\r\n </metadata>\r\n <defs>\r\n  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\r\n </defs>\r\n <g id=\"figure_1\">\r\n  <g id=\"patch_1\">\r\n   <path d=\"M 0 248.518125 \r\nL 946.965625 248.518125 \r\nL 946.965625 0 \r\nL 0 0 \r\nz\r\n\" style=\"fill:none;\"/>\r\n  </g>\r\n  <g id=\"axes_1\">\r\n   <g id=\"patch_2\">\r\n    <path d=\"M 46.965625 224.64 \r\nL 939.765625 224.64 \r\nL 939.765625 7.2 \r\nL 46.965625 7.2 \r\nz\r\n\" style=\"fill:#ffffff;\"/>\r\n   </g>\r\n   <g id=\"matplotlib.axis_1\">\r\n    <g id=\"xtick_1\">\r\n     <g id=\"line2d_1\">\r\n      <defs>\r\n       <path d=\"M 0 0 \r\nL 0 3.5 \r\n\" id=\"m0ab183ef01\" style=\"stroke:#000000;stroke-width:0.8;\"/>\r\n      </defs>\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"87.547443\" xlink:href=\"#m0ab183ef01\" y=\"224.64\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_1\">\r\n      <!-- 1949-01 -->\r\n      <g transform=\"translate(66.656037 239.238437)scale(0.1 -0.1)\">\r\n       <defs>\r\n        <path d=\"M 12.40625 8.296875 \r\nL 28.515625 8.296875 \r\nL 28.515625 63.921875 \r\nL 10.984375 60.40625 \r\nL 10.984375 69.390625 \r\nL 28.421875 72.90625 \r\nL 38.28125 72.90625 \r\nL 38.28125 8.296875 \r\nL 54.390625 8.296875 \r\nL 54.390625 0 \r\nL 12.40625 0 \r\nz\r\n\" id=\"DejaVuSans-49\"/>\r\n        <path d=\"M 10.984375 1.515625 \r\nL 10.984375 10.5 \r\nQ 14.703125 8.734375 18.5 7.8125 \r\nQ 22.3125 6.890625 25.984375 6.890625 \r\nQ 35.75 6.890625 40.890625 13.453125 \r\nQ 46.046875 20.015625 46.78125 33.40625 \r\nQ 43.953125 29.203125 39.59375 26.953125 \r\nQ 35.25 24.703125 29.984375 24.703125 \r\nQ 19.046875 24.703125 12.671875 31.3125 \r\nQ 6.296875 37.9375 6.296875 49.421875 \r\nQ 6.296875 60.640625 12.9375 67.421875 \r\nQ 19.578125 74.21875 30.609375 74.21875 \r\nQ 43.265625 74.21875 49.921875 64.515625 \r\nQ 56.59375 54.828125 56.59375 36.375 \r\nQ 56.59375 19.140625 48.40625 8.859375 \r\nQ 40.234375 -1.421875 26.421875 -1.421875 \r\nQ 22.703125 -1.421875 18.890625 -0.6875 \r\nQ 15.09375 0.046875 10.984375 1.515625 \r\nz\r\nM 30.609375 32.421875 \r\nQ 37.25 32.421875 41.125 36.953125 \r\nQ 45.015625 41.5 45.015625 49.421875 \r\nQ 45.015625 57.28125 41.125 61.84375 \r\nQ 37.25 66.40625 30.609375 66.40625 \r\nQ 23.96875 66.40625 20.09375 61.84375 \r\nQ 16.21875 57.28125 16.21875 49.421875 \r\nQ 16.21875 41.5 20.09375 36.953125 \r\nQ 23.96875 32.421875 30.609375 32.421875 \r\nz\r\n\" id=\"DejaVuSans-57\"/>\r\n        <path d=\"M 37.796875 64.3125 \r\nL 12.890625 25.390625 \r\nL 37.796875 25.390625 \r\nz\r\nM 35.203125 72.90625 \r\nL 47.609375 72.90625 \r\nL 47.609375 25.390625 \r\nL 58.015625 25.390625 \r\nL 58.015625 17.1875 \r\nL 47.609375 17.1875 \r\nL 47.609375 0 \r\nL 37.796875 0 \r\nL 37.796875 17.1875 \r\nL 4.890625 17.1875 \r\nL 4.890625 26.703125 \r\nz\r\n\" id=\"DejaVuSans-52\"/>\r\n        <path d=\"M 4.890625 31.390625 \r\nL 31.203125 31.390625 \r\nL 31.203125 23.390625 \r\nL 4.890625 23.390625 \r\nz\r\n\" id=\"DejaVuSans-45\"/>\r\n        <path d=\"M 31.78125 66.40625 \r\nQ 24.171875 66.40625 20.328125 58.90625 \r\nQ 16.5 51.421875 16.5 36.375 \r\nQ 16.5 21.390625 20.328125 13.890625 \r\nQ 24.171875 6.390625 31.78125 6.390625 \r\nQ 39.453125 6.390625 43.28125 13.890625 \r\nQ 47.125 21.390625 47.125 36.375 \r\nQ 47.125 51.421875 43.28125 58.90625 \r\nQ 39.453125 66.40625 31.78125 66.40625 \r\nz\r\nM 31.78125 74.21875 \r\nQ 44.046875 74.21875 50.515625 64.515625 \r\nQ 56.984375 54.828125 56.984375 36.375 \r\nQ 56.984375 17.96875 50.515625 8.265625 \r\nQ 44.046875 -1.421875 31.78125 -1.421875 \r\nQ 19.53125 -1.421875 13.0625 8.265625 \r\nQ 6.59375 17.96875 6.59375 36.375 \r\nQ 6.59375 54.828125 13.0625 64.515625 \r\nQ 19.53125 74.21875 31.78125 74.21875 \r\nz\r\n\" id=\"DejaVuSans-48\"/>\r\n       </defs>\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-52\"/>\r\n       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"254.492188\" xlink:href=\"#DejaVuSans-45\"/>\r\n       <use x=\"290.576172\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"354.199219\" xlink:href=\"#DejaVuSans-49\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_2\">\r\n     <g id=\"line2d_2\">\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"201.063019\" xlink:href=\"#m0ab183ef01\" y=\"224.64\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_2\">\r\n      <!-- 1950-09 -->\r\n      <g transform=\"translate(180.171612 239.238437)scale(0.1 -0.1)\">\r\n       <defs>\r\n        <path d=\"M 10.796875 72.90625 \r\nL 49.515625 72.90625 \r\nL 49.515625 64.59375 \r\nL 19.828125 64.59375 \r\nL 19.828125 46.734375 \r\nQ 21.96875 47.46875 24.109375 47.828125 \r\nQ 26.265625 48.1875 28.421875 48.1875 \r\nQ 40.625 48.1875 47.75 41.5 \r\nQ 54.890625 34.8125 54.890625 23.390625 \r\nQ 54.890625 11.625 47.5625 5.09375 \r\nQ 40.234375 -1.421875 26.90625 -1.421875 \r\nQ 22.3125 -1.421875 17.546875 -0.640625 \r\nQ 12.796875 0.140625 7.71875 1.703125 \r\nL 7.71875 11.625 \r\nQ 12.109375 9.234375 16.796875 8.0625 \r\nQ 21.484375 6.890625 26.703125 6.890625 \r\nQ 35.15625 6.890625 40.078125 11.328125 \r\nQ 45.015625 15.765625 45.015625 23.390625 \r\nQ 45.015625 31 40.078125 35.4375 \r\nQ 35.15625 39.890625 26.703125 39.890625 \r\nQ 22.75 39.890625 18.8125 39.015625 \r\nQ 14.890625 38.140625 10.796875 36.28125 \r\nz\r\n\" id=\"DejaVuSans-53\"/>\r\n       </defs>\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"254.492188\" xlink:href=\"#DejaVuSans-45\"/>\r\n       <use x=\"290.576172\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"354.199219\" xlink:href=\"#DejaVuSans-57\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_3\">\r\n     <g id=\"line2d_3\">\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"314.578594\" xlink:href=\"#m0ab183ef01\" y=\"224.64\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_3\">\r\n      <!-- 1952-05 -->\r\n      <g transform=\"translate(293.687188 239.238437)scale(0.1 -0.1)\">\r\n       <defs>\r\n        <path d=\"M 19.1875 8.296875 \r\nL 53.609375 8.296875 \r\nL 53.609375 0 \r\nL 7.328125 0 \r\nL 7.328125 8.296875 \r\nQ 12.9375 14.109375 22.625 23.890625 \r\nQ 32.328125 33.6875 34.8125 36.53125 \r\nQ 39.546875 41.84375 41.421875 45.53125 \r\nQ 43.3125 49.21875 43.3125 52.78125 \r\nQ 43.3125 58.59375 39.234375 62.25 \r\nQ 35.15625 65.921875 28.609375 65.921875 \r\nQ 23.96875 65.921875 18.8125 64.3125 \r\nQ 13.671875 62.703125 7.8125 59.421875 \r\nL 7.8125 69.390625 \r\nQ 13.765625 71.78125 18.9375 73 \r\nQ 24.125 74.21875 28.421875 74.21875 \r\nQ 39.75 74.21875 46.484375 68.546875 \r\nQ 53.21875 62.890625 53.21875 53.421875 \r\nQ 53.21875 48.921875 51.53125 44.890625 \r\nQ 49.859375 40.875 45.40625 35.40625 \r\nQ 44.1875 33.984375 37.640625 27.21875 \r\nQ 31.109375 20.453125 19.1875 8.296875 \r\nz\r\n\" id=\"DejaVuSans-50\"/>\r\n       </defs>\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-50\"/>\r\n       <use x=\"254.492188\" xlink:href=\"#DejaVuSans-45\"/>\r\n       <use x=\"290.576172\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"354.199219\" xlink:href=\"#DejaVuSans-53\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_4\">\r\n     <g id=\"line2d_4\">\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"428.094169\" xlink:href=\"#m0ab183ef01\" y=\"224.64\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_4\">\r\n      <!-- 1954-01 -->\r\n      <g transform=\"translate(407.202763 239.238437)scale(0.1 -0.1)\">\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-52\"/>\r\n       <use x=\"254.492188\" xlink:href=\"#DejaVuSans-45\"/>\r\n       <use x=\"290.576172\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"354.199219\" xlink:href=\"#DejaVuSans-49\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_5\">\r\n     <g id=\"line2d_5\">\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"541.609745\" xlink:href=\"#m0ab183ef01\" y=\"224.64\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_5\">\r\n      <!-- 1955-09 -->\r\n      <g transform=\"translate(520.718338 239.238437)scale(0.1 -0.1)\">\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"254.492188\" xlink:href=\"#DejaVuSans-45\"/>\r\n       <use x=\"290.576172\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"354.199219\" xlink:href=\"#DejaVuSans-57\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_6\">\r\n     <g id=\"line2d_6\">\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"655.12532\" xlink:href=\"#m0ab183ef01\" y=\"224.64\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_6\">\r\n      <!-- 1957-05 -->\r\n      <g transform=\"translate(634.233914 239.238437)scale(0.1 -0.1)\">\r\n       <defs>\r\n        <path d=\"M 8.203125 72.90625 \r\nL 55.078125 72.90625 \r\nL 55.078125 68.703125 \r\nL 28.609375 0 \r\nL 18.3125 0 \r\nL 43.21875 64.59375 \r\nL 8.203125 64.59375 \r\nz\r\n\" id=\"DejaVuSans-55\"/>\r\n       </defs>\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-55\"/>\r\n       <use x=\"254.492188\" xlink:href=\"#DejaVuSans-45\"/>\r\n       <use x=\"290.576172\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"354.199219\" xlink:href=\"#DejaVuSans-53\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_7\">\r\n     <g id=\"line2d_7\">\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"768.640895\" xlink:href=\"#m0ab183ef01\" y=\"224.64\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_7\">\r\n      <!-- 1959-01 -->\r\n      <g transform=\"translate(747.749489 239.238437)scale(0.1 -0.1)\">\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"254.492188\" xlink:href=\"#DejaVuSans-45\"/>\r\n       <use x=\"290.576172\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"354.199219\" xlink:href=\"#DejaVuSans-49\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"xtick_8\">\r\n     <g id=\"line2d_8\">\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"882.156471\" xlink:href=\"#m0ab183ef01\" y=\"224.64\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_8\">\r\n      <!-- 1960-09 -->\r\n      <g transform=\"translate(861.265064 239.238437)scale(0.1 -0.1)\">\r\n       <defs>\r\n        <path d=\"M 33.015625 40.375 \r\nQ 26.375 40.375 22.484375 35.828125 \r\nQ 18.609375 31.296875 18.609375 23.390625 \r\nQ 18.609375 15.53125 22.484375 10.953125 \r\nQ 26.375 6.390625 33.015625 6.390625 \r\nQ 39.65625 6.390625 43.53125 10.953125 \r\nQ 47.40625 15.53125 47.40625 23.390625 \r\nQ 47.40625 31.296875 43.53125 35.828125 \r\nQ 39.65625 40.375 33.015625 40.375 \r\nz\r\nM 52.59375 71.296875 \r\nL 52.59375 62.3125 \r\nQ 48.875 64.0625 45.09375 64.984375 \r\nQ 41.3125 65.921875 37.59375 65.921875 \r\nQ 27.828125 65.921875 22.671875 59.328125 \r\nQ 17.53125 52.734375 16.796875 39.40625 \r\nQ 19.671875 43.65625 24.015625 45.921875 \r\nQ 28.375 48.1875 33.59375 48.1875 \r\nQ 44.578125 48.1875 50.953125 41.515625 \r\nQ 57.328125 34.859375 57.328125 23.390625 \r\nQ 57.328125 12.15625 50.6875 5.359375 \r\nQ 44.046875 -1.421875 33.015625 -1.421875 \r\nQ 20.359375 -1.421875 13.671875 8.265625 \r\nQ 6.984375 17.96875 6.984375 36.375 \r\nQ 6.984375 53.65625 15.1875 63.9375 \r\nQ 23.390625 74.21875 37.203125 74.21875 \r\nQ 40.921875 74.21875 44.703125 73.484375 \r\nQ 48.484375 72.75 52.59375 71.296875 \r\nz\r\n\" id=\"DejaVuSans-54\"/>\r\n       </defs>\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-57\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-54\"/>\r\n       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"254.492188\" xlink:href=\"#DejaVuSans-45\"/>\r\n       <use x=\"290.576172\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"354.199219\" xlink:href=\"#DejaVuSans-57\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n   </g>\r\n   <g id=\"matplotlib.axis_2\">\r\n    <g id=\"ytick_1\">\r\n     <g id=\"line2d_9\">\r\n      <defs>\r\n       <path d=\"M 0 0 \r\nL -3.5 0 \r\n\" id=\"m2a2fff43ac\" style=\"stroke:#000000;stroke-width:0.8;\"/>\r\n      </defs>\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"46.965625\" xlink:href=\"#m2a2fff43ac\" y=\"216.282794\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_9\">\r\n      <!-- 100 -->\r\n      <g transform=\"translate(20.878125 220.082013)scale(0.1 -0.1)\">\r\n       <use xlink:href=\"#DejaVuSans-49\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_2\">\r\n     <g id=\"line2d_10\">\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"46.965625\" xlink:href=\"#m2a2fff43ac\" y=\"178.122036\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_10\">\r\n      <!-- 200 -->\r\n      <g transform=\"translate(20.878125 181.921255)scale(0.1 -0.1)\">\r\n       <use xlink:href=\"#DejaVuSans-50\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_3\">\r\n     <g id=\"line2d_11\">\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"46.965625\" xlink:href=\"#m2a2fff43ac\" y=\"139.961278\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_11\">\r\n      <!-- 300 -->\r\n      <g transform=\"translate(20.878125 143.760496)scale(0.1 -0.1)\">\r\n       <defs>\r\n        <path d=\"M 40.578125 39.3125 \r\nQ 47.65625 37.796875 51.625 33 \r\nQ 55.609375 28.21875 55.609375 21.1875 \r\nQ 55.609375 10.40625 48.1875 4.484375 \r\nQ 40.765625 -1.421875 27.09375 -1.421875 \r\nQ 22.515625 -1.421875 17.65625 -0.515625 \r\nQ 12.796875 0.390625 7.625 2.203125 \r\nL 7.625 11.71875 \r\nQ 11.71875 9.328125 16.59375 8.109375 \r\nQ 21.484375 6.890625 26.8125 6.890625 \r\nQ 36.078125 6.890625 40.9375 10.546875 \r\nQ 45.796875 14.203125 45.796875 21.1875 \r\nQ 45.796875 27.640625 41.28125 31.265625 \r\nQ 36.765625 34.90625 28.71875 34.90625 \r\nL 20.21875 34.90625 \r\nL 20.21875 43.015625 \r\nL 29.109375 43.015625 \r\nQ 36.375 43.015625 40.234375 45.921875 \r\nQ 44.09375 48.828125 44.09375 54.296875 \r\nQ 44.09375 59.90625 40.109375 62.90625 \r\nQ 36.140625 65.921875 28.71875 65.921875 \r\nQ 24.65625 65.921875 20.015625 65.03125 \r\nQ 15.375 64.15625 9.8125 62.3125 \r\nL 9.8125 71.09375 \r\nQ 15.4375 72.65625 20.34375 73.4375 \r\nQ 25.25 74.21875 29.59375 74.21875 \r\nQ 40.828125 74.21875 47.359375 69.109375 \r\nQ 53.90625 64.015625 53.90625 55.328125 \r\nQ 53.90625 49.265625 50.4375 45.09375 \r\nQ 46.96875 40.921875 40.578125 39.3125 \r\nz\r\n\" id=\"DejaVuSans-51\"/>\r\n       </defs>\r\n       <use xlink:href=\"#DejaVuSans-51\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_4\">\r\n     <g id=\"line2d_12\">\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"46.965625\" xlink:href=\"#m2a2fff43ac\" y=\"101.800519\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_12\">\r\n      <!-- 400 -->\r\n      <g transform=\"translate(20.878125 105.599738)scale(0.1 -0.1)\">\r\n       <use xlink:href=\"#DejaVuSans-52\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_5\">\r\n     <g id=\"line2d_13\">\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"46.965625\" xlink:href=\"#m2a2fff43ac\" y=\"63.639761\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_13\">\r\n      <!-- 500 -->\r\n      <g transform=\"translate(20.878125 67.43898)scale(0.1 -0.1)\">\r\n       <use xlink:href=\"#DejaVuSans-53\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"ytick_6\">\r\n     <g id=\"line2d_14\">\r\n      <g>\r\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"46.965625\" xlink:href=\"#m2a2fff43ac\" y=\"25.479003\"/>\r\n      </g>\r\n     </g>\r\n     <g id=\"text_14\">\r\n      <!-- 600 -->\r\n      <g transform=\"translate(20.878125 29.278222)scale(0.1 -0.1)\">\r\n       <use xlink:href=\"#DejaVuSans-54\"/>\r\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\r\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\r\n      </g>\r\n     </g>\r\n    </g>\r\n    <g id=\"text_15\">\r\n     <!-- Number of airline passengers -->\r\n     <g transform=\"translate(14.798438 189.728594)rotate(-90)scale(0.1 -0.1)\">\r\n      <defs>\r\n       <path d=\"M 9.8125 72.90625 \r\nL 23.09375 72.90625 \r\nL 55.421875 11.921875 \r\nL 55.421875 72.90625 \r\nL 64.984375 72.90625 \r\nL 64.984375 0 \r\nL 51.703125 0 \r\nL 19.390625 60.984375 \r\nL 19.390625 0 \r\nL 9.8125 0 \r\nz\r\n\" id=\"DejaVuSans-78\"/>\r\n       <path d=\"M 8.5 21.578125 \r\nL 8.5 54.6875 \r\nL 17.484375 54.6875 \r\nL 17.484375 21.921875 \r\nQ 17.484375 14.15625 20.5 10.265625 \r\nQ 23.53125 6.390625 29.59375 6.390625 \r\nQ 36.859375 6.390625 41.078125 11.03125 \r\nQ 45.3125 15.671875 45.3125 23.6875 \r\nL 45.3125 54.6875 \r\nL 54.296875 54.6875 \r\nL 54.296875 0 \r\nL 45.3125 0 \r\nL 45.3125 8.40625 \r\nQ 42.046875 3.421875 37.71875 1 \r\nQ 33.40625 -1.421875 27.6875 -1.421875 \r\nQ 18.265625 -1.421875 13.375 4.4375 \r\nQ 8.5 10.296875 8.5 21.578125 \r\nz\r\nM 31.109375 56 \r\nz\r\n\" id=\"DejaVuSans-117\"/>\r\n       <path d=\"M 52 44.1875 \r\nQ 55.375 50.25 60.0625 53.125 \r\nQ 64.75 56 71.09375 56 \r\nQ 79.640625 56 84.28125 50.015625 \r\nQ 88.921875 44.046875 88.921875 33.015625 \r\nL 88.921875 0 \r\nL 79.890625 0 \r\nL 79.890625 32.71875 \r\nQ 79.890625 40.578125 77.09375 44.375 \r\nQ 74.3125 48.1875 68.609375 48.1875 \r\nQ 61.625 48.1875 57.5625 43.546875 \r\nQ 53.515625 38.921875 53.515625 30.90625 \r\nL 53.515625 0 \r\nL 44.484375 0 \r\nL 44.484375 32.71875 \r\nQ 44.484375 40.625 41.703125 44.40625 \r\nQ 38.921875 48.1875 33.109375 48.1875 \r\nQ 26.21875 48.1875 22.15625 43.53125 \r\nQ 18.109375 38.875 18.109375 30.90625 \r\nL 18.109375 0 \r\nL 9.078125 0 \r\nL 9.078125 54.6875 \r\nL 18.109375 54.6875 \r\nL 18.109375 46.1875 \r\nQ 21.1875 51.21875 25.484375 53.609375 \r\nQ 29.78125 56 35.6875 56 \r\nQ 41.65625 56 45.828125 52.96875 \r\nQ 50 49.953125 52 44.1875 \r\nz\r\n\" id=\"DejaVuSans-109\"/>\r\n       <path d=\"M 48.6875 27.296875 \r\nQ 48.6875 37.203125 44.609375 42.84375 \r\nQ 40.53125 48.484375 33.40625 48.484375 \r\nQ 26.265625 48.484375 22.1875 42.84375 \r\nQ 18.109375 37.203125 18.109375 27.296875 \r\nQ 18.109375 17.390625 22.1875 11.75 \r\nQ 26.265625 6.109375 33.40625 6.109375 \r\nQ 40.53125 6.109375 44.609375 11.75 \r\nQ 48.6875 17.390625 48.6875 27.296875 \r\nz\r\nM 18.109375 46.390625 \r\nQ 20.953125 51.265625 25.265625 53.625 \r\nQ 29.59375 56 35.59375 56 \r\nQ 45.5625 56 51.78125 48.09375 \r\nQ 58.015625 40.1875 58.015625 27.296875 \r\nQ 58.015625 14.40625 51.78125 6.484375 \r\nQ 45.5625 -1.421875 35.59375 -1.421875 \r\nQ 29.59375 -1.421875 25.265625 0.953125 \r\nQ 20.953125 3.328125 18.109375 8.203125 \r\nL 18.109375 0 \r\nL 9.078125 0 \r\nL 9.078125 75.984375 \r\nL 18.109375 75.984375 \r\nz\r\n\" id=\"DejaVuSans-98\"/>\r\n       <path d=\"M 56.203125 29.59375 \r\nL 56.203125 25.203125 \r\nL 14.890625 25.203125 \r\nQ 15.484375 15.921875 20.484375 11.0625 \r\nQ 25.484375 6.203125 34.421875 6.203125 \r\nQ 39.59375 6.203125 44.453125 7.46875 \r\nQ 49.3125 8.734375 54.109375 11.28125 \r\nL 54.109375 2.78125 \r\nQ 49.265625 0.734375 44.1875 -0.34375 \r\nQ 39.109375 -1.421875 33.890625 -1.421875 \r\nQ 20.796875 -1.421875 13.15625 6.1875 \r\nQ 5.515625 13.8125 5.515625 26.8125 \r\nQ 5.515625 40.234375 12.765625 48.109375 \r\nQ 20.015625 56 32.328125 56 \r\nQ 43.359375 56 49.78125 48.890625 \r\nQ 56.203125 41.796875 56.203125 29.59375 \r\nz\r\nM 47.21875 32.234375 \r\nQ 47.125 39.59375 43.09375 43.984375 \r\nQ 39.0625 48.390625 32.421875 48.390625 \r\nQ 24.90625 48.390625 20.390625 44.140625 \r\nQ 15.875 39.890625 15.1875 32.171875 \r\nz\r\n\" id=\"DejaVuSans-101\"/>\r\n       <path d=\"M 41.109375 46.296875 \r\nQ 39.59375 47.171875 37.8125 47.578125 \r\nQ 36.03125 48 33.890625 48 \r\nQ 26.265625 48 22.1875 43.046875 \r\nQ 18.109375 38.09375 18.109375 28.8125 \r\nL 18.109375 0 \r\nL 9.078125 0 \r\nL 9.078125 54.6875 \r\nL 18.109375 54.6875 \r\nL 18.109375 46.1875 \r\nQ 20.953125 51.171875 25.484375 53.578125 \r\nQ 30.03125 56 36.53125 56 \r\nQ 37.453125 56 38.578125 55.875 \r\nQ 39.703125 55.765625 41.0625 55.515625 \r\nz\r\n\" id=\"DejaVuSans-114\"/>\r\n       <path id=\"DejaVuSans-32\"/>\r\n       <path d=\"M 30.609375 48.390625 \r\nQ 23.390625 48.390625 19.1875 42.75 \r\nQ 14.984375 37.109375 14.984375 27.296875 \r\nQ 14.984375 17.484375 19.15625 11.84375 \r\nQ 23.34375 6.203125 30.609375 6.203125 \r\nQ 37.796875 6.203125 41.984375 11.859375 \r\nQ 46.1875 17.53125 46.1875 27.296875 \r\nQ 46.1875 37.015625 41.984375 42.703125 \r\nQ 37.796875 48.390625 30.609375 48.390625 \r\nz\r\nM 30.609375 56 \r\nQ 42.328125 56 49.015625 48.375 \r\nQ 55.71875 40.765625 55.71875 27.296875 \r\nQ 55.71875 13.875 49.015625 6.21875 \r\nQ 42.328125 -1.421875 30.609375 -1.421875 \r\nQ 18.84375 -1.421875 12.171875 6.21875 \r\nQ 5.515625 13.875 5.515625 27.296875 \r\nQ 5.515625 40.765625 12.171875 48.375 \r\nQ 18.84375 56 30.609375 56 \r\nz\r\n\" id=\"DejaVuSans-111\"/>\r\n       <path d=\"M 37.109375 75.984375 \r\nL 37.109375 68.5 \r\nL 28.515625 68.5 \r\nQ 23.6875 68.5 21.796875 66.546875 \r\nQ 19.921875 64.59375 19.921875 59.515625 \r\nL 19.921875 54.6875 \r\nL 34.71875 54.6875 \r\nL 34.71875 47.703125 \r\nL 19.921875 47.703125 \r\nL 19.921875 0 \r\nL 10.890625 0 \r\nL 10.890625 47.703125 \r\nL 2.296875 47.703125 \r\nL 2.296875 54.6875 \r\nL 10.890625 54.6875 \r\nL 10.890625 58.5 \r\nQ 10.890625 67.625 15.140625 71.796875 \r\nQ 19.390625 75.984375 28.609375 75.984375 \r\nz\r\n\" id=\"DejaVuSans-102\"/>\r\n       <path d=\"M 34.28125 27.484375 \r\nQ 23.390625 27.484375 19.1875 25 \r\nQ 14.984375 22.515625 14.984375 16.5 \r\nQ 14.984375 11.71875 18.140625 8.90625 \r\nQ 21.296875 6.109375 26.703125 6.109375 \r\nQ 34.1875 6.109375 38.703125 11.40625 \r\nQ 43.21875 16.703125 43.21875 25.484375 \r\nL 43.21875 27.484375 \r\nz\r\nM 52.203125 31.203125 \r\nL 52.203125 0 \r\nL 43.21875 0 \r\nL 43.21875 8.296875 \r\nQ 40.140625 3.328125 35.546875 0.953125 \r\nQ 30.953125 -1.421875 24.3125 -1.421875 \r\nQ 15.921875 -1.421875 10.953125 3.296875 \r\nQ 6 8.015625 6 15.921875 \r\nQ 6 25.140625 12.171875 29.828125 \r\nQ 18.359375 34.515625 30.609375 34.515625 \r\nL 43.21875 34.515625 \r\nL 43.21875 35.40625 \r\nQ 43.21875 41.609375 39.140625 45 \r\nQ 35.0625 48.390625 27.6875 48.390625 \r\nQ 23 48.390625 18.546875 47.265625 \r\nQ 14.109375 46.140625 10.015625 43.890625 \r\nL 10.015625 52.203125 \r\nQ 14.9375 54.109375 19.578125 55.046875 \r\nQ 24.21875 56 28.609375 56 \r\nQ 40.484375 56 46.34375 49.84375 \r\nQ 52.203125 43.703125 52.203125 31.203125 \r\nz\r\n\" id=\"DejaVuSans-97\"/>\r\n       <path d=\"M 9.421875 54.6875 \r\nL 18.40625 54.6875 \r\nL 18.40625 0 \r\nL 9.421875 0 \r\nz\r\nM 9.421875 75.984375 \r\nL 18.40625 75.984375 \r\nL 18.40625 64.59375 \r\nL 9.421875 64.59375 \r\nz\r\n\" id=\"DejaVuSans-105\"/>\r\n       <path d=\"M 9.421875 75.984375 \r\nL 18.40625 75.984375 \r\nL 18.40625 0 \r\nL 9.421875 0 \r\nz\r\n\" id=\"DejaVuSans-108\"/>\r\n       <path d=\"M 54.890625 33.015625 \r\nL 54.890625 0 \r\nL 45.90625 0 \r\nL 45.90625 32.71875 \r\nQ 45.90625 40.484375 42.875 44.328125 \r\nQ 39.84375 48.1875 33.796875 48.1875 \r\nQ 26.515625 48.1875 22.3125 43.546875 \r\nQ 18.109375 38.921875 18.109375 30.90625 \r\nL 18.109375 0 \r\nL 9.078125 0 \r\nL 9.078125 54.6875 \r\nL 18.109375 54.6875 \r\nL 18.109375 46.1875 \r\nQ 21.34375 51.125 25.703125 53.5625 \r\nQ 30.078125 56 35.796875 56 \r\nQ 45.21875 56 50.046875 50.171875 \r\nQ 54.890625 44.34375 54.890625 33.015625 \r\nz\r\n\" id=\"DejaVuSans-110\"/>\r\n       <path d=\"M 18.109375 8.203125 \r\nL 18.109375 -20.796875 \r\nL 9.078125 -20.796875 \r\nL 9.078125 54.6875 \r\nL 18.109375 54.6875 \r\nL 18.109375 46.390625 \r\nQ 20.953125 51.265625 25.265625 53.625 \r\nQ 29.59375 56 35.59375 56 \r\nQ 45.5625 56 51.78125 48.09375 \r\nQ 58.015625 40.1875 58.015625 27.296875 \r\nQ 58.015625 14.40625 51.78125 6.484375 \r\nQ 45.5625 -1.421875 35.59375 -1.421875 \r\nQ 29.59375 -1.421875 25.265625 0.953125 \r\nQ 20.953125 3.328125 18.109375 8.203125 \r\nz\r\nM 48.6875 27.296875 \r\nQ 48.6875 37.203125 44.609375 42.84375 \r\nQ 40.53125 48.484375 33.40625 48.484375 \r\nQ 26.265625 48.484375 22.1875 42.84375 \r\nQ 18.109375 37.203125 18.109375 27.296875 \r\nQ 18.109375 17.390625 22.1875 11.75 \r\nQ 26.265625 6.109375 33.40625 6.109375 \r\nQ 40.53125 6.109375 44.609375 11.75 \r\nQ 48.6875 17.390625 48.6875 27.296875 \r\nz\r\n\" id=\"DejaVuSans-112\"/>\r\n       <path d=\"M 44.28125 53.078125 \r\nL 44.28125 44.578125 \r\nQ 40.484375 46.53125 36.375 47.5 \r\nQ 32.28125 48.484375 27.875 48.484375 \r\nQ 21.1875 48.484375 17.84375 46.4375 \r\nQ 14.5 44.390625 14.5 40.28125 \r\nQ 14.5 37.15625 16.890625 35.375 \r\nQ 19.28125 33.59375 26.515625 31.984375 \r\nL 29.59375 31.296875 \r\nQ 39.15625 29.25 43.1875 25.515625 \r\nQ 47.21875 21.78125 47.21875 15.09375 \r\nQ 47.21875 7.46875 41.1875 3.015625 \r\nQ 35.15625 -1.421875 24.609375 -1.421875 \r\nQ 20.21875 -1.421875 15.453125 -0.5625 \r\nQ 10.6875 0.296875 5.421875 2 \r\nL 5.421875 11.28125 \r\nQ 10.40625 8.6875 15.234375 7.390625 \r\nQ 20.0625 6.109375 24.8125 6.109375 \r\nQ 31.15625 6.109375 34.5625 8.28125 \r\nQ 37.984375 10.453125 37.984375 14.40625 \r\nQ 37.984375 18.0625 35.515625 20.015625 \r\nQ 33.0625 21.96875 24.703125 23.78125 \r\nL 21.578125 24.515625 \r\nQ 13.234375 26.265625 9.515625 29.90625 \r\nQ 5.8125 33.546875 5.8125 39.890625 \r\nQ 5.8125 47.609375 11.28125 51.796875 \r\nQ 16.75 56 26.8125 56 \r\nQ 31.78125 56 36.171875 55.265625 \r\nQ 40.578125 54.546875 44.28125 53.078125 \r\nz\r\n\" id=\"DejaVuSans-115\"/>\r\n       <path d=\"M 45.40625 27.984375 \r\nQ 45.40625 37.75 41.375 43.109375 \r\nQ 37.359375 48.484375 30.078125 48.484375 \r\nQ 22.859375 48.484375 18.828125 43.109375 \r\nQ 14.796875 37.75 14.796875 27.984375 \r\nQ 14.796875 18.265625 18.828125 12.890625 \r\nQ 22.859375 7.515625 30.078125 7.515625 \r\nQ 37.359375 7.515625 41.375 12.890625 \r\nQ 45.40625 18.265625 45.40625 27.984375 \r\nz\r\nM 54.390625 6.78125 \r\nQ 54.390625 -7.171875 48.1875 -13.984375 \r\nQ 42 -20.796875 29.203125 -20.796875 \r\nQ 24.46875 -20.796875 20.265625 -20.09375 \r\nQ 16.0625 -19.390625 12.109375 -17.921875 \r\nL 12.109375 -9.1875 \r\nQ 16.0625 -11.328125 19.921875 -12.34375 \r\nQ 23.78125 -13.375 27.78125 -13.375 \r\nQ 36.625 -13.375 41.015625 -8.765625 \r\nQ 45.40625 -4.15625 45.40625 5.171875 \r\nL 45.40625 9.625 \r\nQ 42.625 4.78125 38.28125 2.390625 \r\nQ 33.9375 0 27.875 0 \r\nQ 17.828125 0 11.671875 7.65625 \r\nQ 5.515625 15.328125 5.515625 27.984375 \r\nQ 5.515625 40.671875 11.671875 48.328125 \r\nQ 17.828125 56 27.875 56 \r\nQ 33.9375 56 38.28125 53.609375 \r\nQ 42.625 51.21875 45.40625 46.390625 \r\nL 45.40625 54.6875 \r\nL 54.390625 54.6875 \r\nz\r\n\" id=\"DejaVuSans-103\"/>\r\n      </defs>\r\n      <use xlink:href=\"#DejaVuSans-78\"/>\r\n      <use x=\"74.804688\" xlink:href=\"#DejaVuSans-117\"/>\r\n      <use x=\"138.183594\" xlink:href=\"#DejaVuSans-109\"/>\r\n      <use x=\"235.595703\" xlink:href=\"#DejaVuSans-98\"/>\r\n      <use x=\"299.072266\" xlink:href=\"#DejaVuSans-101\"/>\r\n      <use x=\"360.595703\" xlink:href=\"#DejaVuSans-114\"/>\r\n      <use x=\"401.708984\" xlink:href=\"#DejaVuSans-32\"/>\r\n      <use x=\"433.496094\" xlink:href=\"#DejaVuSans-111\"/>\r\n      <use x=\"494.677734\" xlink:href=\"#DejaVuSans-102\"/>\r\n      <use x=\"529.882812\" xlink:href=\"#DejaVuSans-32\"/>\r\n      <use x=\"561.669922\" xlink:href=\"#DejaVuSans-97\"/>\r\n      <use x=\"622.949219\" xlink:href=\"#DejaVuSans-105\"/>\r\n      <use x=\"650.732422\" xlink:href=\"#DejaVuSans-114\"/>\r\n      <use x=\"691.845703\" xlink:href=\"#DejaVuSans-108\"/>\r\n      <use x=\"719.628906\" xlink:href=\"#DejaVuSans-105\"/>\r\n      <use x=\"747.412109\" xlink:href=\"#DejaVuSans-110\"/>\r\n      <use x=\"810.791016\" xlink:href=\"#DejaVuSans-101\"/>\r\n      <use x=\"872.314453\" xlink:href=\"#DejaVuSans-32\"/>\r\n      <use x=\"904.101562\" xlink:href=\"#DejaVuSans-112\"/>\r\n      <use x=\"967.578125\" xlink:href=\"#DejaVuSans-97\"/>\r\n      <use x=\"1028.857422\" xlink:href=\"#DejaVuSans-115\"/>\r\n      <use x=\"1080.957031\" xlink:href=\"#DejaVuSans-115\"/>\r\n      <use x=\"1133.056641\" xlink:href=\"#DejaVuSans-101\"/>\r\n      <use x=\"1194.580078\" xlink:href=\"#DejaVuSans-110\"/>\r\n      <use x=\"1257.958984\" xlink:href=\"#DejaVuSans-103\"/>\r\n      <use x=\"1321.435547\" xlink:href=\"#DejaVuSans-101\"/>\r\n      <use x=\"1382.958984\" xlink:href=\"#DejaVuSans-114\"/>\r\n      <use x=\"1424.072266\" xlink:href=\"#DejaVuSans-115\"/>\r\n     </g>\r\n    </g>\r\n   </g>\r\n   <g id=\"line2d_15\">\r\n    <path clip-path=\"url(#pa8f17e7db1)\" d=\"M 87.547443 211.703503 \r\nL 93.223222 209.413857 \r\nL 98.899001 204.071351 \r\nL 104.574779 205.216174 \r\nL 110.250558 208.269035 \r\nL 115.926337 202.926529 \r\nL 121.602116 197.96563 \r\nL 127.277895 197.96563 \r\nL 132.953673 202.544921 \r\nL 138.629452 209.03225 \r\nL 144.305231 214.756364 \r\nL 149.98101 209.413857 \r\nL 155.656788 210.55868 \r\nL 161.332567 206.360997 \r\nL 167.008346 200.636883 \r\nL 172.684125 202.926529 \r\nL 178.359903 206.742604 \r\nL 184.035682 197.584022 \r\nL 189.711461 189.570263 \r\nL 195.38724 189.570263 \r\nL 201.063019 194.149554 \r\nL 206.738797 203.689744 \r\nL 212.414576 210.940288 \r\nL 218.090355 201.018491 \r\nL 229.441912 197.202415 \r\nL 235.117691 186.517403 \r\nL 240.79347 192.241516 \r\nL 246.469249 188.807048 \r\nL 252.145027 186.517403 \r\nL 257.820806 178.503643 \r\nL 263.496585 178.503643 \r\nL 269.172364 184.227757 \r\nL 274.848142 192.623124 \r\nL 280.523921 198.728845 \r\nL 286.1997 191.096694 \r\nL 291.875479 189.188656 \r\nL 297.551258 185.754187 \r\nL 303.227036 180.793289 \r\nL 308.902815 185.37258 \r\nL 314.578594 184.609365 \r\nL 320.254373 171.253099 \r\nL 331.60593 162.094517 \r\nL 337.281709 174.687568 \r\nL 342.957488 181.556504 \r\nL 348.633266 188.807048 \r\nL 354.309045 180.411681 \r\nL 359.984824 179.648466 \r\nL 365.660603 179.648466 \r\nL 371.336382 164.384163 \r\nL 377.01216 164.76577 \r\nL 382.687939 167.055416 \r\nL 388.363718 161.71291 \r\nL 394.039497 153.699151 \r\nL 399.715275 150.64629 \r\nL 405.391054 164.002555 \r\nL 411.066833 173.924352 \r\nL 416.742612 185.754187 \r\nL 422.41839 177.740428 \r\nL 428.094169 176.595605 \r\nL 433.769948 182.701327 \r\nL 439.445727 164.76577 \r\nL 445.121505 167.818631 \r\nL 450.797284 165.147378 \r\nL 456.473063 153.699151 \r\nL 462.148842 139.198062 \r\nL 467.824621 142.632531 \r\nL 473.500399 155.607188 \r\nL 479.176178 167.055416 \r\nL 484.851957 176.977213 \r\nL 490.527736 167.055416 \r\nL 496.203514 162.094517 \r\nL 501.879293 165.528986 \r\nL 507.555072 152.554328 \r\nL 513.230851 151.791113 \r\nL 518.906629 151.409505 \r\nL 524.582408 134.237164 \r\nL 530.258187 115.538392 \r\nL 535.933966 122.025721 \r\nL 541.609745 135.381987 \r\nL 547.285523 149.883075 \r\nL 552.961302 164.002555 \r\nL 558.637081 148.356644 \r\nL 564.31286 146.066999 \r\nL 569.988638 148.738252 \r\nL 575.664417 133.473949 \r\nL 581.340196 135.000379 \r\nL 587.015975 133.092341 \r\nL 592.691753 111.722317 \r\nL 598.367532 96.839621 \r\nL 604.043311 99.892482 \r\nL 615.394868 137.671632 \r\nL 621.070647 151.027898 \r\nL 626.746426 137.671632 \r\nL 632.422205 134.237164 \r\nL 638.097984 139.57967 \r\nL 643.773762 118.591253 \r\nL 649.449541 121.644114 \r\nL 655.12532 118.972861 \r\nL 660.801099 93.405153 \r\nL 666.476877 76.996027 \r\nL 672.152656 76.232812 \r\nL 677.828435 100.274089 \r\nL 683.504214 122.025721 \r\nL 689.179992 138.05324 \r\nL 694.855771 126.223405 \r\nL 700.53155 124.696974 \r\nL 706.207329 133.092341 \r\nL 711.883108 116.301608 \r\nL 717.558886 121.644114 \r\nL 723.234665 115.92 \r\nL 728.910444 88.444254 \r\nL 734.586223 67.07423 \r\nL 740.262001 61.731723 \r\nL 745.93778 100.274089 \r\nL 751.613559 117.44643 \r\nL 757.289338 136.145202 \r\nL 762.965116 125.841797 \r\nL 768.640895 117.064823 \r\nL 774.316674 123.933759 \r\nL 779.992453 99.510874 \r\nL 785.668231 103.32695 \r\nL 791.34401 94.168368 \r\nL 797.019789 74.324774 \r\nL 802.695568 45.322597 \r\nL 808.371347 41.124914 \r\nL 814.047125 77.759242 \r\nL 819.722904 99.129266 \r\nL 825.398683 116.301608 \r\nL 831.074462 99.892482 \r\nL 836.75024 95.313191 \r\nL 842.426019 105.234988 \r\nL 848.101798 94.549975 \r\nL 853.777577 78.522457 \r\nL 859.453355 74.324774 \r\nL 865.129134 50.283496 \r\nL 870.804913 17.083636 \r\nL 876.480692 23.189358 \r\nL 882.156471 60.586901 \r\nL 887.832249 78.522457 \r\nL 893.508028 105.616595 \r\nL 899.183807 89.589077 \r\nL 899.183807 89.589077 \r\n\" style=\"fill:none;stroke:#0173b2;stroke-linecap:square;stroke-width:1.5;\"/>\r\n    <defs>\r\n     <path d=\"M 0 3 \r\nC 0.795609 3 1.55874 2.683901 2.12132 2.12132 \r\nC 2.683901 1.55874 3 0.795609 3 0 \r\nC 3 -0.795609 2.683901 -1.55874 2.12132 -2.12132 \r\nC 1.55874 -2.683901 0.795609 -3 0 -3 \r\nC -0.795609 -3 -1.55874 -2.683901 -2.12132 -2.12132 \r\nC -2.683901 -1.55874 -3 -0.795609 -3 0 \r\nC -3 0.795609 -2.683901 1.55874 -2.12132 2.12132 \r\nC -1.55874 2.683901 -0.795609 3 0 3 \r\nz\r\n\" id=\"m897fad72d7\" style=\"stroke:#ffffff;stroke-width:0.75;\"/>\r\n    </defs>\r\n    <g clip-path=\"url(#pa8f17e7db1)\">\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"87.547443\" xlink:href=\"#m897fad72d7\" y=\"211.703503\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"93.223222\" xlink:href=\"#m897fad72d7\" y=\"209.413857\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"98.899001\" xlink:href=\"#m897fad72d7\" y=\"204.071351\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"104.574779\" xlink:href=\"#m897fad72d7\" y=\"205.216174\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"110.250558\" xlink:href=\"#m897fad72d7\" y=\"208.269035\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"115.926337\" xlink:href=\"#m897fad72d7\" y=\"202.926529\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"121.602116\" xlink:href=\"#m897fad72d7\" y=\"197.96563\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"127.277895\" xlink:href=\"#m897fad72d7\" y=\"197.96563\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"132.953673\" xlink:href=\"#m897fad72d7\" y=\"202.544921\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"138.629452\" xlink:href=\"#m897fad72d7\" y=\"209.03225\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"144.305231\" xlink:href=\"#m897fad72d7\" y=\"214.756364\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"149.98101\" xlink:href=\"#m897fad72d7\" y=\"209.413857\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"155.656788\" xlink:href=\"#m897fad72d7\" y=\"210.55868\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"161.332567\" xlink:href=\"#m897fad72d7\" y=\"206.360997\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"167.008346\" xlink:href=\"#m897fad72d7\" y=\"200.636883\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"172.684125\" xlink:href=\"#m897fad72d7\" y=\"202.926529\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"178.359903\" xlink:href=\"#m897fad72d7\" y=\"206.742604\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"184.035682\" xlink:href=\"#m897fad72d7\" y=\"197.584022\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"189.711461\" xlink:href=\"#m897fad72d7\" y=\"189.570263\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"195.38724\" xlink:href=\"#m897fad72d7\" y=\"189.570263\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"201.063019\" xlink:href=\"#m897fad72d7\" y=\"194.149554\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"206.738797\" xlink:href=\"#m897fad72d7\" y=\"203.689744\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"212.414576\" xlink:href=\"#m897fad72d7\" y=\"210.940288\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"218.090355\" xlink:href=\"#m897fad72d7\" y=\"201.018491\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"223.766134\" xlink:href=\"#m897fad72d7\" y=\"199.110453\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"229.441912\" xlink:href=\"#m897fad72d7\" y=\"197.202415\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"235.117691\" xlink:href=\"#m897fad72d7\" y=\"186.517403\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"240.79347\" xlink:href=\"#m897fad72d7\" y=\"192.241516\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"246.469249\" xlink:href=\"#m897fad72d7\" y=\"188.807048\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"252.145027\" xlink:href=\"#m897fad72d7\" y=\"186.517403\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"257.820806\" xlink:href=\"#m897fad72d7\" y=\"178.503643\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"263.496585\" xlink:href=\"#m897fad72d7\" y=\"178.503643\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"269.172364\" xlink:href=\"#m897fad72d7\" y=\"184.227757\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"274.848142\" xlink:href=\"#m897fad72d7\" y=\"192.623124\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"280.523921\" xlink:href=\"#m897fad72d7\" y=\"198.728845\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"286.1997\" xlink:href=\"#m897fad72d7\" y=\"191.096694\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"291.875479\" xlink:href=\"#m897fad72d7\" y=\"189.188656\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"297.551258\" xlink:href=\"#m897fad72d7\" y=\"185.754187\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"303.227036\" xlink:href=\"#m897fad72d7\" y=\"180.793289\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"308.902815\" xlink:href=\"#m897fad72d7\" y=\"185.37258\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"314.578594\" xlink:href=\"#m897fad72d7\" y=\"184.609365\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"320.254373\" xlink:href=\"#m897fad72d7\" y=\"171.253099\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"325.930151\" xlink:href=\"#m897fad72d7\" y=\"166.673808\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"331.60593\" xlink:href=\"#m897fad72d7\" y=\"162.094517\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"337.281709\" xlink:href=\"#m897fad72d7\" y=\"174.687568\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"342.957488\" xlink:href=\"#m897fad72d7\" y=\"181.556504\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"348.633266\" xlink:href=\"#m897fad72d7\" y=\"188.807048\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"354.309045\" xlink:href=\"#m897fad72d7\" y=\"180.411681\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"359.984824\" xlink:href=\"#m897fad72d7\" y=\"179.648466\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"365.660603\" xlink:href=\"#m897fad72d7\" y=\"179.648466\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"371.336382\" xlink:href=\"#m897fad72d7\" y=\"164.384163\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"377.01216\" xlink:href=\"#m897fad72d7\" y=\"164.76577\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"382.687939\" xlink:href=\"#m897fad72d7\" y=\"167.055416\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"388.363718\" xlink:href=\"#m897fad72d7\" y=\"161.71291\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"394.039497\" xlink:href=\"#m897fad72d7\" y=\"153.699151\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"399.715275\" xlink:href=\"#m897fad72d7\" y=\"150.64629\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"405.391054\" xlink:href=\"#m897fad72d7\" y=\"164.002555\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"411.066833\" xlink:href=\"#m897fad72d7\" y=\"173.924352\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"416.742612\" xlink:href=\"#m897fad72d7\" y=\"185.754187\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"422.41839\" xlink:href=\"#m897fad72d7\" y=\"177.740428\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"428.094169\" xlink:href=\"#m897fad72d7\" y=\"176.595605\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"433.769948\" xlink:href=\"#m897fad72d7\" y=\"182.701327\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"439.445727\" xlink:href=\"#m897fad72d7\" y=\"164.76577\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"445.121505\" xlink:href=\"#m897fad72d7\" y=\"167.818631\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"450.797284\" xlink:href=\"#m897fad72d7\" y=\"165.147378\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"456.473063\" xlink:href=\"#m897fad72d7\" y=\"153.699151\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"462.148842\" xlink:href=\"#m897fad72d7\" y=\"139.198062\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"467.824621\" xlink:href=\"#m897fad72d7\" y=\"142.632531\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"473.500399\" xlink:href=\"#m897fad72d7\" y=\"155.607188\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"479.176178\" xlink:href=\"#m897fad72d7\" y=\"167.055416\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"484.851957\" xlink:href=\"#m897fad72d7\" y=\"176.977213\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"490.527736\" xlink:href=\"#m897fad72d7\" y=\"167.055416\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"496.203514\" xlink:href=\"#m897fad72d7\" y=\"162.094517\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"501.879293\" xlink:href=\"#m897fad72d7\" y=\"165.528986\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"507.555072\" xlink:href=\"#m897fad72d7\" y=\"152.554328\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"513.230851\" xlink:href=\"#m897fad72d7\" y=\"151.791113\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"518.906629\" xlink:href=\"#m897fad72d7\" y=\"151.409505\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"524.582408\" xlink:href=\"#m897fad72d7\" y=\"134.237164\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"530.258187\" xlink:href=\"#m897fad72d7\" y=\"115.538392\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"535.933966\" xlink:href=\"#m897fad72d7\" y=\"122.025721\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"541.609745\" xlink:href=\"#m897fad72d7\" y=\"135.381987\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"547.285523\" xlink:href=\"#m897fad72d7\" y=\"149.883075\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"552.961302\" xlink:href=\"#m897fad72d7\" y=\"164.002555\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"558.637081\" xlink:href=\"#m897fad72d7\" y=\"148.356644\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"564.31286\" xlink:href=\"#m897fad72d7\" y=\"146.066999\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"569.988638\" xlink:href=\"#m897fad72d7\" y=\"148.738252\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"575.664417\" xlink:href=\"#m897fad72d7\" y=\"133.473949\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"581.340196\" xlink:href=\"#m897fad72d7\" y=\"135.000379\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"587.015975\" xlink:href=\"#m897fad72d7\" y=\"133.092341\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"592.691753\" xlink:href=\"#m897fad72d7\" y=\"111.722317\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"598.367532\" xlink:href=\"#m897fad72d7\" y=\"96.839621\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"604.043311\" xlink:href=\"#m897fad72d7\" y=\"99.892482\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"609.71909\" xlink:href=\"#m897fad72d7\" y=\"118.972861\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"615.394868\" xlink:href=\"#m897fad72d7\" y=\"137.671632\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"621.070647\" xlink:href=\"#m897fad72d7\" y=\"151.027898\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"626.746426\" xlink:href=\"#m897fad72d7\" y=\"137.671632\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"632.422205\" xlink:href=\"#m897fad72d7\" y=\"134.237164\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"638.097984\" xlink:href=\"#m897fad72d7\" y=\"139.57967\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"643.773762\" xlink:href=\"#m897fad72d7\" y=\"118.591253\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"649.449541\" xlink:href=\"#m897fad72d7\" y=\"121.644114\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"655.12532\" xlink:href=\"#m897fad72d7\" y=\"118.972861\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"660.801099\" xlink:href=\"#m897fad72d7\" y=\"93.405153\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"666.476877\" xlink:href=\"#m897fad72d7\" y=\"76.996027\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"672.152656\" xlink:href=\"#m897fad72d7\" y=\"76.232812\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"677.828435\" xlink:href=\"#m897fad72d7\" y=\"100.274089\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"683.504214\" xlink:href=\"#m897fad72d7\" y=\"122.025721\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"689.179992\" xlink:href=\"#m897fad72d7\" y=\"138.05324\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"694.855771\" xlink:href=\"#m897fad72d7\" y=\"126.223405\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"700.53155\" xlink:href=\"#m897fad72d7\" y=\"124.696974\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"706.207329\" xlink:href=\"#m897fad72d7\" y=\"133.092341\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"711.883108\" xlink:href=\"#m897fad72d7\" y=\"116.301608\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"717.558886\" xlink:href=\"#m897fad72d7\" y=\"121.644114\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"723.234665\" xlink:href=\"#m897fad72d7\" y=\"115.92\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"728.910444\" xlink:href=\"#m897fad72d7\" y=\"88.444254\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"734.586223\" xlink:href=\"#m897fad72d7\" y=\"67.07423\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"740.262001\" xlink:href=\"#m897fad72d7\" y=\"61.731723\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"745.93778\" xlink:href=\"#m897fad72d7\" y=\"100.274089\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"751.613559\" xlink:href=\"#m897fad72d7\" y=\"117.44643\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"757.289338\" xlink:href=\"#m897fad72d7\" y=\"136.145202\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"762.965116\" xlink:href=\"#m897fad72d7\" y=\"125.841797\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"768.640895\" xlink:href=\"#m897fad72d7\" y=\"117.064823\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"774.316674\" xlink:href=\"#m897fad72d7\" y=\"123.933759\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"779.992453\" xlink:href=\"#m897fad72d7\" y=\"99.510874\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"785.668231\" xlink:href=\"#m897fad72d7\" y=\"103.32695\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"791.34401\" xlink:href=\"#m897fad72d7\" y=\"94.168368\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"797.019789\" xlink:href=\"#m897fad72d7\" y=\"74.324774\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"802.695568\" xlink:href=\"#m897fad72d7\" y=\"45.322597\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"808.371347\" xlink:href=\"#m897fad72d7\" y=\"41.124914\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"814.047125\" xlink:href=\"#m897fad72d7\" y=\"77.759242\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"819.722904\" xlink:href=\"#m897fad72d7\" y=\"99.129266\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"825.398683\" xlink:href=\"#m897fad72d7\" y=\"116.301608\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"831.074462\" xlink:href=\"#m897fad72d7\" y=\"99.892482\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"836.75024\" xlink:href=\"#m897fad72d7\" y=\"95.313191\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"842.426019\" xlink:href=\"#m897fad72d7\" y=\"105.234988\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"848.101798\" xlink:href=\"#m897fad72d7\" y=\"94.549975\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"853.777577\" xlink:href=\"#m897fad72d7\" y=\"78.522457\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"859.453355\" xlink:href=\"#m897fad72d7\" y=\"74.324774\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"865.129134\" xlink:href=\"#m897fad72d7\" y=\"50.283496\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"870.804913\" xlink:href=\"#m897fad72d7\" y=\"17.083636\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"876.480692\" xlink:href=\"#m897fad72d7\" y=\"23.189358\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"882.156471\" xlink:href=\"#m897fad72d7\" y=\"60.586901\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"887.832249\" xlink:href=\"#m897fad72d7\" y=\"78.522457\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"893.508028\" xlink:href=\"#m897fad72d7\" y=\"105.616595\"/>\r\n     <use style=\"fill:#0173b2;stroke:#ffffff;stroke-width:0.75;\" x=\"899.183807\" xlink:href=\"#m897fad72d7\" y=\"89.589077\"/>\r\n    </g>\r\n   </g>\r\n   <g id=\"patch_3\">\r\n    <path d=\"M 46.965625 224.64 \r\nL 46.965625 7.2 \r\n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\r\n   </g>\r\n   <g id=\"patch_4\">\r\n    <path d=\"M 939.765625 224.64 \r\nL 939.765625 7.2 \r\n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\r\n   </g>\r\n   <g id=\"patch_5\">\r\n    <path d=\"M 46.965625 224.64 \r\nL 939.765625 224.64 \r\n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\r\n   </g>\r\n   <g id=\"patch_6\">\r\n    <path d=\"M 46.965625 7.2 \r\nL 939.765625 7.2 \r\n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\r\n   </g>\r\n  </g>\r\n </g>\r\n <defs>\r\n  <clipPath id=\"pa8f17e7db1\">\r\n   <rect height=\"217.44\" width=\"892.8\" x=\"46.965625\" y=\"7.2\"/>\r\n  </clipPath>\r\n </defs>\r\n</svg>\r\n",
-      "image/png": "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\n"
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1152x288 with 1 Axes>"
+      ]
      },
      "metadata": {
       "needs_background": "light"
-     }
+     },
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -65,8 +66,90 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "execute_result",
      "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Reference</th>\n",
+       "      <th>Turbo</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ID</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>naive</th>\n",
+       "      <td>Naive</td>\n",
+       "      <td>sktime.forecasting.naive.NaiveForecaster</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>poly_trend</th>\n",
+       "      <td>PolyTrend</td>\n",
+       "      <td>sktime.forecasting.trend.PolynomialTrendForeca...</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>arima</th>\n",
+       "      <td>ARIMA</td>\n",
+       "      <td>sktime.forecasting.arima.ARIMA</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>exp_smooth</th>\n",
+       "      <td>ExponentialSmoothing</td>\n",
+       "      <td>sktime.forecasting.exp_smoothing.ExponentialSm...</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>auto_ets</th>\n",
+       "      <td>AutoETS</td>\n",
+       "      <td>sktime.forecasting.ets.AutoETS</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>theta</th>\n",
+       "      <td>Theta</td>\n",
+       "      <td>sktime.forecasting.theta.ThetaForecaster</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>rf_dts</th>\n",
+       "      <td>RandomForestDTS</td>\n",
+       "      <td>pycaret.containers.models.time_series.RandomFo...</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ensemble_forecaster</th>\n",
+       "      <td>EnsembleForecaster</td>\n",
+       "      <td>pycaret.internal.ensemble._EnsembleForecasterW...</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
       "text/plain": [
        "                                     Name  \\\n",
        "ID                                          \n",
@@ -89,11 +172,11 @@
        "theta                         sktime.forecasting.theta.ThetaForecaster   True  \n",
        "rf_dts               pycaret.containers.models.time_series.RandomFo...   True  \n",
        "ensemble_forecaster  pycaret.internal.ensemble._EnsembleForecasterW...   True  "
-      ],
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Name</th>\n      <th>Reference</th>\n      <th>Turbo</th>\n    </tr>\n    <tr>\n      <th>ID</th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>naive</th>\n      <td>Naive</td>\n      <td>sktime.forecasting.naive.NaiveForecaster</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>poly_trend</th>\n      <td>PolyTrend</td>\n      <td>sktime.forecasting.trend.PolynomialTrendForeca...</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>arima</th>\n      <td>ARIMA</td>\n      <td>sktime.forecasting.arima.ARIMA</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>exp_smooth</th>\n      <td>ExponentialSmoothing</td>\n      <td>sktime.forecasting.exp_smoothing.ExponentialSm...</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>auto_ets</th>\n      <td>AutoETS</td>\n      <td>sktime.forecasting.ets.AutoETS</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>theta</th>\n      <td>Theta</td>\n      <td>sktime.forecasting.theta.ThetaForecaster</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>rf_dts</th>\n      <td>RandomForestDTS</td>\n      <td>pycaret.containers.models.time_series.RandomFo...</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <th>ensemble_forecaster</th>\n      <td>EnsembleForecaster</td>\n      <td>pycaret.internal.ensemble._EnsembleForecasterW...</td>\n      <td>True</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
+      ]
      },
+     "execution_count": 4,
      "metadata": {},
-     "execution_count": 4
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -115,12 +198,55 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb8ece088>",
-      "text/html": "<style  type=\"text/css\" >\n#T_b971e_row3_col0,#T_b971e_row3_col1,#T_b971e_row3_col2,#T_b971e_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_b971e_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_b971e_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_b971e_row0_col0\" class=\"data row0 col0\" >0.2544</td>\n                        <td id=\"T_b971e_row0_col1\" class=\"data row0 col1\" >0.2172</td>\n                        <td id=\"T_b971e_row0_col2\" class=\"data row0 col2\" >86.4672</td>\n                        <td id=\"T_b971e_row0_col3\" class=\"data row0 col3\" >10986.2059</td>\n            </tr>\n            <tr>\n                        <th id=\"T_b971e_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_b971e_row1_col0\" class=\"data row1 col0\" >0.1969</td>\n                        <td id=\"T_b971e_row1_col1\" class=\"data row1 col1\" >0.1705</td>\n                        <td id=\"T_b971e_row1_col2\" class=\"data row1 col2\" >72.3623</td>\n                        <td id=\"T_b971e_row1_col3\" class=\"data row1 col3\" >9262.3183</td>\n            </tr>\n            <tr>\n                        <th id=\"T_b971e_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_b971e_row2_col0\" class=\"data row2 col0\" >0.2978</td>\n                        <td id=\"T_b971e_row2_col1\" class=\"data row2 col1\" >0.2508</td>\n                        <td id=\"T_b971e_row2_col2\" class=\"data row2 col2\" >115.1556</td>\n                        <td id=\"T_b971e_row2_col3\" class=\"data row2 col3\" >18344.7882</td>\n            </tr>\n            <tr>\n                        <th id=\"T_b971e_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_b971e_row3_col0\" class=\"data row3 col0\" >0.2497</td>\n                        <td id=\"T_b971e_row3_col1\" class=\"data row3 col1\" >0.2128</td>\n                        <td id=\"T_b971e_row3_col2\" class=\"data row3 col2\" >91.3284</td>\n                        <td id=\"T_b971e_row3_col3\" class=\"data row3 col3\" >12864.4375</td>\n            </tr>\n            <tr>\n                        <th id=\"T_b971e_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_b971e_row4_col0\" class=\"data row4 col0\" >0.0413</td>\n                        <td id=\"T_b971e_row4_col1\" class=\"data row4 col1\" >0.0329</td>\n                        <td id=\"T_b971e_row4_col2\" class=\"data row4 col2\" >17.8053</td>\n                        <td id=\"T_b971e_row4_col3\" class=\"data row4 col3\" >3938.5810</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_5fbe6_row3_col0,#T_5fbe6_row3_col1,#T_5fbe6_row3_col2,#T_5fbe6_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_5fbe6_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_5fbe6_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_5fbe6_row0_col0\" class=\"data row0 col0\" >0.2544</td>\n",
+       "                        <td id=\"T_5fbe6_row0_col1\" class=\"data row0 col1\" >0.2172</td>\n",
+       "                        <td id=\"T_5fbe6_row0_col2\" class=\"data row0 col2\" >86.4672</td>\n",
+       "                        <td id=\"T_5fbe6_row0_col3\" class=\"data row0 col3\" >10986.2059</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_5fbe6_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_5fbe6_row1_col0\" class=\"data row1 col0\" >0.1969</td>\n",
+       "                        <td id=\"T_5fbe6_row1_col1\" class=\"data row1 col1\" >0.1705</td>\n",
+       "                        <td id=\"T_5fbe6_row1_col2\" class=\"data row1 col2\" >72.3623</td>\n",
+       "                        <td id=\"T_5fbe6_row1_col3\" class=\"data row1 col3\" >9262.3184</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_5fbe6_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_5fbe6_row2_col0\" class=\"data row2 col0\" >0.2978</td>\n",
+       "                        <td id=\"T_5fbe6_row2_col1\" class=\"data row2 col1\" >0.2508</td>\n",
+       "                        <td id=\"T_5fbe6_row2_col2\" class=\"data row2 col2\" >115.1556</td>\n",
+       "                        <td id=\"T_5fbe6_row2_col3\" class=\"data row2 col3\" >18344.7882</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_5fbe6_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_5fbe6_row3_col0\" class=\"data row3 col0\" >0.2497</td>\n",
+       "                        <td id=\"T_5fbe6_row3_col1\" class=\"data row3 col1\" >0.2128</td>\n",
+       "                        <td id=\"T_5fbe6_row3_col2\" class=\"data row3 col2\" >91.3284</td>\n",
+       "                        <td id=\"T_5fbe6_row3_col3\" class=\"data row3 col3\" >12864.4375</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_5fbe6_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_5fbe6_row4_col0\" class=\"data row4 col0\" >0.0413</td>\n",
+       "                        <td id=\"T_5fbe6_row4_col1\" class=\"data row4 col1\" >0.0329</td>\n",
+       "                        <td id=\"T_5fbe6_row4_col2\" class=\"data row4 col2\" >17.8053</td>\n",
+       "                        <td id=\"T_5fbe6_row4_col3\" class=\"data row4 col3\" >3938.5809</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a36ea450>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -135,7 +261,6 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
        "1960-01    399.517880\n",
@@ -153,8 +278,9 @@
        "Freq: M, dtype: float64"
       ]
      },
+     "execution_count": 6,
      "metadata": {},
-     "execution_count": 6
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -175,12 +301,55 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb8ec8ac8>",
-      "text/html": "<style  type=\"text/css\" >\n#T_09d10_row3_col0,#T_09d10_row3_col1,#T_09d10_row3_col2,#T_09d10_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_09d10_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_09d10_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_09d10_row0_col0\" class=\"data row0 col0\" >0.2544</td>\n                        <td id=\"T_09d10_row0_col1\" class=\"data row0 col1\" >0.2172</td>\n                        <td id=\"T_09d10_row0_col2\" class=\"data row0 col2\" >86.4672</td>\n                        <td id=\"T_09d10_row0_col3\" class=\"data row0 col3\" >10986.2059</td>\n            </tr>\n            <tr>\n                        <th id=\"T_09d10_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_09d10_row1_col0\" class=\"data row1 col0\" >0.1931</td>\n                        <td id=\"T_09d10_row1_col1\" class=\"data row1 col1\" >0.1675</td>\n                        <td id=\"T_09d10_row1_col2\" class=\"data row1 col2\" >71.1742</td>\n                        <td id=\"T_09d10_row1_col3\" class=\"data row1 col3\" >9049.5816</td>\n            </tr>\n            <tr>\n                        <th id=\"T_09d10_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_09d10_row2_col0\" class=\"data row2 col0\" >0.2962</td>\n                        <td id=\"T_09d10_row2_col1\" class=\"data row2 col1\" >0.2496</td>\n                        <td id=\"T_09d10_row2_col2\" class=\"data row2 col2\" >114.6292</td>\n                        <td id=\"T_09d10_row2_col3\" class=\"data row2 col3\" >18211.8564</td>\n            </tr>\n            <tr>\n                        <th id=\"T_09d10_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_09d10_row3_col0\" class=\"data row3 col0\" >0.2479</td>\n                        <td id=\"T_09d10_row3_col1\" class=\"data row3 col1\" >0.2114</td>\n                        <td id=\"T_09d10_row3_col2\" class=\"data row3 col2\" >90.7569</td>\n                        <td id=\"T_09d10_row3_col3\" class=\"data row3 col3\" >12749.2146</td>\n            </tr>\n            <tr>\n                        <th id=\"T_09d10_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_09d10_row4_col0\" class=\"data row4 col0\" >0.0424</td>\n                        <td id=\"T_09d10_row4_col1\" class=\"data row4 col1\" >0.0338</td>\n                        <td id=\"T_09d10_row4_col2\" class=\"data row4 col2\" >17.9979</td>\n                        <td id=\"T_09d10_row4_col3\" class=\"data row4 col3\" >3942.7545</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_6baf0_row3_col0,#T_6baf0_row3_col1,#T_6baf0_row3_col2,#T_6baf0_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_6baf0_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_6baf0_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_6baf0_row0_col0\" class=\"data row0 col0\" >0.2544</td>\n",
+       "                        <td id=\"T_6baf0_row0_col1\" class=\"data row0 col1\" >0.2172</td>\n",
+       "                        <td id=\"T_6baf0_row0_col2\" class=\"data row0 col2\" >86.4672</td>\n",
+       "                        <td id=\"T_6baf0_row0_col3\" class=\"data row0 col3\" >10986.2059</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_6baf0_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_6baf0_row1_col0\" class=\"data row1 col0\" >0.1931</td>\n",
+       "                        <td id=\"T_6baf0_row1_col1\" class=\"data row1 col1\" >0.1675</td>\n",
+       "                        <td id=\"T_6baf0_row1_col2\" class=\"data row1 col2\" >71.1742</td>\n",
+       "                        <td id=\"T_6baf0_row1_col3\" class=\"data row1 col3\" >9049.5815</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_6baf0_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_6baf0_row2_col0\" class=\"data row2 col0\" >0.2962</td>\n",
+       "                        <td id=\"T_6baf0_row2_col1\" class=\"data row2 col1\" >0.2496</td>\n",
+       "                        <td id=\"T_6baf0_row2_col2\" class=\"data row2 col2\" >114.6292</td>\n",
+       "                        <td id=\"T_6baf0_row2_col3\" class=\"data row2 col3\" >18211.8563</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_6baf0_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_6baf0_row3_col0\" class=\"data row3 col0\" >0.2479</td>\n",
+       "                        <td id=\"T_6baf0_row3_col1\" class=\"data row3 col1\" >0.2114</td>\n",
+       "                        <td id=\"T_6baf0_row3_col2\" class=\"data row3 col2\" >90.7569</td>\n",
+       "                        <td id=\"T_6baf0_row3_col3\" class=\"data row3 col3\" >12749.2146</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_6baf0_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_6baf0_row4_col0\" class=\"data row4 col0\" >0.0424</td>\n",
+       "                        <td id=\"T_6baf0_row4_col1\" class=\"data row4 col1\" >0.0338</td>\n",
+       "                        <td id=\"T_6baf0_row4_col2\" class=\"data row4 col2\" >17.9979</td>\n",
+       "                        <td id=\"T_6baf0_row4_col3\" class=\"data row4 col3\" >3942.7545</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe200f5d450>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -195,7 +364,6 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
        "1960-01    399.517880\n",
@@ -213,8 +381,9 @@
        "Freq: M, dtype: float64"
       ]
      },
+     "execution_count": 8,
      "metadata": {},
-     "execution_count": 8
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -234,28 +403,83 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "IntProgress(value=0, description='Processing: ', max=3)",
       "application/vnd.jupyter.widget-view+json": {
+       "model_id": "fa408e805a8d4bcd9b364b99b192338a",
        "version_major": 2,
-       "version_minor": 0,
-       "model_id": "7d05872e1878458e944e8e3c710383c0"
-      }
+       "version_minor": 0
+      },
+      "text/plain": [
+       "IntProgress(value=0, description='Processing: ', max=3)"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "                                                                  \n                                                                  \nInitiated  . . . . . . . . . . . . . . . . . .            10:53:09\nStatus     . . . . . . . . . . . . . . . . . .    Finalizing Model\nEstimator  . . . . . . . . . . . . . . . . . .  EnsembleForecaster",
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n    <tr>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>Initiated</th>\n      <td>. . . . . . . . . . . . . . . . . .</td>\n      <td>10:53:09</td>\n    </tr>\n    <tr>\n      <th>Status</th>\n      <td>. . . . . . . . . . . . . . . . . .</td>\n      <td>Finalizing Model</td>\n    </tr>\n    <tr>\n      <th>Estimator</th>\n      <td>. . . . . . . . . . . . . . . . . .</td>\n      <td>EnsembleForecaster</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Initiated</th>\n",
+       "      <td>. . . . . . . . . . . . . . . . . .</td>\n",
+       "      <td>13:50:44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Status</th>\n",
+       "      <td>. . . . . . . . . . . . . . . . . .</td>\n",
+       "      <td>Compiling Final Models</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Estimator</th>\n",
+       "      <td>. . . . . . . . . . . . . . . . . .</td>\n",
+       "      <td>PolyTrend</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                                      \n",
+       "                                                                      \n",
+       "Initiated  . . . . . . . . . . . . . . . . . .                13:50:44\n",
+       "Status     . . . . . . . . . . . . . . . . . .  Compiling Final Models\n",
+       "Estimator  . . . . . . . . . . . . . . . . . .               PolyTrend"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
       "Not Enough Data Points, set a lower number of folds or fh\n"
      ]
@@ -284,22 +508,93 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbbb0f24c8>",
-      "text/html": "<style  type=\"text/css\" >\n</style><table id=\"T_87b21_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Description</th>        <th class=\"col_heading level0 col1\" >Value</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_87b21_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_87b21_row0_col0\" class=\"data row0 col0\" >session_id</td>\n                        <td id=\"T_87b21_row0_col1\" class=\"data row0 col1\" >42</td>\n            </tr>\n            <tr>\n                        <th id=\"T_87b21_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_87b21_row1_col0\" class=\"data row1 col0\" >Original Data</td>\n                        <td id=\"T_87b21_row1_col1\" class=\"data row1 col1\" >(144, 1)</td>\n            </tr>\n            <tr>\n                        <th id=\"T_87b21_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_87b21_row2_col0\" class=\"data row2 col0\" >Missing Values</td>\n                        <td id=\"T_87b21_row2_col1\" class=\"data row2 col1\" >False</td>\n            </tr>\n            <tr>\n                        <th id=\"T_87b21_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n                        <td id=\"T_87b21_row3_col0\" class=\"data row3 col0\" >Transformed Train Set</td>\n                        <td id=\"T_87b21_row3_col1\" class=\"data row3 col1\" >(132,)</td>\n            </tr>\n            <tr>\n                        <th id=\"T_87b21_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n                        <td id=\"T_87b21_row4_col0\" class=\"data row4 col0\" >Transformed Test Set</td>\n                        <td id=\"T_87b21_row4_col1\" class=\"data row4 col1\" >(12,)</td>\n            </tr>\n            <tr>\n                        <th id=\"T_87b21_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n                        <td id=\"T_87b21_row5_col0\" class=\"data row5 col0\" >Fold Generator</td>\n                        <td id=\"T_87b21_row5_col1\" class=\"data row5 col1\" >ExpandingWindowSplitter</td>\n            </tr>\n            <tr>\n                        <th id=\"T_87b21_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n                        <td id=\"T_87b21_row6_col0\" class=\"data row6 col0\" >Fold Number</td>\n                        <td id=\"T_87b21_row6_col1\" class=\"data row6 col1\" >3</td>\n            </tr>\n            <tr>\n                        <th id=\"T_87b21_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n                        <td id=\"T_87b21_row7_col0\" class=\"data row7 col0\" >CPU Jobs</td>\n                        <td id=\"T_87b21_row7_col1\" class=\"data row7 col1\" >-1</td>\n            </tr>\n            <tr>\n                        <th id=\"T_87b21_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n                        <td id=\"T_87b21_row8_col0\" class=\"data row8 col0\" >Use GPU</td>\n                        <td id=\"T_87b21_row8_col1\" class=\"data row8 col1\" >False</td>\n            </tr>\n            <tr>\n                        <th id=\"T_87b21_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n                        <td id=\"T_87b21_row9_col0\" class=\"data row9 col0\" >Log Experiment</td>\n                        <td id=\"T_87b21_row9_col1\" class=\"data row9 col1\" >False</td>\n            </tr>\n            <tr>\n                        <th id=\"T_87b21_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n                        <td id=\"T_87b21_row10_col0\" class=\"data row10 col0\" >Experiment Name</td>\n                        <td id=\"T_87b21_row10_col1\" class=\"data row10 col1\" >no_logging</td>\n            </tr>\n            <tr>\n                        <th id=\"T_87b21_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n                        <td id=\"T_87b21_row11_col0\" class=\"data row11 col0\" >USI</td>\n                        <td id=\"T_87b21_row11_col1\" class=\"data row11 col1\" >26fb</td>\n            </tr>\n            <tr>\n                        <th id=\"T_87b21_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n                        <td id=\"T_87b21_row12_col0\" class=\"data row12 col0\" >Imputation Type</td>\n                        <td id=\"T_87b21_row12_col1\" class=\"data row12 col1\" >simple</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "</style><table id=\"T_d207a_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Description</th>        <th class=\"col_heading level0 col1\" >Value</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_d207a_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_d207a_row0_col0\" class=\"data row0 col0\" >session_id</td>\n",
+       "                        <td id=\"T_d207a_row0_col1\" class=\"data row0 col1\" >42</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d207a_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_d207a_row1_col0\" class=\"data row1 col0\" >Original Data</td>\n",
+       "                        <td id=\"T_d207a_row1_col1\" class=\"data row1 col1\" >(144, 1)</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d207a_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_d207a_row2_col0\" class=\"data row2 col0\" >Missing Values</td>\n",
+       "                        <td id=\"T_d207a_row2_col1\" class=\"data row2 col1\" >False</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d207a_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
+       "                        <td id=\"T_d207a_row3_col0\" class=\"data row3 col0\" >Transformed Train Set</td>\n",
+       "                        <td id=\"T_d207a_row3_col1\" class=\"data row3 col1\" >(132,)</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d207a_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
+       "                        <td id=\"T_d207a_row4_col0\" class=\"data row4 col0\" >Transformed Test Set</td>\n",
+       "                        <td id=\"T_d207a_row4_col1\" class=\"data row4 col1\" >(12,)</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d207a_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
+       "                        <td id=\"T_d207a_row5_col0\" class=\"data row5 col0\" >Fold Generator</td>\n",
+       "                        <td id=\"T_d207a_row5_col1\" class=\"data row5 col1\" >ExpandingWindowSplitter</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d207a_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
+       "                        <td id=\"T_d207a_row6_col0\" class=\"data row6 col0\" >Fold Number</td>\n",
+       "                        <td id=\"T_d207a_row6_col1\" class=\"data row6 col1\" >3</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d207a_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
+       "                        <td id=\"T_d207a_row7_col0\" class=\"data row7 col0\" >CPU Jobs</td>\n",
+       "                        <td id=\"T_d207a_row7_col1\" class=\"data row7 col1\" >-1</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d207a_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
+       "                        <td id=\"T_d207a_row8_col0\" class=\"data row8 col0\" >Use GPU</td>\n",
+       "                        <td id=\"T_d207a_row8_col1\" class=\"data row8 col1\" >False</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d207a_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
+       "                        <td id=\"T_d207a_row9_col0\" class=\"data row9 col0\" >Log Experiment</td>\n",
+       "                        <td id=\"T_d207a_row9_col1\" class=\"data row9 col1\" >False</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d207a_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
+       "                        <td id=\"T_d207a_row10_col0\" class=\"data row10 col0\" >Experiment Name</td>\n",
+       "                        <td id=\"T_d207a_row10_col1\" class=\"data row10 col1\" >no_logging</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d207a_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
+       "                        <td id=\"T_d207a_row11_col0\" class=\"data row11 col0\" >USI</td>\n",
+       "                        <td id=\"T_d207a_row11_col1\" class=\"data row11 col1\" >34cf</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d207a_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
+       "                        <td id=\"T_d207a_row12_col0\" class=\"data row12 col0\" >Imputation Type</td>\n",
+       "                        <td id=\"T_d207a_row12_col1\" class=\"data row12 col1\" >simple</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a3590490>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
-       "<pycaret.internal.PycaretExperiment.TimeSeriesExperiment at 0x1cbb8f46e88>"
+       "<pycaret.internal.PycaretExperiment.TimeSeriesExperiment at 0x7fe1a37085d0>"
       ]
      },
+     "execution_count": 10,
      "metadata": {},
-     "execution_count": 10
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -320,15 +615,57 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb90cd448>",
-      "text/html": "<style  type=\"text/css\" >\n#T_4537d_row3_col0,#T_4537d_row3_col1,#T_4537d_row3_col2,#T_4537d_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_4537d_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_4537d_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_4537d_row0_col0\" class=\"data row0 col0\" >0.1766</td>\n                        <td id=\"T_4537d_row0_col1\" class=\"data row0 col1\" >0.1549</td>\n                        <td id=\"T_4537d_row0_col2\" class=\"data row0 col2\" >63.4167</td>\n                        <td id=\"T_4537d_row0_col3\" class=\"data row0 col3\" >6967.9167</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4537d_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_4537d_row1_col0\" class=\"data row1 col0\" >0.1351</td>\n                        <td id=\"T_4537d_row1_col1\" class=\"data row1 col1\" >0.1205</td>\n                        <td id=\"T_4537d_row1_col2\" class=\"data row1 col2\" >52.3333</td>\n                        <td id=\"T_4537d_row1_col3\" class=\"data row1 col3\" >5842.1667</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4537d_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_4537d_row2_col0\" class=\"data row2 col0\" >0.2259</td>\n                        <td id=\"T_4537d_row2_col1\" class=\"data row2 col1\" >0.1954</td>\n                        <td id=\"T_4537d_row2_col2\" class=\"data row2 col2\" >91.3333</td>\n                        <td id=\"T_4537d_row2_col3\" class=\"data row2 col3\" >12811.6667</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4537d_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_4537d_row3_col0\" class=\"data row3 col0\" >0.1792</td>\n                        <td id=\"T_4537d_row3_col1\" class=\"data row3 col1\" >0.1569</td>\n                        <td id=\"T_4537d_row3_col2\" class=\"data row3 col2\" >69.0278</td>\n                        <td id=\"T_4537d_row3_col3\" class=\"data row3 col3\" >8540.5833</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4537d_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_4537d_row4_col0\" class=\"data row4 col0\" >0.0371</td>\n                        <td id=\"T_4537d_row4_col1\" class=\"data row4 col1\" >0.0306</td>\n                        <td id=\"T_4537d_row4_col2\" class=\"data row4 col2\" >16.4086</td>\n                        <td id=\"T_4537d_row4_col3\" class=\"data row4 col3\" >3054.8806</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_063b6_row3_col0,#T_063b6_row3_col1,#T_063b6_row3_col2,#T_063b6_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_063b6_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_063b6_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_063b6_row0_col0\" class=\"data row0 col0\" >0.1766</td>\n",
+       "                        <td id=\"T_063b6_row0_col1\" class=\"data row0 col1\" >0.1549</td>\n",
+       "                        <td id=\"T_063b6_row0_col2\" class=\"data row0 col2\" >63.4167</td>\n",
+       "                        <td id=\"T_063b6_row0_col3\" class=\"data row0 col3\" >6967.9167</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_063b6_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_063b6_row1_col0\" class=\"data row1 col0\" >0.1351</td>\n",
+       "                        <td id=\"T_063b6_row1_col1\" class=\"data row1 col1\" >0.1205</td>\n",
+       "                        <td id=\"T_063b6_row1_col2\" class=\"data row1 col2\" >52.3333</td>\n",
+       "                        <td id=\"T_063b6_row1_col3\" class=\"data row1 col3\" >5842.1667</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_063b6_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_063b6_row2_col0\" class=\"data row2 col0\" >0.2259</td>\n",
+       "                        <td id=\"T_063b6_row2_col1\" class=\"data row2 col1\" >0.1954</td>\n",
+       "                        <td id=\"T_063b6_row2_col2\" class=\"data row2 col2\" >91.3333</td>\n",
+       "                        <td id=\"T_063b6_row2_col3\" class=\"data row2 col3\" >12811.6667</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_063b6_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_063b6_row3_col0\" class=\"data row3 col0\" >0.1792</td>\n",
+       "                        <td id=\"T_063b6_row3_col1\" class=\"data row3 col1\" >0.1569</td>\n",
+       "                        <td id=\"T_063b6_row3_col2\" class=\"data row3 col2\" >69.0278</td>\n",
+       "                        <td id=\"T_063b6_row3_col3\" class=\"data row3 col3\" >8540.5833</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_063b6_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_063b6_row4_col0\" class=\"data row4 col0\" >0.0371</td>\n",
+       "                        <td id=\"T_063b6_row4_col1\" class=\"data row4 col1\" >0.0306</td>\n",
+       "                        <td id=\"T_063b6_row4_col2\" class=\"data row4 col2\" >16.4086</td>\n",
+       "                        <td id=\"T_063b6_row4_col3\" class=\"data row4 col3\" >3054.8806</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a371fd90>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
        "1960-01    405.0\n",
@@ -346,8 +683,9 @@
        "Freq: M, dtype: float64"
       ]
      },
+     "execution_count": 11,
      "metadata": {},
-     "execution_count": 11
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -361,18 +699,62 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb8fb0d48>",
-      "text/html": "<style  type=\"text/css\" >\n#T_4ebf4_row3_col0,#T_4ebf4_row3_col1,#T_4ebf4_row3_col2,#T_4ebf4_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_4ebf4_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_4ebf4_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_4ebf4_row0_col0\" class=\"data row0 col0\" >0.1138</td>\n                        <td id=\"T_4ebf4_row0_col1\" class=\"data row0 col1\" >0.1076</td>\n                        <td id=\"T_4ebf4_row0_col2\" class=\"data row0 col2\" >40.1667</td>\n                        <td id=\"T_4ebf4_row0_col3\" class=\"data row0 col3\" >1720.1667</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4ebf4_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_4ebf4_row1_col0\" class=\"data row1 col0\" >0.0322</td>\n                        <td id=\"T_4ebf4_row1_col1\" class=\"data row1 col1\" >0.0314</td>\n                        <td id=\"T_4ebf4_row1_col2\" class=\"data row1 col2\" >12.5833</td>\n                        <td id=\"T_4ebf4_row1_col3\" class=\"data row1 col3\" >289.4167</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4ebf4_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_4ebf4_row2_col0\" class=\"data row2 col0\" >0.1176</td>\n                        <td id=\"T_4ebf4_row2_col1\" class=\"data row2 col1\" >0.1106</td>\n                        <td id=\"T_4ebf4_row2_col2\" class=\"data row2 col2\" >47.3333</td>\n                        <td id=\"T_4ebf4_row2_col3\" class=\"data row2 col3\" >2426.0000</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4ebf4_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_4ebf4_row3_col0\" class=\"data row3 col0\" >0.0879</td>\n                        <td id=\"T_4ebf4_row3_col1\" class=\"data row3 col1\" >0.0832</td>\n                        <td id=\"T_4ebf4_row3_col2\" class=\"data row3 col2\" >33.3611</td>\n                        <td id=\"T_4ebf4_row3_col3\" class=\"data row3 col3\" >1478.5278</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4ebf4_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_4ebf4_row4_col0\" class=\"data row4 col0\" >0.0394</td>\n                        <td id=\"T_4ebf4_row4_col1\" class=\"data row4 col1\" >0.0367</td>\n                        <td id=\"T_4ebf4_row4_col2\" class=\"data row4 col2\" >14.9806</td>\n                        <td id=\"T_4ebf4_row4_col3\" class=\"data row4 col3\" >888.8341</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_bc85a_row3_col0,#T_bc85a_row3_col1,#T_bc85a_row3_col2,#T_bc85a_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_bc85a_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_bc85a_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_bc85a_row0_col0\" class=\"data row0 col0\" >0.1138</td>\n",
+       "                        <td id=\"T_bc85a_row0_col1\" class=\"data row0 col1\" >0.1076</td>\n",
+       "                        <td id=\"T_bc85a_row0_col2\" class=\"data row0 col2\" >40.1667</td>\n",
+       "                        <td id=\"T_bc85a_row0_col3\" class=\"data row0 col3\" >1720.1667</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_bc85a_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_bc85a_row1_col0\" class=\"data row1 col0\" >0.0322</td>\n",
+       "                        <td id=\"T_bc85a_row1_col1\" class=\"data row1 col1\" >0.0314</td>\n",
+       "                        <td id=\"T_bc85a_row1_col2\" class=\"data row1 col2\" >12.5833</td>\n",
+       "                        <td id=\"T_bc85a_row1_col3\" class=\"data row1 col3\" >289.4167</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_bc85a_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_bc85a_row2_col0\" class=\"data row2 col0\" >0.1176</td>\n",
+       "                        <td id=\"T_bc85a_row2_col1\" class=\"data row2 col1\" >0.1106</td>\n",
+       "                        <td id=\"T_bc85a_row2_col2\" class=\"data row2 col2\" >47.3333</td>\n",
+       "                        <td id=\"T_bc85a_row2_col3\" class=\"data row2 col3\" >2426.0000</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_bc85a_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_bc85a_row3_col0\" class=\"data row3 col0\" >0.0879</td>\n",
+       "                        <td id=\"T_bc85a_row3_col1\" class=\"data row3 col1\" >0.0832</td>\n",
+       "                        <td id=\"T_bc85a_row3_col2\" class=\"data row3 col2\" >33.3611</td>\n",
+       "                        <td id=\"T_bc85a_row3_col3\" class=\"data row3 col3\" >1478.5278</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_bc85a_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_bc85a_row4_col0\" class=\"data row4 col0\" >0.0394</td>\n",
+       "                        <td id=\"T_bc85a_row4_col1\" class=\"data row4 col1\" >0.0367</td>\n",
+       "                        <td id=\"T_bc85a_row4_col2\" class=\"data row4 col2\" >14.9806</td>\n",
+       "                        <td id=\"T_bc85a_row4_col3\" class=\"data row4 col3\" >888.8341</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a36d0710>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "NaiveForecaster(sp=1, strategy='last', window_length=None)\nNaiveForecaster(sp=12, strategy='last', window_length=None)\n"
+      "NaiveForecaster(sp=1, strategy='last', window_length=None)\n",
+      "NaiveForecaster(sp=12, strategy='last', window_length=None)\n"
      ]
     }
    ],
@@ -389,18 +771,62 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb658f948>",
-      "text/html": "<style  type=\"text/css\" >\n#T_2c450_row3_col0,#T_2c450_row3_col1,#T_2c450_row3_col2,#T_2c450_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_2c450_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_2c450_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_2c450_row0_col0\" class=\"data row0 col0\" >0.1138</td>\n                        <td id=\"T_2c450_row0_col1\" class=\"data row0 col1\" >0.1076</td>\n                        <td id=\"T_2c450_row0_col2\" class=\"data row0 col2\" >40.1667</td>\n                        <td id=\"T_2c450_row0_col3\" class=\"data row0 col3\" >1720.1667</td>\n            </tr>\n            <tr>\n                        <th id=\"T_2c450_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_2c450_row1_col0\" class=\"data row1 col0\" >0.0322</td>\n                        <td id=\"T_2c450_row1_col1\" class=\"data row1 col1\" >0.0314</td>\n                        <td id=\"T_2c450_row1_col2\" class=\"data row1 col2\" >12.5833</td>\n                        <td id=\"T_2c450_row1_col3\" class=\"data row1 col3\" >289.4167</td>\n            </tr>\n            <tr>\n                        <th id=\"T_2c450_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_2c450_row2_col0\" class=\"data row2 col0\" >0.1176</td>\n                        <td id=\"T_2c450_row2_col1\" class=\"data row2 col1\" >0.1106</td>\n                        <td id=\"T_2c450_row2_col2\" class=\"data row2 col2\" >47.3333</td>\n                        <td id=\"T_2c450_row2_col3\" class=\"data row2 col3\" >2426.0000</td>\n            </tr>\n            <tr>\n                        <th id=\"T_2c450_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_2c450_row3_col0\" class=\"data row3 col0\" >0.0879</td>\n                        <td id=\"T_2c450_row3_col1\" class=\"data row3 col1\" >0.0832</td>\n                        <td id=\"T_2c450_row3_col2\" class=\"data row3 col2\" >33.3611</td>\n                        <td id=\"T_2c450_row3_col3\" class=\"data row3 col3\" >1478.5278</td>\n            </tr>\n            <tr>\n                        <th id=\"T_2c450_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_2c450_row4_col0\" class=\"data row4 col0\" >0.0394</td>\n                        <td id=\"T_2c450_row4_col1\" class=\"data row4 col1\" >0.0367</td>\n                        <td id=\"T_2c450_row4_col2\" class=\"data row4 col2\" >14.9806</td>\n                        <td id=\"T_2c450_row4_col3\" class=\"data row4 col3\" >888.8341</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_e63c1_row3_col0,#T_e63c1_row3_col1,#T_e63c1_row3_col2,#T_e63c1_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_e63c1_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_e63c1_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_e63c1_row0_col0\" class=\"data row0 col0\" >0.1138</td>\n",
+       "                        <td id=\"T_e63c1_row0_col1\" class=\"data row0 col1\" >0.1076</td>\n",
+       "                        <td id=\"T_e63c1_row0_col2\" class=\"data row0 col2\" >40.1667</td>\n",
+       "                        <td id=\"T_e63c1_row0_col3\" class=\"data row0 col3\" >1720.1667</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e63c1_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_e63c1_row1_col0\" class=\"data row1 col0\" >0.0322</td>\n",
+       "                        <td id=\"T_e63c1_row1_col1\" class=\"data row1 col1\" >0.0314</td>\n",
+       "                        <td id=\"T_e63c1_row1_col2\" class=\"data row1 col2\" >12.5833</td>\n",
+       "                        <td id=\"T_e63c1_row1_col3\" class=\"data row1 col3\" >289.4167</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e63c1_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_e63c1_row2_col0\" class=\"data row2 col0\" >0.1176</td>\n",
+       "                        <td id=\"T_e63c1_row2_col1\" class=\"data row2 col1\" >0.1106</td>\n",
+       "                        <td id=\"T_e63c1_row2_col2\" class=\"data row2 col2\" >47.3333</td>\n",
+       "                        <td id=\"T_e63c1_row2_col3\" class=\"data row2 col3\" >2426.0000</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e63c1_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_e63c1_row3_col0\" class=\"data row3 col0\" >0.0879</td>\n",
+       "                        <td id=\"T_e63c1_row3_col1\" class=\"data row3 col1\" >0.0832</td>\n",
+       "                        <td id=\"T_e63c1_row3_col2\" class=\"data row3 col2\" >33.3611</td>\n",
+       "                        <td id=\"T_e63c1_row3_col3\" class=\"data row3 col3\" >1478.5278</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e63c1_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_e63c1_row4_col0\" class=\"data row4 col0\" >0.0394</td>\n",
+       "                        <td id=\"T_e63c1_row4_col1\" class=\"data row4 col1\" >0.0367</td>\n",
+       "                        <td id=\"T_e63c1_row4_col2\" class=\"data row4 col2\" >14.9806</td>\n",
+       "                        <td id=\"T_e63c1_row4_col3\" class=\"data row4 col3\" >888.8341</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a3723890>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "NaiveForecaster(sp=1, strategy='last', window_length=None)\nNaiveForecaster(sp=12, strategy='last', window_length=None)\n"
+      "NaiveForecaster(sp=1, strategy='last', window_length=None)\n",
+      "NaiveForecaster(sp=12, strategy='last', window_length=None)\n"
      ]
     }
    ],
@@ -424,15 +850,57 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb7ebdf88>",
-      "text/html": "<style  type=\"text/css\" >\n#T_8b78b_row3_col0,#T_8b78b_row3_col1,#T_8b78b_row3_col2,#T_8b78b_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_8b78b_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_8b78b_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_8b78b_row0_col0\" class=\"data row0 col0\" >0.1226</td>\n                        <td id=\"T_8b78b_row0_col1\" class=\"data row0 col1\" >0.1140</td>\n                        <td id=\"T_8b78b_row0_col2\" class=\"data row0 col2\" >45.8148</td>\n                        <td id=\"T_8b78b_row0_col3\" class=\"data row0 col3\" >3789.0261</td>\n            </tr>\n            <tr>\n                        <th id=\"T_8b78b_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_8b78b_row1_col0\" class=\"data row1 col0\" >0.1278</td>\n                        <td id=\"T_8b78b_row1_col1\" class=\"data row1 col1\" >0.1275</td>\n                        <td id=\"T_8b78b_row1_col2\" class=\"data row1 col2\" >49.9929</td>\n                        <td id=\"T_8b78b_row1_col3\" class=\"data row1 col3\" >3759.3858</td>\n            </tr>\n            <tr>\n                        <th id=\"T_8b78b_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_8b78b_row2_col0\" class=\"data row2 col0\" >0.1144</td>\n                        <td id=\"T_8b78b_row2_col1\" class=\"data row2 col1\" >0.1096</td>\n                        <td id=\"T_8b78b_row2_col2\" class=\"data row2 col2\" >50.0825</td>\n                        <td id=\"T_8b78b_row2_col3\" class=\"data row2 col3\" >4545.5664</td>\n            </tr>\n            <tr>\n                        <th id=\"T_8b78b_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_8b78b_row3_col0\" class=\"data row3 col0\" >0.1216</td>\n                        <td id=\"T_8b78b_row3_col1\" class=\"data row3 col1\" >0.1170</td>\n                        <td id=\"T_8b78b_row3_col2\" class=\"data row3 col2\" >48.6301</td>\n                        <td id=\"T_8b78b_row3_col3\" class=\"data row3 col3\" >4031.3261</td>\n            </tr>\n            <tr>\n                        <th id=\"T_8b78b_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_8b78b_row4_col0\" class=\"data row4 col0\" >0.0055</td>\n                        <td id=\"T_8b78b_row4_col1\" class=\"data row4 col1\" >0.0076</td>\n                        <td id=\"T_8b78b_row4_col2\" class=\"data row4 col2\" >1.9910</td>\n                        <td id=\"T_8b78b_row4_col3\" class=\"data row4 col3\" >363.8241</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_88c9a_row3_col0,#T_88c9a_row3_col1,#T_88c9a_row3_col2,#T_88c9a_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_88c9a_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_88c9a_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_88c9a_row0_col0\" class=\"data row0 col0\" >0.1226</td>\n",
+       "                        <td id=\"T_88c9a_row0_col1\" class=\"data row0 col1\" >0.1140</td>\n",
+       "                        <td id=\"T_88c9a_row0_col2\" class=\"data row0 col2\" >45.8148</td>\n",
+       "                        <td id=\"T_88c9a_row0_col3\" class=\"data row0 col3\" >3789.0261</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_88c9a_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_88c9a_row1_col0\" class=\"data row1 col0\" >0.1278</td>\n",
+       "                        <td id=\"T_88c9a_row1_col1\" class=\"data row1 col1\" >0.1275</td>\n",
+       "                        <td id=\"T_88c9a_row1_col2\" class=\"data row1 col2\" >49.9929</td>\n",
+       "                        <td id=\"T_88c9a_row1_col3\" class=\"data row1 col3\" >3759.3858</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_88c9a_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_88c9a_row2_col0\" class=\"data row2 col0\" >0.1144</td>\n",
+       "                        <td id=\"T_88c9a_row2_col1\" class=\"data row2 col1\" >0.1096</td>\n",
+       "                        <td id=\"T_88c9a_row2_col2\" class=\"data row2 col2\" >50.0825</td>\n",
+       "                        <td id=\"T_88c9a_row2_col3\" class=\"data row2 col3\" >4545.5664</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_88c9a_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_88c9a_row3_col0\" class=\"data row3 col0\" >0.1216</td>\n",
+       "                        <td id=\"T_88c9a_row3_col1\" class=\"data row3 col1\" >0.1170</td>\n",
+       "                        <td id=\"T_88c9a_row3_col2\" class=\"data row3 col2\" >48.6301</td>\n",
+       "                        <td id=\"T_88c9a_row3_col3\" class=\"data row3 col3\" >4031.3261</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_88c9a_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_88c9a_row4_col0\" class=\"data row4 col0\" >0.0055</td>\n",
+       "                        <td id=\"T_88c9a_row4_col1\" class=\"data row4 col1\" >0.0076</td>\n",
+       "                        <td id=\"T_88c9a_row4_col2\" class=\"data row4 col2\" >1.9910</td>\n",
+       "                        <td id=\"T_88c9a_row4_col3\" class=\"data row4 col3\" >363.8241</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a36bf290>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
        "1960-01    432.979412\n",
@@ -450,8 +918,9 @@
        "Freq: M, dtype: float64"
       ]
      },
+     "execution_count": 14,
      "metadata": {},
-     "execution_count": 14
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -465,18 +934,62 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb6524788>",
-      "text/html": "<style  type=\"text/css\" >\n#T_ac19b_row3_col0,#T_ac19b_row3_col1,#T_ac19b_row3_col2,#T_ac19b_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_ac19b_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_ac19b_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_ac19b_row0_col0\" class=\"data row0 col0\" >0.1226</td>\n                        <td id=\"T_ac19b_row0_col1\" class=\"data row0 col1\" >0.1140</td>\n                        <td id=\"T_ac19b_row0_col2\" class=\"data row0 col2\" >45.8148</td>\n                        <td id=\"T_ac19b_row0_col3\" class=\"data row0 col3\" >3789.0261</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ac19b_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_ac19b_row1_col0\" class=\"data row1 col0\" >0.1278</td>\n                        <td id=\"T_ac19b_row1_col1\" class=\"data row1 col1\" >0.1275</td>\n                        <td id=\"T_ac19b_row1_col2\" class=\"data row1 col2\" >49.9929</td>\n                        <td id=\"T_ac19b_row1_col3\" class=\"data row1 col3\" >3759.3858</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ac19b_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_ac19b_row2_col0\" class=\"data row2 col0\" >0.1144</td>\n                        <td id=\"T_ac19b_row2_col1\" class=\"data row2 col1\" >0.1096</td>\n                        <td id=\"T_ac19b_row2_col2\" class=\"data row2 col2\" >50.0825</td>\n                        <td id=\"T_ac19b_row2_col3\" class=\"data row2 col3\" >4545.5664</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ac19b_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_ac19b_row3_col0\" class=\"data row3 col0\" >0.1216</td>\n                        <td id=\"T_ac19b_row3_col1\" class=\"data row3 col1\" >0.1170</td>\n                        <td id=\"T_ac19b_row3_col2\" class=\"data row3 col2\" >48.6301</td>\n                        <td id=\"T_ac19b_row3_col3\" class=\"data row3 col3\" >4031.3261</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ac19b_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_ac19b_row4_col0\" class=\"data row4 col0\" >0.0055</td>\n                        <td id=\"T_ac19b_row4_col1\" class=\"data row4 col1\" >0.0076</td>\n                        <td id=\"T_ac19b_row4_col2\" class=\"data row4 col2\" >1.9910</td>\n                        <td id=\"T_ac19b_row4_col3\" class=\"data row4 col3\" >363.8241</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_ac697_row3_col0,#T_ac697_row3_col1,#T_ac697_row3_col2,#T_ac697_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_ac697_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_ac697_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_ac697_row0_col0\" class=\"data row0 col0\" >0.1226</td>\n",
+       "                        <td id=\"T_ac697_row0_col1\" class=\"data row0 col1\" >0.1140</td>\n",
+       "                        <td id=\"T_ac697_row0_col2\" class=\"data row0 col2\" >45.8148</td>\n",
+       "                        <td id=\"T_ac697_row0_col3\" class=\"data row0 col3\" >3789.0261</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_ac697_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_ac697_row1_col0\" class=\"data row1 col0\" >0.1278</td>\n",
+       "                        <td id=\"T_ac697_row1_col1\" class=\"data row1 col1\" >0.1275</td>\n",
+       "                        <td id=\"T_ac697_row1_col2\" class=\"data row1 col2\" >49.9929</td>\n",
+       "                        <td id=\"T_ac697_row1_col3\" class=\"data row1 col3\" >3759.3858</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_ac697_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_ac697_row2_col0\" class=\"data row2 col0\" >0.1144</td>\n",
+       "                        <td id=\"T_ac697_row2_col1\" class=\"data row2 col1\" >0.1096</td>\n",
+       "                        <td id=\"T_ac697_row2_col2\" class=\"data row2 col2\" >50.0825</td>\n",
+       "                        <td id=\"T_ac697_row2_col3\" class=\"data row2 col3\" >4545.5664</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_ac697_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_ac697_row3_col0\" class=\"data row3 col0\" >0.1216</td>\n",
+       "                        <td id=\"T_ac697_row3_col1\" class=\"data row3 col1\" >0.1170</td>\n",
+       "                        <td id=\"T_ac697_row3_col2\" class=\"data row3 col2\" >48.6301</td>\n",
+       "                        <td id=\"T_ac697_row3_col3\" class=\"data row3 col3\" >4031.3261</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_ac697_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_ac697_row4_col0\" class=\"data row4 col0\" >0.0055</td>\n",
+       "                        <td id=\"T_ac697_row4_col1\" class=\"data row4 col1\" >0.0076</td>\n",
+       "                        <td id=\"T_ac697_row4_col2\" class=\"data row4 col2\" >1.9910</td>\n",
+       "                        <td id=\"T_ac697_row4_col3\" class=\"data row4 col3\" >363.8241</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a356eed0>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "PolynomialTrendForecaster(degree=1, regressor=None, with_intercept=True)\nPolynomialTrendForecaster(degree=1, regressor=None, with_intercept=True)\n"
+      "PolynomialTrendForecaster(degree=1, regressor=None, with_intercept=True)\n",
+      "PolynomialTrendForecaster(degree=1, regressor=None, with_intercept=True)\n"
      ]
     }
    ],
@@ -493,18 +1006,62 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb8fdec88>",
-      "text/html": "<style  type=\"text/css\" >\n#T_5761f_row3_col0,#T_5761f_row3_col1,#T_5761f_row3_col2,#T_5761f_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_5761f_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_5761f_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_5761f_row0_col0\" class=\"data row0 col0\" >0.1215</td>\n                        <td id=\"T_5761f_row0_col1\" class=\"data row0 col1\" >0.1232</td>\n                        <td id=\"T_5761f_row0_col2\" class=\"data row0 col2\" >45.6407</td>\n                        <td id=\"T_5761f_row0_col3\" class=\"data row0 col3\" >3009.1181</td>\n            </tr>\n            <tr>\n                        <th id=\"T_5761f_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_5761f_row1_col0\" class=\"data row1 col0\" >0.1651</td>\n                        <td id=\"T_5761f_row1_col1\" class=\"data row1 col1\" >0.1792</td>\n                        <td id=\"T_5761f_row1_col2\" class=\"data row1 col2\" >65.0246</td>\n                        <td id=\"T_5761f_row1_col3\" class=\"data row1 col3\" >5126.1853</td>\n            </tr>\n            <tr>\n                        <th id=\"T_5761f_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_5761f_row2_col0\" class=\"data row2 col0\" >0.1146</td>\n                        <td id=\"T_5761f_row2_col1\" class=\"data row2 col1\" >0.1110</td>\n                        <td id=\"T_5761f_row2_col2\" class=\"data row2 col2\" >50.1574</td>\n                        <td id=\"T_5761f_row2_col3\" class=\"data row2 col3\" >4417.8619</td>\n            </tr>\n            <tr>\n                        <th id=\"T_5761f_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_5761f_row3_col0\" class=\"data row3 col0\" >0.1337</td>\n                        <td id=\"T_5761f_row3_col1\" class=\"data row3 col1\" >0.1378</td>\n                        <td id=\"T_5761f_row3_col2\" class=\"data row3 col2\" >53.6076</td>\n                        <td id=\"T_5761f_row3_col3\" class=\"data row3 col3\" >4184.3884</td>\n            </tr>\n            <tr>\n                        <th id=\"T_5761f_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_5761f_row4_col0\" class=\"data row4 col0\" >0.0223</td>\n                        <td id=\"T_5761f_row4_col1\" class=\"data row4 col1\" >0.0297</td>\n                        <td id=\"T_5761f_row4_col2\" class=\"data row4 col2\" >8.2810</td>\n                        <td id=\"T_5761f_row4_col3\" class=\"data row4 col3\" >879.9150</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_8f925_row3_col0,#T_8f925_row3_col1,#T_8f925_row3_col2,#T_8f925_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_8f925_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_8f925_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_8f925_row0_col0\" class=\"data row0 col0\" >0.1215</td>\n",
+       "                        <td id=\"T_8f925_row0_col1\" class=\"data row0 col1\" >0.1232</td>\n",
+       "                        <td id=\"T_8f925_row0_col2\" class=\"data row0 col2\" >45.6407</td>\n",
+       "                        <td id=\"T_8f925_row0_col3\" class=\"data row0 col3\" >3009.1181</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_8f925_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_8f925_row1_col0\" class=\"data row1 col0\" >0.1651</td>\n",
+       "                        <td id=\"T_8f925_row1_col1\" class=\"data row1 col1\" >0.1792</td>\n",
+       "                        <td id=\"T_8f925_row1_col2\" class=\"data row1 col2\" >65.0246</td>\n",
+       "                        <td id=\"T_8f925_row1_col3\" class=\"data row1 col3\" >5126.1853</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_8f925_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_8f925_row2_col0\" class=\"data row2 col0\" >0.1146</td>\n",
+       "                        <td id=\"T_8f925_row2_col1\" class=\"data row2 col1\" >0.1110</td>\n",
+       "                        <td id=\"T_8f925_row2_col2\" class=\"data row2 col2\" >50.1574</td>\n",
+       "                        <td id=\"T_8f925_row2_col3\" class=\"data row2 col3\" >4417.8619</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_8f925_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_8f925_row3_col0\" class=\"data row3 col0\" >0.1337</td>\n",
+       "                        <td id=\"T_8f925_row3_col1\" class=\"data row3 col1\" >0.1378</td>\n",
+       "                        <td id=\"T_8f925_row3_col2\" class=\"data row3 col2\" >53.6076</td>\n",
+       "                        <td id=\"T_8f925_row3_col3\" class=\"data row3 col3\" >4184.3884</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_8f925_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_8f925_row4_col0\" class=\"data row4 col0\" >0.0223</td>\n",
+       "                        <td id=\"T_8f925_row4_col1\" class=\"data row4 col1\" >0.0297</td>\n",
+       "                        <td id=\"T_8f925_row4_col2\" class=\"data row4 col2\" >8.2810</td>\n",
+       "                        <td id=\"T_8f925_row4_col3\" class=\"data row4 col3\" >879.9150</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a358af10>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "PolynomialTrendForecaster(degree=1, regressor=None, with_intercept=True)\nPolynomialTrendForecaster(degree=3, regressor=None, with_intercept=True)\n"
+      "PolynomialTrendForecaster(degree=1, regressor=None, with_intercept=True)\n",
+      "PolynomialTrendForecaster(degree=3, regressor=None, with_intercept=True)\n"
      ]
     }
    ],
@@ -516,11 +1073,11 @@
    ]
   },
   {
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "## ARIMA"
-   ],
-   "cell_type": "markdown",
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "code",
@@ -528,15 +1085,57 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb153ca88>",
-      "text/html": "<style  type=\"text/css\" >\n#T_c61fb_row3_col0,#T_c61fb_row3_col1,#T_c61fb_row3_col2,#T_c61fb_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_c61fb_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_c61fb_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_c61fb_row0_col0\" class=\"data row0 col0\" >0.2544</td>\n                        <td id=\"T_c61fb_row0_col1\" class=\"data row0 col1\" >0.2172</td>\n                        <td id=\"T_c61fb_row0_col2\" class=\"data row0 col2\" >86.4672</td>\n                        <td id=\"T_c61fb_row0_col3\" class=\"data row0 col3\" >10986.2059</td>\n            </tr>\n            <tr>\n                        <th id=\"T_c61fb_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_c61fb_row1_col0\" class=\"data row1 col0\" >0.1931</td>\n                        <td id=\"T_c61fb_row1_col1\" class=\"data row1 col1\" >0.1675</td>\n                        <td id=\"T_c61fb_row1_col2\" class=\"data row1 col2\" >71.1742</td>\n                        <td id=\"T_c61fb_row1_col3\" class=\"data row1 col3\" >9049.5816</td>\n            </tr>\n            <tr>\n                        <th id=\"T_c61fb_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_c61fb_row2_col0\" class=\"data row2 col0\" >0.2962</td>\n                        <td id=\"T_c61fb_row2_col1\" class=\"data row2 col1\" >0.2496</td>\n                        <td id=\"T_c61fb_row2_col2\" class=\"data row2 col2\" >114.6292</td>\n                        <td id=\"T_c61fb_row2_col3\" class=\"data row2 col3\" >18211.8564</td>\n            </tr>\n            <tr>\n                        <th id=\"T_c61fb_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_c61fb_row3_col0\" class=\"data row3 col0\" >0.2479</td>\n                        <td id=\"T_c61fb_row3_col1\" class=\"data row3 col1\" >0.2114</td>\n                        <td id=\"T_c61fb_row3_col2\" class=\"data row3 col2\" >90.7569</td>\n                        <td id=\"T_c61fb_row3_col3\" class=\"data row3 col3\" >12749.2146</td>\n            </tr>\n            <tr>\n                        <th id=\"T_c61fb_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_c61fb_row4_col0\" class=\"data row4 col0\" >0.0424</td>\n                        <td id=\"T_c61fb_row4_col1\" class=\"data row4 col1\" >0.0338</td>\n                        <td id=\"T_c61fb_row4_col2\" class=\"data row4 col2\" >17.9979</td>\n                        <td id=\"T_c61fb_row4_col3\" class=\"data row4 col3\" >3942.7545</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_993ae_row3_col0,#T_993ae_row3_col1,#T_993ae_row3_col2,#T_993ae_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_993ae_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_993ae_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_993ae_row0_col0\" class=\"data row0 col0\" >0.2544</td>\n",
+       "                        <td id=\"T_993ae_row0_col1\" class=\"data row0 col1\" >0.2172</td>\n",
+       "                        <td id=\"T_993ae_row0_col2\" class=\"data row0 col2\" >86.4672</td>\n",
+       "                        <td id=\"T_993ae_row0_col3\" class=\"data row0 col3\" >10986.2059</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_993ae_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_993ae_row1_col0\" class=\"data row1 col0\" >0.1931</td>\n",
+       "                        <td id=\"T_993ae_row1_col1\" class=\"data row1 col1\" >0.1675</td>\n",
+       "                        <td id=\"T_993ae_row1_col2\" class=\"data row1 col2\" >71.1742</td>\n",
+       "                        <td id=\"T_993ae_row1_col3\" class=\"data row1 col3\" >9049.5815</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_993ae_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_993ae_row2_col0\" class=\"data row2 col0\" >0.2962</td>\n",
+       "                        <td id=\"T_993ae_row2_col1\" class=\"data row2 col1\" >0.2496</td>\n",
+       "                        <td id=\"T_993ae_row2_col2\" class=\"data row2 col2\" >114.6292</td>\n",
+       "                        <td id=\"T_993ae_row2_col3\" class=\"data row2 col3\" >18211.8563</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_993ae_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_993ae_row3_col0\" class=\"data row3 col0\" >0.2479</td>\n",
+       "                        <td id=\"T_993ae_row3_col1\" class=\"data row3 col1\" >0.2114</td>\n",
+       "                        <td id=\"T_993ae_row3_col2\" class=\"data row3 col2\" >90.7569</td>\n",
+       "                        <td id=\"T_993ae_row3_col3\" class=\"data row3 col3\" >12749.2146</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_993ae_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_993ae_row4_col0\" class=\"data row4 col0\" >0.0424</td>\n",
+       "                        <td id=\"T_993ae_row4_col1\" class=\"data row4 col1\" >0.0338</td>\n",
+       "                        <td id=\"T_993ae_row4_col2\" class=\"data row4 col2\" >17.9979</td>\n",
+       "                        <td id=\"T_993ae_row4_col3\" class=\"data row4 col3\" >3942.7545</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a3588f90>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
        "1960-01    399.517880\n",
@@ -554,8 +1153,9 @@
        "Freq: M, dtype: float64"
       ]
      },
+     "execution_count": 17,
      "metadata": {},
-     "execution_count": 17
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -569,18 +1169,68 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb8ec1448>",
-      "text/html": "<style  type=\"text/css\" >\n#T_ef1af_row3_col0,#T_ef1af_row3_col1,#T_ef1af_row3_col2,#T_ef1af_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_ef1af_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_ef1af_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_ef1af_row0_col0\" class=\"data row0 col0\" >0.2767</td>\n                        <td id=\"T_ef1af_row0_col1\" class=\"data row0 col1\" >0.2401</td>\n                        <td id=\"T_ef1af_row0_col2\" class=\"data row0 col2\" >91.6004</td>\n                        <td id=\"T_ef1af_row0_col3\" class=\"data row0 col3\" >9823.6666</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ef1af_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_ef1af_row1_col0\" class=\"data row1 col0\" >0.1797</td>\n                        <td id=\"T_ef1af_row1_col1\" class=\"data row1 col1\" >0.1623</td>\n                        <td id=\"T_ef1af_row1_col2\" class=\"data row1 col2\" >65.5763</td>\n                        <td id=\"T_ef1af_row1_col3\" class=\"data row1 col3\" >5777.5063</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ef1af_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_ef1af_row2_col0\" class=\"data row2 col0\" >0.3155</td>\n                        <td id=\"T_ef1af_row2_col1\" class=\"data row2 col1\" >0.2685</td>\n                        <td id=\"T_ef1af_row2_col2\" class=\"data row2 col2\" >118.6957</td>\n                        <td id=\"T_ef1af_row2_col3\" class=\"data row2 col3\" >16425.1666</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ef1af_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_ef1af_row3_col0\" class=\"data row3 col0\" >0.2573</td>\n                        <td id=\"T_ef1af_row3_col1\" class=\"data row3 col1\" >0.2237</td>\n                        <td id=\"T_ef1af_row3_col2\" class=\"data row3 col2\" >91.9575</td>\n                        <td id=\"T_ef1af_row3_col3\" class=\"data row3 col3\" >10675.4465</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ef1af_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_ef1af_row4_col0\" class=\"data row4 col0\" >0.0571</td>\n                        <td id=\"T_ef1af_row4_col1\" class=\"data row4 col1\" >0.0449</td>\n                        <td id=\"T_ef1af_row4_col2\" class=\"data row4 col2\" >21.6874</td>\n                        <td id=\"T_ef1af_row4_col3\" class=\"data row4 col3\" >4388.4177</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_e7a6e_row3_col0,#T_e7a6e_row3_col1,#T_e7a6e_row3_col2,#T_e7a6e_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_e7a6e_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_e7a6e_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_e7a6e_row0_col0\" class=\"data row0 col0\" >0.2767</td>\n",
+       "                        <td id=\"T_e7a6e_row0_col1\" class=\"data row0 col1\" >0.2401</td>\n",
+       "                        <td id=\"T_e7a6e_row0_col2\" class=\"data row0 col2\" >91.6004</td>\n",
+       "                        <td id=\"T_e7a6e_row0_col3\" class=\"data row0 col3\" >9823.6668</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e7a6e_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_e7a6e_row1_col0\" class=\"data row1 col0\" >0.1797</td>\n",
+       "                        <td id=\"T_e7a6e_row1_col1\" class=\"data row1 col1\" >0.1623</td>\n",
+       "                        <td id=\"T_e7a6e_row1_col2\" class=\"data row1 col2\" >65.5746</td>\n",
+       "                        <td id=\"T_e7a6e_row1_col3\" class=\"data row1 col3\" >5777.2750</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e7a6e_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_e7a6e_row2_col0\" class=\"data row2 col0\" >0.3155</td>\n",
+       "                        <td id=\"T_e7a6e_row2_col1\" class=\"data row2 col1\" >0.2685</td>\n",
+       "                        <td id=\"T_e7a6e_row2_col2\" class=\"data row2 col2\" >118.6964</td>\n",
+       "                        <td id=\"T_e7a6e_row2_col3\" class=\"data row2 col3\" >16425.3251</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e7a6e_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_e7a6e_row3_col0\" class=\"data row3 col0\" >0.2573</td>\n",
+       "                        <td id=\"T_e7a6e_row3_col1\" class=\"data row3 col1\" >0.2236</td>\n",
+       "                        <td id=\"T_e7a6e_row3_col2\" class=\"data row3 col2\" >91.9571</td>\n",
+       "                        <td id=\"T_e7a6e_row3_col3\" class=\"data row3 col3\" >10675.4223</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e7a6e_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_e7a6e_row4_col0\" class=\"data row4 col0\" >0.0571</td>\n",
+       "                        <td id=\"T_e7a6e_row4_col1\" class=\"data row4 col1\" >0.0449</td>\n",
+       "                        <td id=\"T_e7a6e_row4_col2\" class=\"data row4 col2\" >21.6883</td>\n",
+       "                        <td id=\"T_e7a6e_row4_col3\" class=\"data row4 col3\" >4388.5729</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e5a3da50>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "ARIMA(maxiter=50, method='lbfgs', order=(1, 0, 0), out_of_sample_size=0,\n      scoring='mse', scoring_args=None, seasonal_order=(0, 0, 0, 0),\n      start_params=None, suppress_warnings=False, trend=None,\n      with_intercept=True)\nARIMA(maxiter=50, method='lbfgs', order=(0, 0, 1), out_of_sample_size=0,\n      scoring='mse', scoring_args=None, seasonal_order=(0, 0, 1, 12),\n      start_params=None, suppress_warnings=False, trend=None,\n      with_intercept=True)\n"
+      "ARIMA(maxiter=50, method='lbfgs', order=(1, 0, 0), out_of_sample_size=0,\n",
+      "      scoring='mse', scoring_args=None, seasonal_order=(0, 0, 0, 0),\n",
+      "      start_params=None, suppress_warnings=False, trend=None,\n",
+      "      with_intercept=True)\n",
+      "ARIMA(maxiter=50, method='lbfgs', order=(0, 0, 1), out_of_sample_size=0,\n",
+      "      scoring='mse', scoring_args=None, seasonal_order=(0, 0, 1, 12),\n",
+      "      start_params=None, suppress_warnings=False, trend=None,\n",
+      "      with_intercept=True)\n"
      ]
     }
    ],
@@ -597,18 +1247,68 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb658fa88>",
-      "text/html": "<style  type=\"text/css\" >\n#T_6dc3f_row3_col0,#T_6dc3f_row3_col1,#T_6dc3f_row3_col2,#T_6dc3f_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_6dc3f_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_6dc3f_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_6dc3f_row0_col0\" class=\"data row0 col0\" >0.0339</td>\n                        <td id=\"T_6dc3f_row0_col1\" class=\"data row0 col1\" >0.0331</td>\n                        <td id=\"T_6dc3f_row0_col2\" class=\"data row0 col2\" >13.2626</td>\n                        <td id=\"T_6dc3f_row0_col3\" class=\"data row0 col3\" >277.8525</td>\n            </tr>\n            <tr>\n                        <th id=\"T_6dc3f_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_6dc3f_row1_col0\" class=\"data row1 col0\" >0.0513</td>\n                        <td id=\"T_6dc3f_row1_col1\" class=\"data row1 col1\" >0.0530</td>\n                        <td id=\"T_6dc3f_row1_col2\" class=\"data row1 col2\" >19.1686</td>\n                        <td id=\"T_6dc3f_row1_col3\" class=\"data row1 col3\" >455.3259</td>\n            </tr>\n            <tr>\n                        <th id=\"T_6dc3f_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_6dc3f_row2_col0\" class=\"data row2 col0\" >0.0506</td>\n                        <td id=\"T_6dc3f_row2_col1\" class=\"data row2 col1\" >0.0491</td>\n                        <td id=\"T_6dc3f_row2_col2\" class=\"data row2 col2\" >21.1925</td>\n                        <td id=\"T_6dc3f_row2_col3\" class=\"data row2 col3\" >551.0621</td>\n            </tr>\n            <tr>\n                        <th id=\"T_6dc3f_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_6dc3f_row3_col0\" class=\"data row3 col0\" >0.0453</td>\n                        <td id=\"T_6dc3f_row3_col1\" class=\"data row3 col1\" >0.0451</td>\n                        <td id=\"T_6dc3f_row3_col2\" class=\"data row3 col2\" >17.8746</td>\n                        <td id=\"T_6dc3f_row3_col3\" class=\"data row3 col3\" >428.0802</td>\n            </tr>\n            <tr>\n                        <th id=\"T_6dc3f_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_6dc3f_row4_col0\" class=\"data row4 col0\" >0.0080</td>\n                        <td id=\"T_6dc3f_row4_col1\" class=\"data row4 col1\" >0.0086</td>\n                        <td id=\"T_6dc3f_row4_col2\" class=\"data row4 col2\" >3.3642</td>\n                        <td id=\"T_6dc3f_row4_col3\" class=\"data row4 col3\" >113.1890</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_94bbf_row3_col0,#T_94bbf_row3_col1,#T_94bbf_row3_col2,#T_94bbf_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_94bbf_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_94bbf_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_94bbf_row0_col0\" class=\"data row0 col0\" >0.0339</td>\n",
+       "                        <td id=\"T_94bbf_row0_col1\" class=\"data row0 col1\" >0.0331</td>\n",
+       "                        <td id=\"T_94bbf_row0_col2\" class=\"data row0 col2\" >13.2626</td>\n",
+       "                        <td id=\"T_94bbf_row0_col3\" class=\"data row0 col3\" >277.8525</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_94bbf_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_94bbf_row1_col0\" class=\"data row1 col0\" >0.0513</td>\n",
+       "                        <td id=\"T_94bbf_row1_col1\" class=\"data row1 col1\" >0.0530</td>\n",
+       "                        <td id=\"T_94bbf_row1_col2\" class=\"data row1 col2\" >19.1686</td>\n",
+       "                        <td id=\"T_94bbf_row1_col3\" class=\"data row1 col3\" >455.3259</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_94bbf_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_94bbf_row2_col0\" class=\"data row2 col0\" >0.0506</td>\n",
+       "                        <td id=\"T_94bbf_row2_col1\" class=\"data row2 col1\" >0.0491</td>\n",
+       "                        <td id=\"T_94bbf_row2_col2\" class=\"data row2 col2\" >21.1925</td>\n",
+       "                        <td id=\"T_94bbf_row2_col3\" class=\"data row2 col3\" >551.0621</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_94bbf_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_94bbf_row3_col0\" class=\"data row3 col0\" >0.0453</td>\n",
+       "                        <td id=\"T_94bbf_row3_col1\" class=\"data row3 col1\" >0.0451</td>\n",
+       "                        <td id=\"T_94bbf_row3_col2\" class=\"data row3 col2\" >17.8746</td>\n",
+       "                        <td id=\"T_94bbf_row3_col3\" class=\"data row3 col3\" >428.0802</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_94bbf_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_94bbf_row4_col0\" class=\"data row4 col0\" >0.0080</td>\n",
+       "                        <td id=\"T_94bbf_row4_col1\" class=\"data row4 col1\" >0.0086</td>\n",
+       "                        <td id=\"T_94bbf_row4_col2\" class=\"data row4 col2\" >3.3642</td>\n",
+       "                        <td id=\"T_94bbf_row4_col3\" class=\"data row4 col3\" >113.1890</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e5a3dc50>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "ARIMA(maxiter=50, method='lbfgs', order=(1, 0, 0), out_of_sample_size=0,\n      scoring='mse', scoring_args=None, seasonal_order=(0, 0, 0, 0),\n      start_params=None, suppress_warnings=False, trend=None,\n      with_intercept=True)\nARIMA(maxiter=50, method='lbfgs', order=(0, 0, 0), out_of_sample_size=0,\n      scoring='mse', scoring_args=None, seasonal_order=(1, 1, 0, 12),\n      start_params=None, suppress_warnings=False, trend=None,\n      with_intercept=True)\n"
+      "ARIMA(maxiter=50, method='lbfgs', order=(1, 0, 0), out_of_sample_size=0,\n",
+      "      scoring='mse', scoring_args=None, seasonal_order=(0, 0, 0, 0),\n",
+      "      start_params=None, suppress_warnings=False, trend=None,\n",
+      "      with_intercept=True)\n",
+      "ARIMA(maxiter=50, method='lbfgs', order=(0, 0, 0), out_of_sample_size=0,\n",
+      "      scoring='mse', scoring_args=None, seasonal_order=(1, 1, 0, 12),\n",
+      "      start_params=None, suppress_warnings=False, trend=None,\n",
+      "      with_intercept=True)\n"
      ]
     }
    ],
@@ -632,15 +1332,57 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbbb0e75c8>",
-      "text/html": "<style  type=\"text/css\" >\n#T_ab67d_row3_col0,#T_ab67d_row3_col1,#T_ab67d_row3_col2,#T_ab67d_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_ab67d_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_ab67d_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_ab67d_row0_col0\" class=\"data row0 col0\" >0.1766</td>\n                        <td id=\"T_ab67d_row0_col1\" class=\"data row0 col1\" >0.1549</td>\n                        <td id=\"T_ab67d_row0_col2\" class=\"data row0 col2\" >63.4167</td>\n                        <td id=\"T_ab67d_row0_col3\" class=\"data row0 col3\" >6967.9167</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ab67d_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_ab67d_row1_col0\" class=\"data row1 col0\" >0.1351</td>\n                        <td id=\"T_ab67d_row1_col1\" class=\"data row1 col1\" >0.1205</td>\n                        <td id=\"T_ab67d_row1_col2\" class=\"data row1 col2\" >52.3333</td>\n                        <td id=\"T_ab67d_row1_col3\" class=\"data row1 col3\" >5842.1667</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ab67d_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_ab67d_row2_col0\" class=\"data row2 col0\" >0.2263</td>\n                        <td id=\"T_ab67d_row2_col1\" class=\"data row2 col1\" >0.1957</td>\n                        <td id=\"T_ab67d_row2_col2\" class=\"data row2 col2\" >91.4671</td>\n                        <td id=\"T_ab67d_row2_col3\" class=\"data row2 col3\" >12836.1198</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ab67d_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_ab67d_row3_col0\" class=\"data row3 col0\" >0.1793</td>\n                        <td id=\"T_ab67d_row3_col1\" class=\"data row3 col1\" >0.1570</td>\n                        <td id=\"T_ab67d_row3_col2\" class=\"data row3 col2\" >69.0724</td>\n                        <td id=\"T_ab67d_row3_col3\" class=\"data row3 col3\" >8548.7344</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ab67d_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_ab67d_row4_col0\" class=\"data row4 col0\" >0.0373</td>\n                        <td id=\"T_ab67d_row4_col1\" class=\"data row4 col1\" >0.0307</td>\n                        <td id=\"T_ab67d_row4_col2\" class=\"data row4 col2\" >16.4692</td>\n                        <td id=\"T_ab67d_row4_col3\" class=\"data row4 col3\" >3066.2771</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_faeee_row3_col0,#T_faeee_row3_col1,#T_faeee_row3_col2,#T_faeee_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_faeee_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_faeee_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_faeee_row0_col0\" class=\"data row0 col0\" >0.1766</td>\n",
+       "                        <td id=\"T_faeee_row0_col1\" class=\"data row0 col1\" >0.1549</td>\n",
+       "                        <td id=\"T_faeee_row0_col2\" class=\"data row0 col2\" >63.4167</td>\n",
+       "                        <td id=\"T_faeee_row0_col3\" class=\"data row0 col3\" >6967.9167</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_faeee_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_faeee_row1_col0\" class=\"data row1 col0\" >0.1351</td>\n",
+       "                        <td id=\"T_faeee_row1_col1\" class=\"data row1 col1\" >0.1205</td>\n",
+       "                        <td id=\"T_faeee_row1_col2\" class=\"data row1 col2\" >52.3333</td>\n",
+       "                        <td id=\"T_faeee_row1_col3\" class=\"data row1 col3\" >5842.1667</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_faeee_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_faeee_row2_col0\" class=\"data row2 col0\" >0.2263</td>\n",
+       "                        <td id=\"T_faeee_row2_col1\" class=\"data row2 col1\" >0.1957</td>\n",
+       "                        <td id=\"T_faeee_row2_col2\" class=\"data row2 col2\" >91.4671</td>\n",
+       "                        <td id=\"T_faeee_row2_col3\" class=\"data row2 col3\" >12836.1198</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_faeee_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_faeee_row3_col0\" class=\"data row3 col0\" >0.1793</td>\n",
+       "                        <td id=\"T_faeee_row3_col1\" class=\"data row3 col1\" >0.1570</td>\n",
+       "                        <td id=\"T_faeee_row3_col2\" class=\"data row3 col2\" >69.0724</td>\n",
+       "                        <td id=\"T_faeee_row3_col3\" class=\"data row3 col3\" >8548.7344</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_faeee_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_faeee_row4_col0\" class=\"data row4 col0\" >0.0373</td>\n",
+       "                        <td id=\"T_faeee_row4_col1\" class=\"data row4 col1\" >0.0307</td>\n",
+       "                        <td id=\"T_faeee_row4_col2\" class=\"data row4 col2\" >16.4692</td>\n",
+       "                        <td id=\"T_faeee_row4_col3\" class=\"data row4 col3\" >3066.2771</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e5a36450>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
        "1960-01    404.786132\n",
@@ -658,8 +1400,9 @@
        "Freq: M, dtype: float64"
       ]
      },
+     "execution_count": 20,
      "metadata": {},
-     "execution_count": 20
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -673,18 +1416,68 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbbb108288>",
-      "text/html": "<style  type=\"text/css\" >\n#T_ab5ff_row3_col0,#T_ab5ff_row3_col1,#T_ab5ff_row3_col2,#T_ab5ff_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_ab5ff_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_ab5ff_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_ab5ff_row0_col0\" class=\"data row0 col0\" >0.0273</td>\n                        <td id=\"T_ab5ff_row0_col1\" class=\"data row0 col1\" >0.0272</td>\n                        <td id=\"T_ab5ff_row0_col2\" class=\"data row0 col2\" >10.5620</td>\n                        <td id=\"T_ab5ff_row0_col3\" class=\"data row0 col3\" >182.1899</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ab5ff_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_ab5ff_row1_col0\" class=\"data row1 col0\" >0.0704</td>\n                        <td id=\"T_ab5ff_row1_col1\" class=\"data row1 col1\" >0.0738</td>\n                        <td id=\"T_ab5ff_row1_col2\" class=\"data row1 col2\" >26.2572</td>\n                        <td id=\"T_ab5ff_row1_col3\" class=\"data row1 col3\" >903.9130</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ab5ff_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_ab5ff_row2_col0\" class=\"data row2 col0\" >0.0265</td>\n                        <td id=\"T_ab5ff_row2_col1\" class=\"data row2 col1\" >0.0261</td>\n                        <td id=\"T_ab5ff_row2_col2\" class=\"data row2 col2\" >11.2644</td>\n                        <td id=\"T_ab5ff_row2_col3\" class=\"data row2 col3\" >179.8604</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ab5ff_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_ab5ff_row3_col0\" class=\"data row3 col0\" >0.0414</td>\n                        <td id=\"T_ab5ff_row3_col1\" class=\"data row3 col1\" >0.0424</td>\n                        <td id=\"T_ab5ff_row3_col2\" class=\"data row3 col2\" >16.0279</td>\n                        <td id=\"T_ab5ff_row3_col3\" class=\"data row3 col3\" >421.9878</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ab5ff_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_ab5ff_row4_col0\" class=\"data row4 col0\" >0.0205</td>\n                        <td id=\"T_ab5ff_row4_col1\" class=\"data row4 col1\" >0.0222</td>\n                        <td id=\"T_ab5ff_row4_col2\" class=\"data row4 col2\" >7.2389</td>\n                        <td id=\"T_ab5ff_row4_col3\" class=\"data row4 col3\" >340.7739</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_d068b_row3_col0,#T_d068b_row3_col1,#T_d068b_row3_col2,#T_d068b_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_d068b_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_d068b_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_d068b_row0_col0\" class=\"data row0 col0\" >0.0273</td>\n",
+       "                        <td id=\"T_d068b_row0_col1\" class=\"data row0 col1\" >0.0272</td>\n",
+       "                        <td id=\"T_d068b_row0_col2\" class=\"data row0 col2\" >10.5620</td>\n",
+       "                        <td id=\"T_d068b_row0_col3\" class=\"data row0 col3\" >182.1899</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d068b_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_d068b_row1_col0\" class=\"data row1 col0\" >0.0704</td>\n",
+       "                        <td id=\"T_d068b_row1_col1\" class=\"data row1 col1\" >0.0738</td>\n",
+       "                        <td id=\"T_d068b_row1_col2\" class=\"data row1 col2\" >26.2573</td>\n",
+       "                        <td id=\"T_d068b_row1_col3\" class=\"data row1 col3\" >903.9160</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d068b_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_d068b_row2_col0\" class=\"data row2 col0\" >0.0265</td>\n",
+       "                        <td id=\"T_d068b_row2_col1\" class=\"data row2 col1\" >0.0261</td>\n",
+       "                        <td id=\"T_d068b_row2_col2\" class=\"data row2 col2\" >11.2644</td>\n",
+       "                        <td id=\"T_d068b_row2_col3\" class=\"data row2 col3\" >179.8603</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d068b_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_d068b_row3_col0\" class=\"data row3 col0\" >0.0414</td>\n",
+       "                        <td id=\"T_d068b_row3_col1\" class=\"data row3 col1\" >0.0424</td>\n",
+       "                        <td id=\"T_d068b_row3_col2\" class=\"data row3 col2\" >16.0279</td>\n",
+       "                        <td id=\"T_d068b_row3_col3\" class=\"data row3 col3\" >421.9887</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_d068b_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_d068b_row4_col0\" class=\"data row4 col0\" >0.0205</td>\n",
+       "                        <td id=\"T_d068b_row4_col1\" class=\"data row4 col1\" >0.0222</td>\n",
+       "                        <td id=\"T_d068b_row4_col2\" class=\"data row4 col2\" >7.2390</td>\n",
+       "                        <td id=\"T_d068b_row4_col3\" class=\"data row4 col3\" >340.7754</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e5a3df50>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "ExponentialSmoothing(damped_trend=False, initial_level=None,\n                     initial_seasonal=None, initial_trend=None,\n                     initialization_method='estimated', seasonal=None, sp=None,\n                     trend=None, use_boxcox=None)\nExponentialSmoothing(damped_trend=False, initial_level=None,\n                     initial_seasonal=None, initial_trend=None,\n                     initialization_method='estimated', seasonal='add', sp=12,\n                     trend='add', use_boxcox=True)\n"
+      "ExponentialSmoothing(damped_trend=False, initial_level=None,\n",
+      "                     initial_seasonal=None, initial_trend=None,\n",
+      "                     initialization_method='estimated', seasonal=None, sp=None,\n",
+      "                     trend=None, use_boxcox=None)\n",
+      "ExponentialSmoothing(damped_trend=False, initial_level=None,\n",
+      "                     initial_seasonal=None, initial_trend=None,\n",
+      "                     initialization_method='estimated', seasonal='add', sp=12,\n",
+      "                     trend='add', use_boxcox=True)\n"
      ]
     }
    ],
@@ -701,18 +1494,68 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbbc172c48>",
-      "text/html": "<style  type=\"text/css\" >\n#T_4095e_row3_col0,#T_4095e_row3_col1,#T_4095e_row3_col2,#T_4095e_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_4095e_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_4095e_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_4095e_row0_col0\" class=\"data row0 col0\" >0.0273</td>\n                        <td id=\"T_4095e_row0_col1\" class=\"data row0 col1\" >0.0272</td>\n                        <td id=\"T_4095e_row0_col2\" class=\"data row0 col2\" >10.5620</td>\n                        <td id=\"T_4095e_row0_col3\" class=\"data row0 col3\" >182.1899</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4095e_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_4095e_row1_col0\" class=\"data row1 col0\" >0.0704</td>\n                        <td id=\"T_4095e_row1_col1\" class=\"data row1 col1\" >0.0738</td>\n                        <td id=\"T_4095e_row1_col2\" class=\"data row1 col2\" >26.2572</td>\n                        <td id=\"T_4095e_row1_col3\" class=\"data row1 col3\" >903.9130</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4095e_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_4095e_row2_col0\" class=\"data row2 col0\" >0.0265</td>\n                        <td id=\"T_4095e_row2_col1\" class=\"data row2 col1\" >0.0261</td>\n                        <td id=\"T_4095e_row2_col2\" class=\"data row2 col2\" >11.2644</td>\n                        <td id=\"T_4095e_row2_col3\" class=\"data row2 col3\" >179.8604</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4095e_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_4095e_row3_col0\" class=\"data row3 col0\" >0.0414</td>\n                        <td id=\"T_4095e_row3_col1\" class=\"data row3 col1\" >0.0424</td>\n                        <td id=\"T_4095e_row3_col2\" class=\"data row3 col2\" >16.0279</td>\n                        <td id=\"T_4095e_row3_col3\" class=\"data row3 col3\" >421.9878</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4095e_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_4095e_row4_col0\" class=\"data row4 col0\" >0.0205</td>\n                        <td id=\"T_4095e_row4_col1\" class=\"data row4 col1\" >0.0222</td>\n                        <td id=\"T_4095e_row4_col2\" class=\"data row4 col2\" >7.2389</td>\n                        <td id=\"T_4095e_row4_col3\" class=\"data row4 col3\" >340.7739</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_74594_row3_col0,#T_74594_row3_col1,#T_74594_row3_col2,#T_74594_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_74594_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_74594_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_74594_row0_col0\" class=\"data row0 col0\" >0.0273</td>\n",
+       "                        <td id=\"T_74594_row0_col1\" class=\"data row0 col1\" >0.0272</td>\n",
+       "                        <td id=\"T_74594_row0_col2\" class=\"data row0 col2\" >10.5620</td>\n",
+       "                        <td id=\"T_74594_row0_col3\" class=\"data row0 col3\" >182.1899</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_74594_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_74594_row1_col0\" class=\"data row1 col0\" >0.0704</td>\n",
+       "                        <td id=\"T_74594_row1_col1\" class=\"data row1 col1\" >0.0738</td>\n",
+       "                        <td id=\"T_74594_row1_col2\" class=\"data row1 col2\" >26.2573</td>\n",
+       "                        <td id=\"T_74594_row1_col3\" class=\"data row1 col3\" >903.9160</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_74594_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_74594_row2_col0\" class=\"data row2 col0\" >0.0265</td>\n",
+       "                        <td id=\"T_74594_row2_col1\" class=\"data row2 col1\" >0.0261</td>\n",
+       "                        <td id=\"T_74594_row2_col2\" class=\"data row2 col2\" >11.2644</td>\n",
+       "                        <td id=\"T_74594_row2_col3\" class=\"data row2 col3\" >179.8603</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_74594_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_74594_row3_col0\" class=\"data row3 col0\" >0.0414</td>\n",
+       "                        <td id=\"T_74594_row3_col1\" class=\"data row3 col1\" >0.0424</td>\n",
+       "                        <td id=\"T_74594_row3_col2\" class=\"data row3 col2\" >16.0279</td>\n",
+       "                        <td id=\"T_74594_row3_col3\" class=\"data row3 col3\" >421.9887</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_74594_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_74594_row4_col0\" class=\"data row4 col0\" >0.0205</td>\n",
+       "                        <td id=\"T_74594_row4_col1\" class=\"data row4 col1\" >0.0222</td>\n",
+       "                        <td id=\"T_74594_row4_col2\" class=\"data row4 col2\" >7.2390</td>\n",
+       "                        <td id=\"T_74594_row4_col3\" class=\"data row4 col3\" >340.7754</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e5a0aa10>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "ExponentialSmoothing(damped_trend=False, initial_level=None,\n                     initial_seasonal=None, initial_trend=None,\n                     initialization_method='estimated', seasonal=None, sp=None,\n                     trend=None, use_boxcox=None)\nExponentialSmoothing(damped_trend=False, initial_level=None,\n                     initial_seasonal=None, initial_trend=None,\n                     initialization_method='estimated', seasonal='additive',\n                     sp=None, trend='additive', use_boxcox=True)\n"
+      "ExponentialSmoothing(damped_trend=False, initial_level=None,\n",
+      "                     initial_seasonal=None, initial_trend=None,\n",
+      "                     initialization_method='estimated', seasonal=None, sp=None,\n",
+      "                     trend=None, use_boxcox=None)\n",
+      "ExponentialSmoothing(damped_trend=False, initial_level=None,\n",
+      "                     initial_seasonal=None, initial_trend=None,\n",
+      "                     initialization_method='estimated', seasonal='additive',\n",
+      "                     sp=None, trend='additive', use_boxcox=True)\n"
      ]
     }
    ],
@@ -736,15 +1579,57 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb90410c8>",
-      "text/html": "<style  type=\"text/css\" >\n#T_0a50e_row3_col0,#T_0a50e_row3_col1,#T_0a50e_row3_col2,#T_0a50e_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_0a50e_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_0a50e_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_0a50e_row0_col0\" class=\"data row0 col0\" >0.1582</td>\n                        <td id=\"T_0a50e_row0_col1\" class=\"data row0 col1\" >0.1406</td>\n                        <td id=\"T_0a50e_row0_col2\" class=\"data row0 col2\" >57.5799</td>\n                        <td id=\"T_0a50e_row0_col3\" class=\"data row0 col3\" >5883.9192</td>\n            </tr>\n            <tr>\n                        <th id=\"T_0a50e_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_0a50e_row1_col0\" class=\"data row1 col0\" >0.1244</td>\n                        <td id=\"T_0a50e_row1_col1\" class=\"data row1 col1\" >0.1131</td>\n                        <td id=\"T_0a50e_row1_col2\" class=\"data row1 col2\" >48.6352</td>\n                        <td id=\"T_0a50e_row1_col3\" class=\"data row1 col3\" >5040.6939</td>\n            </tr>\n            <tr>\n                        <th id=\"T_0a50e_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_0a50e_row2_col0\" class=\"data row2 col0\" >0.1995</td>\n                        <td id=\"T_0a50e_row2_col1\" class=\"data row2 col1\" >0.1738</td>\n                        <td id=\"T_0a50e_row2_col2\" class=\"data row2 col2\" >82.1049</td>\n                        <td id=\"T_0a50e_row2_col3\" class=\"data row2 col3\" >11072.6778</td>\n            </tr>\n            <tr>\n                        <th id=\"T_0a50e_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_0a50e_row3_col0\" class=\"data row3 col0\" >0.1607</td>\n                        <td id=\"T_0a50e_row3_col1\" class=\"data row3 col1\" >0.1425</td>\n                        <td id=\"T_0a50e_row3_col2\" class=\"data row3 col2\" >62.7733</td>\n                        <td id=\"T_0a50e_row3_col3\" class=\"data row3 col3\" >7332.4303</td>\n            </tr>\n            <tr>\n                        <th id=\"T_0a50e_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_0a50e_row4_col0\" class=\"data row4 col0\" >0.0307</td>\n                        <td id=\"T_0a50e_row4_col1\" class=\"data row4 col1\" >0.0248</td>\n                        <td id=\"T_0a50e_row4_col2\" class=\"data row4 col2\" >14.1488</td>\n                        <td id=\"T_0a50e_row4_col3\" class=\"data row4 col3\" >2667.0640</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_e0dcc_row3_col0,#T_e0dcc_row3_col1,#T_e0dcc_row3_col2,#T_e0dcc_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_e0dcc_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_e0dcc_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_e0dcc_row0_col0\" class=\"data row0 col0\" >0.1582</td>\n",
+       "                        <td id=\"T_e0dcc_row0_col1\" class=\"data row0 col1\" >0.1406</td>\n",
+       "                        <td id=\"T_e0dcc_row0_col2\" class=\"data row0 col2\" >57.5799</td>\n",
+       "                        <td id=\"T_e0dcc_row0_col3\" class=\"data row0 col3\" >5883.9192</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e0dcc_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_e0dcc_row1_col0\" class=\"data row1 col0\" >0.1244</td>\n",
+       "                        <td id=\"T_e0dcc_row1_col1\" class=\"data row1 col1\" >0.1131</td>\n",
+       "                        <td id=\"T_e0dcc_row1_col2\" class=\"data row1 col2\" >48.6352</td>\n",
+       "                        <td id=\"T_e0dcc_row1_col3\" class=\"data row1 col3\" >5040.6939</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e0dcc_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_e0dcc_row2_col0\" class=\"data row2 col0\" >0.1995</td>\n",
+       "                        <td id=\"T_e0dcc_row2_col1\" class=\"data row2 col1\" >0.1738</td>\n",
+       "                        <td id=\"T_e0dcc_row2_col2\" class=\"data row2 col2\" >82.1049</td>\n",
+       "                        <td id=\"T_e0dcc_row2_col3\" class=\"data row2 col3\" >11072.6778</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e0dcc_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_e0dcc_row3_col0\" class=\"data row3 col0\" >0.1607</td>\n",
+       "                        <td id=\"T_e0dcc_row3_col1\" class=\"data row3 col1\" >0.1425</td>\n",
+       "                        <td id=\"T_e0dcc_row3_col2\" class=\"data row3 col2\" >62.7733</td>\n",
+       "                        <td id=\"T_e0dcc_row3_col3\" class=\"data row3 col3\" >7332.4303</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e0dcc_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_e0dcc_row4_col0\" class=\"data row4 col0\" >0.0307</td>\n",
+       "                        <td id=\"T_e0dcc_row4_col1\" class=\"data row4 col1\" >0.0248</td>\n",
+       "                        <td id=\"T_e0dcc_row4_col2\" class=\"data row4 col2\" >14.1488</td>\n",
+       "                        <td id=\"T_e0dcc_row4_col3\" class=\"data row4 col3\" >2667.0640</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e59b5dd0>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
        "1960-01    407.356288\n",
@@ -762,8 +1647,9 @@
        "Freq: M, dtype: float64"
       ]
      },
+     "execution_count": 23,
      "metadata": {},
-     "execution_count": 23
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -777,18 +1663,62 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbbc198988>",
-      "text/html": "<style  type=\"text/css\" >\n#T_6cdf8_row3_col0,#T_6cdf8_row3_col1,#T_6cdf8_row3_col2,#T_6cdf8_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_6cdf8_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_6cdf8_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_6cdf8_row0_col0\" class=\"data row0 col0\" >0.0592</td>\n                        <td id=\"T_6cdf8_row0_col1\" class=\"data row0 col1\" >0.0570</td>\n                        <td id=\"T_6cdf8_row0_col2\" class=\"data row0 col2\" >22.3655</td>\n                        <td id=\"T_6cdf8_row0_col3\" class=\"data row0 col3\" >776.5129</td>\n            </tr>\n            <tr>\n                        <th id=\"T_6cdf8_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_6cdf8_row1_col0\" class=\"data row1 col0\" >0.0378</td>\n                        <td id=\"T_6cdf8_row1_col1\" class=\"data row1 col1\" >0.0378</td>\n                        <td id=\"T_6cdf8_row1_col2\" class=\"data row1 col2\" >15.0918</td>\n                        <td id=\"T_6cdf8_row1_col3\" class=\"data row1 col3\" >398.2215</td>\n            </tr>\n            <tr>\n                        <th id=\"T_6cdf8_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_6cdf8_row2_col0\" class=\"data row2 col0\" >0.0884</td>\n                        <td id=\"T_6cdf8_row2_col1\" class=\"data row2 col1\" >0.0832</td>\n                        <td id=\"T_6cdf8_row2_col2\" class=\"data row2 col2\" >37.8295</td>\n                        <td id=\"T_6cdf8_row2_col3\" class=\"data row2 col3\" >2153.9634</td>\n            </tr>\n            <tr>\n                        <th id=\"T_6cdf8_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_6cdf8_row3_col0\" class=\"data row3 col0\" >0.0618</td>\n                        <td id=\"T_6cdf8_row3_col1\" class=\"data row3 col1\" >0.0593</td>\n                        <td id=\"T_6cdf8_row3_col2\" class=\"data row3 col2\" >25.0956</td>\n                        <td id=\"T_6cdf8_row3_col3\" class=\"data row3 col3\" >1109.5659</td>\n            </tr>\n            <tr>\n                        <th id=\"T_6cdf8_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_6cdf8_row4_col0\" class=\"data row4 col0\" >0.0207</td>\n                        <td id=\"T_6cdf8_row4_col1\" class=\"data row4 col1\" >0.0186</td>\n                        <td id=\"T_6cdf8_row4_col2\" class=\"data row4 col2\" >9.4813</td>\n                        <td id=\"T_6cdf8_row4_col3\" class=\"data row4 col3\" >754.4759</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_289ea_row3_col0,#T_289ea_row3_col1,#T_289ea_row3_col2,#T_289ea_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_289ea_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_289ea_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_289ea_row0_col0\" class=\"data row0 col0\" >0.0592</td>\n",
+       "                        <td id=\"T_289ea_row0_col1\" class=\"data row0 col1\" >0.0570</td>\n",
+       "                        <td id=\"T_289ea_row0_col2\" class=\"data row0 col2\" >22.3655</td>\n",
+       "                        <td id=\"T_289ea_row0_col3\" class=\"data row0 col3\" >776.5132</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_289ea_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_289ea_row1_col0\" class=\"data row1 col0\" >0.0378</td>\n",
+       "                        <td id=\"T_289ea_row1_col1\" class=\"data row1 col1\" >0.0378</td>\n",
+       "                        <td id=\"T_289ea_row1_col2\" class=\"data row1 col2\" >15.0918</td>\n",
+       "                        <td id=\"T_289ea_row1_col3\" class=\"data row1 col3\" >398.2215</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_289ea_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_289ea_row2_col0\" class=\"data row2 col0\" >0.0884</td>\n",
+       "                        <td id=\"T_289ea_row2_col1\" class=\"data row2 col1\" >0.0832</td>\n",
+       "                        <td id=\"T_289ea_row2_col2\" class=\"data row2 col2\" >37.8295</td>\n",
+       "                        <td id=\"T_289ea_row2_col3\" class=\"data row2 col3\" >2153.9634</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_289ea_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_289ea_row3_col0\" class=\"data row3 col0\" >0.0618</td>\n",
+       "                        <td id=\"T_289ea_row3_col1\" class=\"data row3 col1\" >0.0593</td>\n",
+       "                        <td id=\"T_289ea_row3_col2\" class=\"data row3 col2\" >25.0956</td>\n",
+       "                        <td id=\"T_289ea_row3_col3\" class=\"data row3 col3\" >1109.5660</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_289ea_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_289ea_row4_col0\" class=\"data row4 col0\" >0.0207</td>\n",
+       "                        <td id=\"T_289ea_row4_col1\" class=\"data row4 col1\" >0.0186</td>\n",
+       "                        <td id=\"T_289ea_row4_col2\" class=\"data row4 col2\" >9.4813</td>\n",
+       "                        <td id=\"T_289ea_row4_col3\" class=\"data row4 col3\" >754.4758</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a3723750>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "ThetaForecaster(deseasonalize=True, initial_level=None, sp=1)\nThetaForecaster(deseasonalize=True, initial_level=None, sp=24)\n"
+      "ThetaForecaster(deseasonalize=True, initial_level=None, sp=1)\n",
+      "ThetaForecaster(deseasonalize=True, initial_level=None, sp=24)\n"
      ]
     }
    ],
@@ -805,18 +1735,62 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb8ece908>",
-      "text/html": "<style  type=\"text/css\" >\n#T_d8064_row3_col0,#T_d8064_row3_col1,#T_d8064_row3_col2,#T_d8064_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_d8064_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_d8064_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_d8064_row0_col0\" class=\"data row0 col0\" >0.0592</td>\n                        <td id=\"T_d8064_row0_col1\" class=\"data row0 col1\" >0.0570</td>\n                        <td id=\"T_d8064_row0_col2\" class=\"data row0 col2\" >22.3655</td>\n                        <td id=\"T_d8064_row0_col3\" class=\"data row0 col3\" >776.5129</td>\n            </tr>\n            <tr>\n                        <th id=\"T_d8064_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_d8064_row1_col0\" class=\"data row1 col0\" >0.0378</td>\n                        <td id=\"T_d8064_row1_col1\" class=\"data row1 col1\" >0.0378</td>\n                        <td id=\"T_d8064_row1_col2\" class=\"data row1 col2\" >15.0918</td>\n                        <td id=\"T_d8064_row1_col3\" class=\"data row1 col3\" >398.2215</td>\n            </tr>\n            <tr>\n                        <th id=\"T_d8064_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_d8064_row2_col0\" class=\"data row2 col0\" >0.0884</td>\n                        <td id=\"T_d8064_row2_col1\" class=\"data row2 col1\" >0.0832</td>\n                        <td id=\"T_d8064_row2_col2\" class=\"data row2 col2\" >37.8295</td>\n                        <td id=\"T_d8064_row2_col3\" class=\"data row2 col3\" >2153.9634</td>\n            </tr>\n            <tr>\n                        <th id=\"T_d8064_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_d8064_row3_col0\" class=\"data row3 col0\" >0.0618</td>\n                        <td id=\"T_d8064_row3_col1\" class=\"data row3 col1\" >0.0593</td>\n                        <td id=\"T_d8064_row3_col2\" class=\"data row3 col2\" >25.0956</td>\n                        <td id=\"T_d8064_row3_col3\" class=\"data row3 col3\" >1109.5659</td>\n            </tr>\n            <tr>\n                        <th id=\"T_d8064_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_d8064_row4_col0\" class=\"data row4 col0\" >0.0207</td>\n                        <td id=\"T_d8064_row4_col1\" class=\"data row4 col1\" >0.0186</td>\n                        <td id=\"T_d8064_row4_col2\" class=\"data row4 col2\" >9.4813</td>\n                        <td id=\"T_d8064_row4_col3\" class=\"data row4 col3\" >754.4759</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_018df_row3_col0,#T_018df_row3_col1,#T_018df_row3_col2,#T_018df_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_018df_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_018df_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_018df_row0_col0\" class=\"data row0 col0\" >0.0592</td>\n",
+       "                        <td id=\"T_018df_row0_col1\" class=\"data row0 col1\" >0.0570</td>\n",
+       "                        <td id=\"T_018df_row0_col2\" class=\"data row0 col2\" >22.3655</td>\n",
+       "                        <td id=\"T_018df_row0_col3\" class=\"data row0 col3\" >776.5132</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_018df_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_018df_row1_col0\" class=\"data row1 col0\" >0.0378</td>\n",
+       "                        <td id=\"T_018df_row1_col1\" class=\"data row1 col1\" >0.0378</td>\n",
+       "                        <td id=\"T_018df_row1_col2\" class=\"data row1 col2\" >15.0918</td>\n",
+       "                        <td id=\"T_018df_row1_col3\" class=\"data row1 col3\" >398.2215</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_018df_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_018df_row2_col0\" class=\"data row2 col0\" >0.0884</td>\n",
+       "                        <td id=\"T_018df_row2_col1\" class=\"data row2 col1\" >0.0832</td>\n",
+       "                        <td id=\"T_018df_row2_col2\" class=\"data row2 col2\" >37.8295</td>\n",
+       "                        <td id=\"T_018df_row2_col3\" class=\"data row2 col3\" >2153.9634</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_018df_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_018df_row3_col0\" class=\"data row3 col0\" >0.0618</td>\n",
+       "                        <td id=\"T_018df_row3_col1\" class=\"data row3 col1\" >0.0593</td>\n",
+       "                        <td id=\"T_018df_row3_col2\" class=\"data row3 col2\" >25.0956</td>\n",
+       "                        <td id=\"T_018df_row3_col3\" class=\"data row3 col3\" >1109.5660</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_018df_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_018df_row4_col0\" class=\"data row4 col0\" >0.0207</td>\n",
+       "                        <td id=\"T_018df_row4_col1\" class=\"data row4 col1\" >0.0186</td>\n",
+       "                        <td id=\"T_018df_row4_col2\" class=\"data row4 col2\" >9.4813</td>\n",
+       "                        <td id=\"T_018df_row4_col3\" class=\"data row4 col3\" >754.4758</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a39e05d0>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "ThetaForecaster(deseasonalize=True, initial_level=None, sp=1)\nThetaForecaster(deseasonalize=True, initial_level=None, sp=24)\n"
+      "ThetaForecaster(deseasonalize=True, initial_level=None, sp=1)\n",
+      "ThetaForecaster(deseasonalize=True, initial_level=None, sp=24)\n"
      ]
     }
    ],
@@ -840,15 +1814,57 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbbd179388>",
-      "text/html": "<style  type=\"text/css\" >\n#T_260fc_row3_col0,#T_260fc_row3_col1,#T_260fc_row3_col2,#T_260fc_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_260fc_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_260fc_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_260fc_row0_col0\" class=\"data row0 col0\" >0.1766</td>\n                        <td id=\"T_260fc_row0_col1\" class=\"data row0 col1\" >0.1549</td>\n                        <td id=\"T_260fc_row0_col2\" class=\"data row0 col2\" >63.4190</td>\n                        <td id=\"T_260fc_row0_col3\" class=\"data row0 col3\" >6968.3536</td>\n            </tr>\n            <tr>\n                        <th id=\"T_260fc_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_260fc_row1_col0\" class=\"data row1 col0\" >0.1351</td>\n                        <td id=\"T_260fc_row1_col1\" class=\"data row1 col1\" >0.1205</td>\n                        <td id=\"T_260fc_row1_col2\" class=\"data row1 col2\" >52.3354</td>\n                        <td id=\"T_260fc_row1_col3\" class=\"data row1 col3\" >5842.4456</td>\n            </tr>\n            <tr>\n                        <th id=\"T_260fc_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_260fc_row2_col0\" class=\"data row2 col0\" >0.2259</td>\n                        <td id=\"T_260fc_row2_col1\" class=\"data row2 col1\" >0.1954</td>\n                        <td id=\"T_260fc_row2_col2\" class=\"data row2 col2\" >91.3360</td>\n                        <td id=\"T_260fc_row2_col3\" class=\"data row2 col3\" >12812.1598</td>\n            </tr>\n            <tr>\n                        <th id=\"T_260fc_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_260fc_row3_col0\" class=\"data row3 col0\" >0.1792</td>\n                        <td id=\"T_260fc_row3_col1\" class=\"data row3 col1\" >0.1569</td>\n                        <td id=\"T_260fc_row3_col2\" class=\"data row3 col2\" >69.0301</td>\n                        <td id=\"T_260fc_row3_col3\" class=\"data row3 col3\" >8540.9863</td>\n            </tr>\n            <tr>\n                        <th id=\"T_260fc_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_260fc_row4_col0\" class=\"data row4 col0\" >0.0371</td>\n                        <td id=\"T_260fc_row4_col1\" class=\"data row4 col1\" >0.0306</td>\n                        <td id=\"T_260fc_row4_col2\" class=\"data row4 col2\" >16.4089</td>\n                        <td id=\"T_260fc_row4_col3\" class=\"data row4 col3\" >3054.9533</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_f1f38_row3_col0,#T_f1f38_row3_col1,#T_f1f38_row3_col2,#T_f1f38_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_f1f38_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_f1f38_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_f1f38_row0_col0\" class=\"data row0 col0\" >0.1766</td>\n",
+       "                        <td id=\"T_f1f38_row0_col1\" class=\"data row0 col1\" >0.1549</td>\n",
+       "                        <td id=\"T_f1f38_row0_col2\" class=\"data row0 col2\" >63.4190</td>\n",
+       "                        <td id=\"T_f1f38_row0_col3\" class=\"data row0 col3\" >6968.3536</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f1f38_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_f1f38_row1_col0\" class=\"data row1 col0\" >0.1351</td>\n",
+       "                        <td id=\"T_f1f38_row1_col1\" class=\"data row1 col1\" >0.1205</td>\n",
+       "                        <td id=\"T_f1f38_row1_col2\" class=\"data row1 col2\" >52.3354</td>\n",
+       "                        <td id=\"T_f1f38_row1_col3\" class=\"data row1 col3\" >5842.4456</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f1f38_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_f1f38_row2_col0\" class=\"data row2 col0\" >0.2259</td>\n",
+       "                        <td id=\"T_f1f38_row2_col1\" class=\"data row2 col1\" >0.1954</td>\n",
+       "                        <td id=\"T_f1f38_row2_col2\" class=\"data row2 col2\" >91.3360</td>\n",
+       "                        <td id=\"T_f1f38_row2_col3\" class=\"data row2 col3\" >12812.1598</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f1f38_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_f1f38_row3_col0\" class=\"data row3 col0\" >0.1792</td>\n",
+       "                        <td id=\"T_f1f38_row3_col1\" class=\"data row3 col1\" >0.1569</td>\n",
+       "                        <td id=\"T_f1f38_row3_col2\" class=\"data row3 col2\" >69.0301</td>\n",
+       "                        <td id=\"T_f1f38_row3_col3\" class=\"data row3 col3\" >8540.9863</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f1f38_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_f1f38_row4_col0\" class=\"data row4 col0\" >0.0371</td>\n",
+       "                        <td id=\"T_f1f38_row4_col1\" class=\"data row4 col1\" >0.0306</td>\n",
+       "                        <td id=\"T_f1f38_row4_col2\" class=\"data row4 col2\" >16.4089</td>\n",
+       "                        <td id=\"T_f1f38_row4_col3\" class=\"data row4 col3\" >3054.9533</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a369e650>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
        "1960-01    404.9957\n",
@@ -866,8 +1882,9 @@
        "Freq: M, dtype: float64"
       ]
      },
+     "execution_count": 26,
      "metadata": {},
-     "execution_count": 26
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -881,18 +1898,74 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb8fd9c88>",
-      "text/html": "<style  type=\"text/css\" >\n#T_cdb55_row3_col0,#T_cdb55_row3_col1,#T_cdb55_row3_col2,#T_cdb55_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_cdb55_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_cdb55_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_cdb55_row0_col0\" class=\"data row0 col0\" >0.0376</td>\n                        <td id=\"T_cdb55_row0_col1\" class=\"data row0 col1\" >0.0366</td>\n                        <td id=\"T_cdb55_row0_col2\" class=\"data row0 col2\" >14.5582</td>\n                        <td id=\"T_cdb55_row0_col3\" class=\"data row0 col3\" >352.4071</td>\n            </tr>\n            <tr>\n                        <th id=\"T_cdb55_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_cdb55_row1_col0\" class=\"data row1 col0\" >0.0447</td>\n                        <td id=\"T_cdb55_row1_col1\" class=\"data row1 col1\" >0.0458</td>\n                        <td id=\"T_cdb55_row1_col2\" class=\"data row1 col2\" >16.8005</td>\n                        <td id=\"T_cdb55_row1_col3\" class=\"data row1 col3\" >373.5136</td>\n            </tr>\n            <tr>\n                        <th id=\"T_cdb55_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_cdb55_row2_col0\" class=\"data row2 col0\" >0.0512</td>\n                        <td id=\"T_cdb55_row2_col1\" class=\"data row2 col1\" >0.0495</td>\n                        <td id=\"T_cdb55_row2_col2\" class=\"data row2 col2\" >20.8908</td>\n                        <td id=\"T_cdb55_row2_col3\" class=\"data row2 col3\" >549.0481</td>\n            </tr>\n            <tr>\n                        <th id=\"T_cdb55_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_cdb55_row3_col0\" class=\"data row3 col0\" >0.0445</td>\n                        <td id=\"T_cdb55_row3_col1\" class=\"data row3 col1\" >0.0440</td>\n                        <td id=\"T_cdb55_row3_col2\" class=\"data row3 col2\" >17.4165</td>\n                        <td id=\"T_cdb55_row3_col3\" class=\"data row3 col3\" >424.9896</td>\n            </tr>\n            <tr>\n                        <th id=\"T_cdb55_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_cdb55_row4_col0\" class=\"data row4 col0\" >0.0055</td>\n                        <td id=\"T_cdb55_row4_col1\" class=\"data row4 col1\" >0.0054</td>\n                        <td id=\"T_cdb55_row4_col2\" class=\"data row4 col2\" >2.6217</td>\n                        <td id=\"T_cdb55_row4_col3\" class=\"data row4 col3\" >88.1448</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_1db51_row3_col0,#T_1db51_row3_col1,#T_1db51_row3_col2,#T_1db51_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_1db51_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_1db51_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_1db51_row0_col0\" class=\"data row0 col0\" >0.0376</td>\n",
+       "                        <td id=\"T_1db51_row0_col1\" class=\"data row0 col1\" >0.0366</td>\n",
+       "                        <td id=\"T_1db51_row0_col2\" class=\"data row0 col2\" >14.5615</td>\n",
+       "                        <td id=\"T_1db51_row0_col3\" class=\"data row0 col3\" >352.4886</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_1db51_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_1db51_row1_col0\" class=\"data row1 col0\" >0.0446</td>\n",
+       "                        <td id=\"T_1db51_row1_col1\" class=\"data row1 col1\" >0.0458</td>\n",
+       "                        <td id=\"T_1db51_row1_col2\" class=\"data row1 col2\" >16.7827</td>\n",
+       "                        <td id=\"T_1db51_row1_col3\" class=\"data row1 col3\" >372.8826</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_1db51_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_1db51_row2_col0\" class=\"data row2 col0\" >0.0512</td>\n",
+       "                        <td id=\"T_1db51_row2_col1\" class=\"data row2 col1\" >0.0495</td>\n",
+       "                        <td id=\"T_1db51_row2_col2\" class=\"data row2 col2\" >20.8904</td>\n",
+       "                        <td id=\"T_1db51_row2_col3\" class=\"data row2 col3\" >549.0250</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_1db51_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_1db51_row3_col0\" class=\"data row3 col0\" >0.0445</td>\n",
+       "                        <td id=\"T_1db51_row3_col1\" class=\"data row3 col1\" >0.0440</td>\n",
+       "                        <td id=\"T_1db51_row3_col2\" class=\"data row3 col2\" >17.4115</td>\n",
+       "                        <td id=\"T_1db51_row3_col3\" class=\"data row3 col3\" >424.7988</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_1db51_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_1db51_row4_col0\" class=\"data row4 col0\" >0.0055</td>\n",
+       "                        <td id=\"T_1db51_row4_col1\" class=\"data row4 col1\" >0.0054</td>\n",
+       "                        <td id=\"T_1db51_row4_col2\" class=\"data row4 col2\" >2.6218</td>\n",
+       "                        <td id=\"T_1db51_row4_col3\" class=\"data row4 col3\" >88.2349</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e5a0a3d0>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "AutoETS(additive_only=False, allow_multiplicative_trend=False, auto=False,\n        bounds=None, callback=None, damped_trend=False, dates=None, disp=False,\n        error='add', freq=None, full_output=True, information_criterion='aic',\n        initial_level=None, initial_seasonal=None, initial_trend=None,\n        initialization_method='estimated', maxiter=1000, missing='none',\n        n_jobs=None, restrict=True, return_params=False, seasonal=None, sp=1,\n        start_params=None, trend=None)\nAutoETS(additive_only=False, allow_multiplicative_trend=False, auto=False,\n        bounds=None, callback=None, damped_trend=False, dates=None, disp=False,\n        error='add', freq=None, full_output=True, information_criterion='aic',\n        initial_level=None, initial_seasonal=None, initial_trend=None,\n        initialization_method='estimated', maxiter=1000, missing='none',\n        n_jobs=None, restrict=True, return_params=False, seasonal='mul', sp=12,\n        start_params=None, trend='add')\n"
+      "AutoETS(additive_only=False, allow_multiplicative_trend=False, auto=False,\n",
+      "        bounds=None, callback=None, damped_trend=False, dates=None, disp=False,\n",
+      "        error='add', freq=None, full_output=True, information_criterion='aic',\n",
+      "        initial_level=None, initial_seasonal=None, initial_trend=None,\n",
+      "        initialization_method='estimated', maxiter=1000, missing='none',\n",
+      "        n_jobs=None, restrict=True, return_params=False, seasonal=None, sp=1,\n",
+      "        start_params=None, trend=None)\n",
+      "AutoETS(additive_only=False, allow_multiplicative_trend=False, auto=False,\n",
+      "        bounds=None, callback=None, damped_trend=False, dates=None, disp=False,\n",
+      "        error='add', freq=None, full_output=True, information_criterion='aic',\n",
+      "        initial_level=None, initial_seasonal=None, initial_trend=None,\n",
+      "        initialization_method='estimated', maxiter=1000, missing='none',\n",
+      "        n_jobs=None, restrict=True, return_params=False, seasonal='mul', sp=12,\n",
+      "        start_params=None, trend='add')\n"
      ]
     }
    ],
@@ -909,18 +1982,74 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbbb10c148>",
-      "text/html": "<style  type=\"text/css\" >\n#T_22bb4_row3_col0,#T_22bb4_row3_col1,#T_22bb4_row3_col2,#T_22bb4_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_22bb4_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_22bb4_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_22bb4_row0_col0\" class=\"data row0 col0\" >0.0376</td>\n                        <td id=\"T_22bb4_row0_col1\" class=\"data row0 col1\" >0.0366</td>\n                        <td id=\"T_22bb4_row0_col2\" class=\"data row0 col2\" >14.5582</td>\n                        <td id=\"T_22bb4_row0_col3\" class=\"data row0 col3\" >352.4071</td>\n            </tr>\n            <tr>\n                        <th id=\"T_22bb4_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_22bb4_row1_col0\" class=\"data row1 col0\" >0.0447</td>\n                        <td id=\"T_22bb4_row1_col1\" class=\"data row1 col1\" >0.0458</td>\n                        <td id=\"T_22bb4_row1_col2\" class=\"data row1 col2\" >16.8005</td>\n                        <td id=\"T_22bb4_row1_col3\" class=\"data row1 col3\" >373.5136</td>\n            </tr>\n            <tr>\n                        <th id=\"T_22bb4_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_22bb4_row2_col0\" class=\"data row2 col0\" >0.0512</td>\n                        <td id=\"T_22bb4_row2_col1\" class=\"data row2 col1\" >0.0495</td>\n                        <td id=\"T_22bb4_row2_col2\" class=\"data row2 col2\" >20.8908</td>\n                        <td id=\"T_22bb4_row2_col3\" class=\"data row2 col3\" >549.0481</td>\n            </tr>\n            <tr>\n                        <th id=\"T_22bb4_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_22bb4_row3_col0\" class=\"data row3 col0\" >0.0445</td>\n                        <td id=\"T_22bb4_row3_col1\" class=\"data row3 col1\" >0.0440</td>\n                        <td id=\"T_22bb4_row3_col2\" class=\"data row3 col2\" >17.4165</td>\n                        <td id=\"T_22bb4_row3_col3\" class=\"data row3 col3\" >424.9896</td>\n            </tr>\n            <tr>\n                        <th id=\"T_22bb4_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_22bb4_row4_col0\" class=\"data row4 col0\" >0.0055</td>\n                        <td id=\"T_22bb4_row4_col1\" class=\"data row4 col1\" >0.0054</td>\n                        <td id=\"T_22bb4_row4_col2\" class=\"data row4 col2\" >2.6217</td>\n                        <td id=\"T_22bb4_row4_col3\" class=\"data row4 col3\" >88.1448</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_4622c_row3_col0,#T_4622c_row3_col1,#T_4622c_row3_col2,#T_4622c_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_4622c_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_4622c_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_4622c_row0_col0\" class=\"data row0 col0\" >0.0376</td>\n",
+       "                        <td id=\"T_4622c_row0_col1\" class=\"data row0 col1\" >0.0366</td>\n",
+       "                        <td id=\"T_4622c_row0_col2\" class=\"data row0 col2\" >14.5615</td>\n",
+       "                        <td id=\"T_4622c_row0_col3\" class=\"data row0 col3\" >352.4886</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_4622c_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_4622c_row1_col0\" class=\"data row1 col0\" >0.0446</td>\n",
+       "                        <td id=\"T_4622c_row1_col1\" class=\"data row1 col1\" >0.0458</td>\n",
+       "                        <td id=\"T_4622c_row1_col2\" class=\"data row1 col2\" >16.7827</td>\n",
+       "                        <td id=\"T_4622c_row1_col3\" class=\"data row1 col3\" >372.8826</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_4622c_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_4622c_row2_col0\" class=\"data row2 col0\" >0.0512</td>\n",
+       "                        <td id=\"T_4622c_row2_col1\" class=\"data row2 col1\" >0.0495</td>\n",
+       "                        <td id=\"T_4622c_row2_col2\" class=\"data row2 col2\" >20.8904</td>\n",
+       "                        <td id=\"T_4622c_row2_col3\" class=\"data row2 col3\" >549.0250</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_4622c_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_4622c_row3_col0\" class=\"data row3 col0\" >0.0445</td>\n",
+       "                        <td id=\"T_4622c_row3_col1\" class=\"data row3 col1\" >0.0440</td>\n",
+       "                        <td id=\"T_4622c_row3_col2\" class=\"data row3 col2\" >17.4115</td>\n",
+       "                        <td id=\"T_4622c_row3_col3\" class=\"data row3 col3\" >424.7988</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_4622c_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_4622c_row4_col0\" class=\"data row4 col0\" >0.0055</td>\n",
+       "                        <td id=\"T_4622c_row4_col1\" class=\"data row4 col1\" >0.0054</td>\n",
+       "                        <td id=\"T_4622c_row4_col2\" class=\"data row4 col2\" >2.6218</td>\n",
+       "                        <td id=\"T_4622c_row4_col3\" class=\"data row4 col3\" >88.2349</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e5a36350>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "AutoETS(additive_only=False, allow_multiplicative_trend=False, auto=False,\n        bounds=None, callback=None, damped_trend=False, dates=None, disp=False,\n        error='add', freq=None, full_output=True, information_criterion='aic',\n        initial_level=None, initial_seasonal=None, initial_trend=None,\n        initialization_method='estimated', maxiter=1000, missing='none',\n        n_jobs=None, restrict=True, return_params=False, seasonal=None, sp=1,\n        start_params=None, trend=None)\nAutoETS(additive_only=False, allow_multiplicative_trend=False, auto=False,\n        bounds=None, callback=None, damped_trend=False, dates=None, disp=False,\n        error='add', freq=None, full_output=True, information_criterion='aic',\n        initial_level=None, initial_seasonal=None, initial_trend=None,\n        initialization_method='estimated', maxiter=1000, missing='none',\n        n_jobs=None, restrict=True, return_params=False, seasonal='mul', sp=12,\n        start_params=None, trend='add')\n"
+      "AutoETS(additive_only=False, allow_multiplicative_trend=False, auto=False,\n",
+      "        bounds=None, callback=None, damped_trend=False, dates=None, disp=False,\n",
+      "        error='add', freq=None, full_output=True, information_criterion='aic',\n",
+      "        initial_level=None, initial_seasonal=None, initial_trend=None,\n",
+      "        initialization_method='estimated', maxiter=1000, missing='none',\n",
+      "        n_jobs=None, restrict=True, return_params=False, seasonal=None, sp=1,\n",
+      "        start_params=None, trend=None)\n",
+      "AutoETS(additive_only=False, allow_multiplicative_trend=False, auto=False,\n",
+      "        bounds=None, callback=None, damped_trend=False, dates=None, disp=False,\n",
+      "        error='add', freq=None, full_output=True, information_criterion='aic',\n",
+      "        initial_level=None, initial_seasonal=None, initial_trend=None,\n",
+      "        initialization_method='estimated', maxiter=1000, missing='none',\n",
+      "        n_jobs=None, restrict=True, return_params=False, seasonal='mul', sp=12,\n",
+      "        start_params=None, trend='add')\n"
      ]
     }
    ],
@@ -944,15 +2073,57 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbbd1745c8>",
-      "text/html": "<style  type=\"text/css\" >\n#T_3b36f_row3_col0,#T_3b36f_row3_col1,#T_3b36f_row3_col2,#T_3b36f_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_3b36f_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_3b36f_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_3b36f_row0_col0\" class=\"data row0 col0\" >0.0842</td>\n                        <td id=\"T_3b36f_row0_col1\" class=\"data row0 col1\" >0.0788</td>\n                        <td id=\"T_3b36f_row0_col2\" class=\"data row0 col2\" >32.2722</td>\n                        <td id=\"T_3b36f_row0_col3\" class=\"data row0 col3\" >1922.0432</td>\n            </tr>\n            <tr>\n                        <th id=\"T_3b36f_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_3b36f_row1_col0\" class=\"data row1 col0\" >0.0714</td>\n                        <td id=\"T_3b36f_row1_col1\" class=\"data row1 col1\" >0.0703</td>\n                        <td id=\"T_3b36f_row1_col2\" class=\"data row1 col2\" >28.4732</td>\n                        <td id=\"T_3b36f_row1_col3\" class=\"data row1 col3\" >1387.7209</td>\n            </tr>\n            <tr>\n                        <th id=\"T_3b36f_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_3b36f_row2_col0\" class=\"data row2 col0\" >0.0531</td>\n                        <td id=\"T_3b36f_row2_col1\" class=\"data row2 col1\" >0.0512</td>\n                        <td id=\"T_3b36f_row2_col2\" class=\"data row2 col2\" >24.1642</td>\n                        <td id=\"T_3b36f_row2_col3\" class=\"data row2 col3\" >1209.6651</td>\n            </tr>\n            <tr>\n                        <th id=\"T_3b36f_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_3b36f_row3_col0\" class=\"data row3 col0\" >0.0696</td>\n                        <td id=\"T_3b36f_row3_col1\" class=\"data row3 col1\" >0.0668</td>\n                        <td id=\"T_3b36f_row3_col2\" class=\"data row3 col2\" >28.3032</td>\n                        <td id=\"T_3b36f_row3_col3\" class=\"data row3 col3\" >1506.4764</td>\n            </tr>\n            <tr>\n                        <th id=\"T_3b36f_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_3b36f_row4_col0\" class=\"data row4 col0\" >0.0128</td>\n                        <td id=\"T_3b36f_row4_col1\" class=\"data row4 col1\" >0.0116</td>\n                        <td id=\"T_3b36f_row4_col2\" class=\"data row4 col2\" >3.3123</td>\n                        <td id=\"T_3b36f_row4_col3\" class=\"data row4 col3\" >302.7075</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_c9243_row3_col0,#T_c9243_row3_col1,#T_c9243_row3_col2,#T_c9243_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_c9243_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_c9243_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_c9243_row0_col0\" class=\"data row0 col0\" >0.0836</td>\n",
+       "                        <td id=\"T_c9243_row0_col1\" class=\"data row0 col1\" >0.0780</td>\n",
+       "                        <td id=\"T_c9243_row0_col2\" class=\"data row0 col2\" >32.2003</td>\n",
+       "                        <td id=\"T_c9243_row0_col3\" class=\"data row0 col3\" >2045.6715</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_c9243_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_c9243_row1_col0\" class=\"data row1 col0\" >0.0701</td>\n",
+       "                        <td id=\"T_c9243_row1_col1\" class=\"data row1 col1\" >0.0694</td>\n",
+       "                        <td id=\"T_c9243_row1_col2\" class=\"data row1 col2\" >27.8217</td>\n",
+       "                        <td id=\"T_c9243_row1_col3\" class=\"data row1 col3\" >1179.8993</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_c9243_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_c9243_row2_col0\" class=\"data row2 col0\" >0.0647</td>\n",
+       "                        <td id=\"T_c9243_row2_col1\" class=\"data row2 col1\" >0.0613</td>\n",
+       "                        <td id=\"T_c9243_row2_col2\" class=\"data row2 col2\" >29.5276</td>\n",
+       "                        <td id=\"T_c9243_row2_col3\" class=\"data row2 col3\" >1811.2837</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_c9243_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_c9243_row3_col0\" class=\"data row3 col0\" >0.0728</td>\n",
+       "                        <td id=\"T_c9243_row3_col1\" class=\"data row3 col1\" >0.0696</td>\n",
+       "                        <td id=\"T_c9243_row3_col2\" class=\"data row3 col2\" >29.8499</td>\n",
+       "                        <td id=\"T_c9243_row3_col3\" class=\"data row3 col3\" >1678.9515</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_c9243_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_c9243_row4_col0\" class=\"data row4 col0\" >0.0079</td>\n",
+       "                        <td id=\"T_c9243_row4_col1\" class=\"data row4 col1\" >0.0068</td>\n",
+       "                        <td id=\"T_c9243_row4_col2\" class=\"data row4 col2\" >1.8020</td>\n",
+       "                        <td id=\"T_c9243_row4_col3\" class=\"data row4 col3\" >365.6266</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a3723450>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
        "1960-01    402.724633\n",
@@ -970,8 +2141,9 @@
        "Freq: M, dtype: float64"
       ]
      },
+     "execution_count": 29,
      "metadata": {},
-     "execution_count": 29
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -985,18 +2157,62 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbbb1471c8>",
-      "text/html": "<style  type=\"text/css\" >\n#T_ff928_row3_col0,#T_ff928_row3_col1,#T_ff928_row3_col2,#T_ff928_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_ff928_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_ff928_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_ff928_row0_col0\" class=\"data row0 col0\" >0.0710</td>\n                        <td id=\"T_ff928_row0_col1\" class=\"data row0 col1\" >0.0671</td>\n                        <td id=\"T_ff928_row0_col2\" class=\"data row0 col2\" >27.6002</td>\n                        <td id=\"T_ff928_row0_col3\" class=\"data row0 col3\" >1413.7530</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ff928_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_ff928_row1_col0\" class=\"data row1 col0\" >0.0632</td>\n                        <td id=\"T_ff928_row1_col1\" class=\"data row1 col1\" >0.0611</td>\n                        <td id=\"T_ff928_row1_col2\" class=\"data row1 col2\" >25.7138</td>\n                        <td id=\"T_ff928_row1_col3\" class=\"data row1 col3\" >1386.0933</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ff928_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_ff928_row2_col0\" class=\"data row2 col0\" >0.0440</td>\n                        <td id=\"T_ff928_row2_col1\" class=\"data row2 col1\" >0.0423</td>\n                        <td id=\"T_ff928_row2_col2\" class=\"data row2 col2\" >20.4062</td>\n                        <td id=\"T_ff928_row2_col3\" class=\"data row2 col3\" >1031.4319</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ff928_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_ff928_row3_col0\" class=\"data row3 col0\" >0.0594</td>\n                        <td id=\"T_ff928_row3_col1\" class=\"data row3 col1\" >0.0568</td>\n                        <td id=\"T_ff928_row3_col2\" class=\"data row3 col2\" >24.5734</td>\n                        <td id=\"T_ff928_row3_col3\" class=\"data row3 col3\" >1277.0927</td>\n            </tr>\n            <tr>\n                        <th id=\"T_ff928_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_ff928_row4_col0\" class=\"data row4 col0\" >0.0113</td>\n                        <td id=\"T_ff928_row4_col1\" class=\"data row4 col1\" >0.0105</td>\n                        <td id=\"T_ff928_row4_col2\" class=\"data row4 col2\" >3.0456</td>\n                        <td id=\"T_ff928_row4_col3\" class=\"data row4 col3\" >174.0751</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_e0876_row3_col0,#T_e0876_row3_col1,#T_e0876_row3_col2,#T_e0876_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_e0876_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_e0876_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_e0876_row0_col0\" class=\"data row0 col0\" >0.0720</td>\n",
+       "                        <td id=\"T_e0876_row0_col1\" class=\"data row0 col1\" >0.0676</td>\n",
+       "                        <td id=\"T_e0876_row0_col2\" class=\"data row0 col2\" >28.0965</td>\n",
+       "                        <td id=\"T_e0876_row0_col3\" class=\"data row0 col3\" >1602.5270</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e0876_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_e0876_row1_col0\" class=\"data row1 col0\" >0.0567</td>\n",
+       "                        <td id=\"T_e0876_row1_col1\" class=\"data row1 col1\" >0.0570</td>\n",
+       "                        <td id=\"T_e0876_row1_col2\" class=\"data row1 col2\" >22.1763</td>\n",
+       "                        <td id=\"T_e0876_row1_col3\" class=\"data row1 col3\" >783.4473</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e0876_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_e0876_row2_col0\" class=\"data row2 col0\" >0.0370</td>\n",
+       "                        <td id=\"T_e0876_row2_col1\" class=\"data row2 col1\" >0.0358</td>\n",
+       "                        <td id=\"T_e0876_row2_col2\" class=\"data row2 col2\" >17.2058</td>\n",
+       "                        <td id=\"T_e0876_row2_col3\" class=\"data row2 col3\" >762.0319</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e0876_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_e0876_row3_col0\" class=\"data row3 col0\" >0.0553</td>\n",
+       "                        <td id=\"T_e0876_row3_col1\" class=\"data row3 col1\" >0.0535</td>\n",
+       "                        <td id=\"T_e0876_row3_col2\" class=\"data row3 col2\" >22.4929</td>\n",
+       "                        <td id=\"T_e0876_row3_col3\" class=\"data row3 col3\" >1049.3354</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_e0876_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_e0876_row4_col0\" class=\"data row4 col0\" >0.0143</td>\n",
+       "                        <td id=\"T_e0876_row4_col1\" class=\"data row4 col1\" >0.0132</td>\n",
+       "                        <td id=\"T_e0876_row4_col2\" class=\"data row4 col2\" >4.4517</td>\n",
+       "                        <td id=\"T_e0876_row4_col3\" class=\"data row4 col3\" >391.2632</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a35b3450>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "RandomForestDTS(degree=1, model='additive', sp=1, window_length=10)\nRandomForestDTS(degree=1, model='additive', sp=12, window_length=10)\n"
+      "RandomForestDTS(degree=1, model='additive', sp=1, window_length=10)\n",
+      "RandomForestDTS(degree=1, model='additive', sp=12, window_length=10)\n"
      ]
     }
    ],
@@ -1013,18 +2229,62 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb8ece908>",
-      "text/html": "<style  type=\"text/css\" >\n#T_36175_row3_col0,#T_36175_row3_col1,#T_36175_row3_col2,#T_36175_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_36175_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_36175_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_36175_row0_col0\" class=\"data row0 col0\" >0.0675</td>\n                        <td id=\"T_36175_row0_col1\" class=\"data row0 col1\" >0.0638</td>\n                        <td id=\"T_36175_row0_col2\" class=\"data row0 col2\" >26.3466</td>\n                        <td id=\"T_36175_row0_col3\" class=\"data row0 col3\" >1340.3292</td>\n            </tr>\n            <tr>\n                        <th id=\"T_36175_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_36175_row1_col0\" class=\"data row1 col0\" >0.0644</td>\n                        <td id=\"T_36175_row1_col1\" class=\"data row1 col1\" >0.0623</td>\n                        <td id=\"T_36175_row1_col2\" class=\"data row1 col2\" >26.1375</td>\n                        <td id=\"T_36175_row1_col3\" class=\"data row1 col3\" >1412.2819</td>\n            </tr>\n            <tr>\n                        <th id=\"T_36175_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_36175_row2_col0\" class=\"data row2 col0\" >0.0422</td>\n                        <td id=\"T_36175_row2_col1\" class=\"data row2 col1\" >0.0406</td>\n                        <td id=\"T_36175_row2_col2\" class=\"data row2 col2\" >19.5914</td>\n                        <td id=\"T_36175_row2_col3\" class=\"data row2 col3\" >959.3516</td>\n            </tr>\n            <tr>\n                        <th id=\"T_36175_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_36175_row3_col0\" class=\"data row3 col0\" >0.0580</td>\n                        <td id=\"T_36175_row3_col1\" class=\"data row3 col1\" >0.0556</td>\n                        <td id=\"T_36175_row3_col2\" class=\"data row3 col2\" >24.0252</td>\n                        <td id=\"T_36175_row3_col3\" class=\"data row3 col3\" >1237.3209</td>\n            </tr>\n            <tr>\n                        <th id=\"T_36175_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_36175_row4_col0\" class=\"data row4 col0\" >0.0113</td>\n                        <td id=\"T_36175_row4_col1\" class=\"data row4 col1\" >0.0106</td>\n                        <td id=\"T_36175_row4_col2\" class=\"data row4 col2\" >3.1363</td>\n                        <td id=\"T_36175_row4_col3\" class=\"data row4 col3\" >198.7368</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_f08f9_row3_col0,#T_f08f9_row3_col1,#T_f08f9_row3_col2,#T_f08f9_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_f08f9_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_f08f9_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_f08f9_row0_col0\" class=\"data row0 col0\" >0.0706</td>\n",
+       "                        <td id=\"T_f08f9_row0_col1\" class=\"data row0 col1\" >0.0666</td>\n",
+       "                        <td id=\"T_f08f9_row0_col2\" class=\"data row0 col2\" >27.5114</td>\n",
+       "                        <td id=\"T_f08f9_row0_col3\" class=\"data row0 col3\" >1448.7132</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f08f9_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_f08f9_row1_col0\" class=\"data row1 col0\" >0.0644</td>\n",
+       "                        <td id=\"T_f08f9_row1_col1\" class=\"data row1 col1\" >0.0622</td>\n",
+       "                        <td id=\"T_f08f9_row1_col2\" class=\"data row1 col2\" >26.2056</td>\n",
+       "                        <td id=\"T_f08f9_row1_col3\" class=\"data row1 col3\" >1439.5357</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f08f9_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_f08f9_row2_col0\" class=\"data row2 col0\" >0.0424</td>\n",
+       "                        <td id=\"T_f08f9_row2_col1\" class=\"data row2 col1\" >0.0409</td>\n",
+       "                        <td id=\"T_f08f9_row2_col2\" class=\"data row2 col2\" >19.6544</td>\n",
+       "                        <td id=\"T_f08f9_row2_col3\" class=\"data row2 col3\" >936.0682</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f08f9_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_f08f9_row3_col0\" class=\"data row3 col0\" >0.0591</td>\n",
+       "                        <td id=\"T_f08f9_row3_col1\" class=\"data row3 col1\" >0.0566</td>\n",
+       "                        <td id=\"T_f08f9_row3_col2\" class=\"data row3 col2\" >24.4571</td>\n",
+       "                        <td id=\"T_f08f9_row3_col3\" class=\"data row3 col3\" >1274.7724</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_f08f9_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_f08f9_row4_col0\" class=\"data row4 col0\" >0.0121</td>\n",
+       "                        <td id=\"T_f08f9_row4_col1\" class=\"data row4 col1\" >0.0112</td>\n",
+       "                        <td id=\"T_f08f9_row4_col2\" class=\"data row4 col2\" >3.4376</td>\n",
+       "                        <td id=\"T_f08f9_row4_col3\" class=\"data row4 col3\" >239.5293</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e59a7610>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     },
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
-      "RandomForestDTS(degree=1, model='additive', sp=1, window_length=10)\nRandomForestDTS(degree=1, model='additive', sp=12, window_length=10)\n"
+      "RandomForestDTS(degree=1, model='additive', sp=1, window_length=10)\n",
+      "RandomForestDTS(degree=1, model='additive', sp=12, window_length=10)\n"
      ]
     }
    ],
@@ -1036,13 +2296,13 @@
    ]
   },
   {
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "## Tune Models\n",
     "\n",
     "Shown above"
-   ],
-   "cell_type": "markdown",
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "markdown",
@@ -1057,12 +2317,55 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbbb0ee108>",
-      "text/html": "<style  type=\"text/css\" >\n#T_4a016_row3_col0,#T_4a016_row3_col1,#T_4a016_row3_col2,#T_4a016_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_4a016_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_4a016_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_4a016_row0_col0\" class=\"data row0 col0\" >0.1766</td>\n                        <td id=\"T_4a016_row0_col1\" class=\"data row0 col1\" >0.1549</td>\n                        <td id=\"T_4a016_row0_col2\" class=\"data row0 col2\" >63.4167</td>\n                        <td id=\"T_4a016_row0_col3\" class=\"data row0 col3\" >6967.9167</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4a016_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_4a016_row1_col0\" class=\"data row1 col0\" >0.1351</td>\n                        <td id=\"T_4a016_row1_col1\" class=\"data row1 col1\" >0.1205</td>\n                        <td id=\"T_4a016_row1_col2\" class=\"data row1 col2\" >52.3333</td>\n                        <td id=\"T_4a016_row1_col3\" class=\"data row1 col3\" >5842.1667</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4a016_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_4a016_row2_col0\" class=\"data row2 col0\" >0.2259</td>\n                        <td id=\"T_4a016_row2_col1\" class=\"data row2 col1\" >0.1954</td>\n                        <td id=\"T_4a016_row2_col2\" class=\"data row2 col2\" >91.3333</td>\n                        <td id=\"T_4a016_row2_col3\" class=\"data row2 col3\" >12811.6667</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4a016_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_4a016_row3_col0\" class=\"data row3 col0\" >0.1792</td>\n                        <td id=\"T_4a016_row3_col1\" class=\"data row3 col1\" >0.1569</td>\n                        <td id=\"T_4a016_row3_col2\" class=\"data row3 col2\" >69.0278</td>\n                        <td id=\"T_4a016_row3_col3\" class=\"data row3 col3\" >8540.5833</td>\n            </tr>\n            <tr>\n                        <th id=\"T_4a016_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_4a016_row4_col0\" class=\"data row4 col0\" >0.0371</td>\n                        <td id=\"T_4a016_row4_col1\" class=\"data row4 col1\" >0.0306</td>\n                        <td id=\"T_4a016_row4_col2\" class=\"data row4 col2\" >16.4086</td>\n                        <td id=\"T_4a016_row4_col3\" class=\"data row4 col3\" >3054.8806</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_06dd9_row3_col0,#T_06dd9_row3_col1,#T_06dd9_row3_col2,#T_06dd9_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_06dd9_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_06dd9_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_06dd9_row0_col0\" class=\"data row0 col0\" >0.1766</td>\n",
+       "                        <td id=\"T_06dd9_row0_col1\" class=\"data row0 col1\" >0.1549</td>\n",
+       "                        <td id=\"T_06dd9_row0_col2\" class=\"data row0 col2\" >63.4167</td>\n",
+       "                        <td id=\"T_06dd9_row0_col3\" class=\"data row0 col3\" >6967.9167</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06dd9_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_06dd9_row1_col0\" class=\"data row1 col0\" >0.1351</td>\n",
+       "                        <td id=\"T_06dd9_row1_col1\" class=\"data row1 col1\" >0.1205</td>\n",
+       "                        <td id=\"T_06dd9_row1_col2\" class=\"data row1 col2\" >52.3333</td>\n",
+       "                        <td id=\"T_06dd9_row1_col3\" class=\"data row1 col3\" >5842.1667</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06dd9_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_06dd9_row2_col0\" class=\"data row2 col0\" >0.2259</td>\n",
+       "                        <td id=\"T_06dd9_row2_col1\" class=\"data row2 col1\" >0.1954</td>\n",
+       "                        <td id=\"T_06dd9_row2_col2\" class=\"data row2 col2\" >91.3333</td>\n",
+       "                        <td id=\"T_06dd9_row2_col3\" class=\"data row2 col3\" >12811.6667</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06dd9_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_06dd9_row3_col0\" class=\"data row3 col0\" >0.1792</td>\n",
+       "                        <td id=\"T_06dd9_row3_col1\" class=\"data row3 col1\" >0.1569</td>\n",
+       "                        <td id=\"T_06dd9_row3_col2\" class=\"data row3 col2\" >69.0278</td>\n",
+       "                        <td id=\"T_06dd9_row3_col3\" class=\"data row3 col3\" >8540.5833</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_06dd9_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_06dd9_row4_col0\" class=\"data row4 col0\" >0.0371</td>\n",
+       "                        <td id=\"T_06dd9_row4_col1\" class=\"data row4 col1\" >0.0306</td>\n",
+       "                        <td id=\"T_06dd9_row4_col2\" class=\"data row4 col2\" >16.4086</td>\n",
+       "                        <td id=\"T_06dd9_row4_col3\" class=\"data row4 col3\" >3054.8806</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e5a28250>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -1076,12 +2379,55 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbbb11af88>",
-      "text/html": "<style  type=\"text/css\" >\n#T_8eede_row3_col0,#T_8eede_row3_col1,#T_8eede_row3_col2,#T_8eede_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_8eede_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_8eede_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_8eede_row0_col0\" class=\"data row0 col0\" >0.2133</td>\n                        <td id=\"T_8eede_row0_col1\" class=\"data row0 col1\" >0.1848</td>\n                        <td id=\"T_8eede_row0_col2\" class=\"data row0 col2\" >74.5645</td>\n                        <td id=\"T_8eede_row0_col3\" class=\"data row0 col3\" >8799.7367</td>\n            </tr>\n            <tr>\n                        <th id=\"T_8eede_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_8eede_row1_col0\" class=\"data row1 col0\" >0.1599</td>\n                        <td id=\"T_8eede_row1_col1\" class=\"data row1 col1\" >0.1404</td>\n                        <td id=\"T_8eede_row1_col2\" class=\"data row1 col2\" >60.6337</td>\n                        <td id=\"T_8eede_row1_col3\" class=\"data row1 col3\" >7259.3401</td>\n            </tr>\n            <tr>\n                        <th id=\"T_8eede_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_8eede_row2_col0\" class=\"data row2 col0\" >0.2604</td>\n                        <td id=\"T_8eede_row2_col1\" class=\"data row2 col1\" >0.2225</td>\n                        <td id=\"T_8eede_row2_col2\" class=\"data row2 col2\" >102.9813</td>\n                        <td id=\"T_8eede_row2_col3\" class=\"data row2 col3\" >15344.8781</td>\n            </tr>\n            <tr>\n                        <th id=\"T_8eede_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_8eede_row3_col0\" class=\"data row3 col0\" >0.2112</td>\n                        <td id=\"T_8eede_row3_col1\" class=\"data row3 col1\" >0.1826</td>\n                        <td id=\"T_8eede_row3_col2\" class=\"data row3 col2\" >79.3932</td>\n                        <td id=\"T_8eede_row3_col3\" class=\"data row3 col3\" >10467.9849</td>\n            </tr>\n            <tr>\n                        <th id=\"T_8eede_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_8eede_row4_col0\" class=\"data row4 col0\" >0.0411</td>\n                        <td id=\"T_8eede_row4_col1\" class=\"data row4 col1\" >0.0336</td>\n                        <td id=\"T_8eede_row4_col2\" class=\"data row4 col2\" >17.6223</td>\n                        <td id=\"T_8eede_row4_col3\" class=\"data row4 col3\" >3505.3550</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_14f50_row3_col0,#T_14f50_row3_col1,#T_14f50_row3_col2,#T_14f50_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_14f50_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_14f50_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_14f50_row0_col0\" class=\"data row0 col0\" >0.2133</td>\n",
+       "                        <td id=\"T_14f50_row0_col1\" class=\"data row0 col1\" >0.1848</td>\n",
+       "                        <td id=\"T_14f50_row0_col2\" class=\"data row0 col2\" >74.5645</td>\n",
+       "                        <td id=\"T_14f50_row0_col3\" class=\"data row0 col3\" >8799.7367</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_14f50_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_14f50_row1_col0\" class=\"data row1 col0\" >0.1599</td>\n",
+       "                        <td id=\"T_14f50_row1_col1\" class=\"data row1 col1\" >0.1404</td>\n",
+       "                        <td id=\"T_14f50_row1_col2\" class=\"data row1 col2\" >60.6337</td>\n",
+       "                        <td id=\"T_14f50_row1_col3\" class=\"data row1 col3\" >7259.3400</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_14f50_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_14f50_row2_col0\" class=\"data row2 col0\" >0.2604</td>\n",
+       "                        <td id=\"T_14f50_row2_col1\" class=\"data row2 col1\" >0.2225</td>\n",
+       "                        <td id=\"T_14f50_row2_col2\" class=\"data row2 col2\" >102.9813</td>\n",
+       "                        <td id=\"T_14f50_row2_col3\" class=\"data row2 col3\" >15344.8780</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_14f50_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_14f50_row3_col0\" class=\"data row3 col0\" >0.2112</td>\n",
+       "                        <td id=\"T_14f50_row3_col1\" class=\"data row3 col1\" >0.1826</td>\n",
+       "                        <td id=\"T_14f50_row3_col2\" class=\"data row3 col2\" >79.3932</td>\n",
+       "                        <td id=\"T_14f50_row3_col3\" class=\"data row3 col3\" >10467.9849</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_14f50_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_14f50_row4_col0\" class=\"data row4 col0\" >0.0411</td>\n",
+       "                        <td id=\"T_14f50_row4_col1\" class=\"data row4 col1\" >0.0336</td>\n",
+       "                        <td id=\"T_14f50_row4_col2\" class=\"data row4 col2\" >17.6223</td>\n",
+       "                        <td id=\"T_14f50_row4_col3\" class=\"data row4 col3\" >3505.3550</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1a3590890>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -1094,12 +2440,55 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbbc198a08>",
-      "text/html": "<style  type=\"text/css\" >\n#T_79744_row3_col0,#T_79744_row3_col1,#T_79744_row3_col2,#T_79744_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_79744_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_79744_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_79744_row0_col0\" class=\"data row0 col0\" >0.2133</td>\n                        <td id=\"T_79744_row0_col1\" class=\"data row0 col1\" >0.1848</td>\n                        <td id=\"T_79744_row0_col2\" class=\"data row0 col2\" >74.5645</td>\n                        <td id=\"T_79744_row0_col3\" class=\"data row0 col3\" >8799.7367</td>\n            </tr>\n            <tr>\n                        <th id=\"T_79744_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_79744_row1_col0\" class=\"data row1 col0\" >0.1599</td>\n                        <td id=\"T_79744_row1_col1\" class=\"data row1 col1\" >0.1404</td>\n                        <td id=\"T_79744_row1_col2\" class=\"data row1 col2\" >60.6337</td>\n                        <td id=\"T_79744_row1_col3\" class=\"data row1 col3\" >7259.3401</td>\n            </tr>\n            <tr>\n                        <th id=\"T_79744_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_79744_row2_col0\" class=\"data row2 col0\" >0.2604</td>\n                        <td id=\"T_79744_row2_col1\" class=\"data row2 col1\" >0.2225</td>\n                        <td id=\"T_79744_row2_col2\" class=\"data row2 col2\" >102.9813</td>\n                        <td id=\"T_79744_row2_col3\" class=\"data row2 col3\" >15344.8781</td>\n            </tr>\n            <tr>\n                        <th id=\"T_79744_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_79744_row3_col0\" class=\"data row3 col0\" >0.2112</td>\n                        <td id=\"T_79744_row3_col1\" class=\"data row3 col1\" >0.1826</td>\n                        <td id=\"T_79744_row3_col2\" class=\"data row3 col2\" >79.3932</td>\n                        <td id=\"T_79744_row3_col3\" class=\"data row3 col3\" >10467.9849</td>\n            </tr>\n            <tr>\n                        <th id=\"T_79744_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_79744_row4_col0\" class=\"data row4 col0\" >0.0411</td>\n                        <td id=\"T_79744_row4_col1\" class=\"data row4 col1\" >0.0336</td>\n                        <td id=\"T_79744_row4_col2\" class=\"data row4 col2\" >17.6223</td>\n                        <td id=\"T_79744_row4_col3\" class=\"data row4 col3\" >3505.3550</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_9e557_row3_col0,#T_9e557_row3_col1,#T_9e557_row3_col2,#T_9e557_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_9e557_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_9e557_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_9e557_row0_col0\" class=\"data row0 col0\" >0.2133</td>\n",
+       "                        <td id=\"T_9e557_row0_col1\" class=\"data row0 col1\" >0.1848</td>\n",
+       "                        <td id=\"T_9e557_row0_col2\" class=\"data row0 col2\" >74.5645</td>\n",
+       "                        <td id=\"T_9e557_row0_col3\" class=\"data row0 col3\" >8799.7367</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_9e557_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_9e557_row1_col0\" class=\"data row1 col0\" >0.1599</td>\n",
+       "                        <td id=\"T_9e557_row1_col1\" class=\"data row1 col1\" >0.1404</td>\n",
+       "                        <td id=\"T_9e557_row1_col2\" class=\"data row1 col2\" >60.6337</td>\n",
+       "                        <td id=\"T_9e557_row1_col3\" class=\"data row1 col3\" >7259.3400</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_9e557_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_9e557_row2_col0\" class=\"data row2 col0\" >0.2604</td>\n",
+       "                        <td id=\"T_9e557_row2_col1\" class=\"data row2 col1\" >0.2225</td>\n",
+       "                        <td id=\"T_9e557_row2_col2\" class=\"data row2 col2\" >102.9813</td>\n",
+       "                        <td id=\"T_9e557_row2_col3\" class=\"data row2 col3\" >15344.8780</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_9e557_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_9e557_row3_col0\" class=\"data row3 col0\" >0.2112</td>\n",
+       "                        <td id=\"T_9e557_row3_col1\" class=\"data row3 col1\" >0.1826</td>\n",
+       "                        <td id=\"T_9e557_row3_col2\" class=\"data row3 col2\" >79.3932</td>\n",
+       "                        <td id=\"T_9e557_row3_col3\" class=\"data row3 col3\" >10467.9849</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_9e557_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_9e557_row4_col0\" class=\"data row4 col0\" >0.0411</td>\n",
+       "                        <td id=\"T_9e557_row4_col1\" class=\"data row4 col1\" >0.0336</td>\n",
+       "                        <td id=\"T_9e557_row4_col2\" class=\"data row4 col2\" >17.6223</td>\n",
+       "                        <td id=\"T_9e557_row4_col3\" class=\"data row4 col3\" >3505.3550</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e59a7850>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -1112,18 +2501,306 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "display_data",
      "data": {
-      "text/plain": "<pandas.io.formats.style.Styler at 0x1cbb90066c8>",
-      "text/html": "<style  type=\"text/css\" >\n#T_1a1de_row3_col0,#T_1a1de_row3_col1,#T_1a1de_row3_col2,#T_1a1de_row3_col3{\n            background:  yellow;\n        }</style><table id=\"T_1a1de_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n                <tr>\n                        <th id=\"T_1a1de_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n                        <td id=\"T_1a1de_row0_col0\" class=\"data row0 col0\" >0.2236</td>\n                        <td id=\"T_1a1de_row0_col1\" class=\"data row0 col1\" >0.1930</td>\n                        <td id=\"T_1a1de_row0_col2\" class=\"data row0 col2\" >77.6065</td>\n                        <td id=\"T_1a1de_row0_col3\" class=\"data row0 col3\" >9340.7390</td>\n            </tr>\n            <tr>\n                        <th id=\"T_1a1de_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n                        <td id=\"T_1a1de_row1_col0\" class=\"data row1 col0\" >0.1666</td>\n                        <td id=\"T_1a1de_row1_col1\" class=\"data row1 col1\" >0.1456</td>\n                        <td id=\"T_1a1de_row1_col2\" class=\"data row1 col2\" >62.8180</td>\n                        <td id=\"T_1a1de_row1_col3\" class=\"data row1 col3\" >7694.2862</td>\n            </tr>\n            <tr>\n                        <th id=\"T_1a1de_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n                        <td id=\"T_1a1de_row2_col0\" class=\"data row2 col0\" >0.2697</td>\n                        <td id=\"T_1a1de_row2_col1\" class=\"data row2 col1\" >0.2296</td>\n                        <td id=\"T_1a1de_row2_col2\" class=\"data row2 col2\" >106.0465</td>\n                        <td id=\"T_1a1de_row2_col3\" class=\"data row2 col3\" >16066.9864</td>\n            </tr>\n            <tr>\n                        <th id=\"T_1a1de_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n                        <td id=\"T_1a1de_row3_col0\" class=\"data row3 col0\" >0.2200</td>\n                        <td id=\"T_1a1de_row3_col1\" class=\"data row3 col1\" >0.1894</td>\n                        <td id=\"T_1a1de_row3_col2\" class=\"data row3 col2\" >82.1570</td>\n                        <td id=\"T_1a1de_row3_col3\" class=\"data row3 col3\" >11034.0039</td>\n            </tr>\n            <tr>\n                        <th id=\"T_1a1de_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n                        <td id=\"T_1a1de_row4_col0\" class=\"data row4 col0\" >0.0422</td>\n                        <td id=\"T_1a1de_row4_col1\" class=\"data row4 col1\" >0.0344</td>\n                        <td id=\"T_1a1de_row4_col2\" class=\"data row4 col2\" >17.9389</td>\n                        <td id=\"T_1a1de_row4_col3\" class=\"data row4 col3\" >3621.7755</td>\n            </tr>\n    </tbody></table>"
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "#T_435de_row3_col0,#T_435de_row3_col1,#T_435de_row3_col2,#T_435de_row3_col3{\n",
+       "            background:  yellow;\n",
+       "        }</style><table id=\"T_435de_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >smape</th>        <th class=\"col_heading level0 col1\" >mape</th>        <th class=\"col_heading level0 col2\" >mae</th>        <th class=\"col_heading level0 col3\" >rmse</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_435de_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_435de_row0_col0\" class=\"data row0 col0\" >0.2236</td>\n",
+       "                        <td id=\"T_435de_row0_col1\" class=\"data row0 col1\" >0.1930</td>\n",
+       "                        <td id=\"T_435de_row0_col2\" class=\"data row0 col2\" >77.6065</td>\n",
+       "                        <td id=\"T_435de_row0_col3\" class=\"data row0 col3\" >9340.7390</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_435de_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_435de_row1_col0\" class=\"data row1 col0\" >0.1666</td>\n",
+       "                        <td id=\"T_435de_row1_col1\" class=\"data row1 col1\" >0.1456</td>\n",
+       "                        <td id=\"T_435de_row1_col2\" class=\"data row1 col2\" >62.8180</td>\n",
+       "                        <td id=\"T_435de_row1_col3\" class=\"data row1 col3\" >7694.2862</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_435de_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_435de_row2_col0\" class=\"data row2 col0\" >0.2697</td>\n",
+       "                        <td id=\"T_435de_row2_col1\" class=\"data row2 col1\" >0.2296</td>\n",
+       "                        <td id=\"T_435de_row2_col2\" class=\"data row2 col2\" >106.0465</td>\n",
+       "                        <td id=\"T_435de_row2_col3\" class=\"data row2 col3\" >16066.9863</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_435de_level0_row3\" class=\"row_heading level0 row3\" >Mean</th>\n",
+       "                        <td id=\"T_435de_row3_col0\" class=\"data row3 col0\" >0.2200</td>\n",
+       "                        <td id=\"T_435de_row3_col1\" class=\"data row3 col1\" >0.1894</td>\n",
+       "                        <td id=\"T_435de_row3_col2\" class=\"data row3 col2\" >82.1570</td>\n",
+       "                        <td id=\"T_435de_row3_col3\" class=\"data row3 col3\" >11034.0038</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_435de_level0_row4\" class=\"row_heading level0 row4\" >SD</th>\n",
+       "                        <td id=\"T_435de_row4_col0\" class=\"data row4 col0\" >0.0422</td>\n",
+       "                        <td id=\"T_435de_row4_col1\" class=\"data row4 col1\" >0.0344</td>\n",
+       "                        <td id=\"T_435de_row4_col2\" class=\"data row4 col2\" >17.9389</td>\n",
+       "                        <td id=\"T_435de_row4_col3\" class=\"data row4 col3\" >3621.7755</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e595bb10>"
+      ]
      },
-     "metadata": {}
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
     "voting_blender = exp.blend_models([arima_model, naive_model], method='voting', weights=[1.2, 0.7])"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Compare Models"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "    #T_36d4d_ th {\n",
+       "          text-align: left;\n",
+       "    }#T_36d4d_row0_col0,#T_36d4d_row1_col0,#T_36d4d_row1_col1,#T_36d4d_row1_col2,#T_36d4d_row1_col3,#T_36d4d_row1_col4,#T_36d4d_row2_col0,#T_36d4d_row2_col1,#T_36d4d_row2_col2,#T_36d4d_row2_col3,#T_36d4d_row2_col4,#T_36d4d_row3_col0,#T_36d4d_row3_col1,#T_36d4d_row3_col2,#T_36d4d_row3_col3,#T_36d4d_row3_col4,#T_36d4d_row4_col0,#T_36d4d_row4_col1,#T_36d4d_row4_col2,#T_36d4d_row4_col3,#T_36d4d_row4_col4,#T_36d4d_row5_col0,#T_36d4d_row5_col1,#T_36d4d_row5_col2,#T_36d4d_row5_col3,#T_36d4d_row5_col4,#T_36d4d_row6_col0,#T_36d4d_row6_col1,#T_36d4d_row6_col2,#T_36d4d_row6_col3,#T_36d4d_row6_col4{\n",
+       "            text-align:  left;\n",
+       "            text-align:  left;\n",
+       "        }#T_36d4d_row0_col1,#T_36d4d_row0_col2,#T_36d4d_row0_col3,#T_36d4d_row0_col4{\n",
+       "            text-align:  left;\n",
+       "            text-align:  left;\n",
+       "            background-color:  yellow;\n",
+       "        }#T_36d4d_row0_col5,#T_36d4d_row1_col5,#T_36d4d_row2_col5,#T_36d4d_row4_col5,#T_36d4d_row5_col5,#T_36d4d_row6_col5{\n",
+       "            text-align:  left;\n",
+       "            text-align:  left;\n",
+       "            background-color:  lightgrey;\n",
+       "        }#T_36d4d_row3_col5{\n",
+       "            text-align:  left;\n",
+       "            text-align:  left;\n",
+       "            background-color:  yellow;\n",
+       "            background-color:  lightgrey;\n",
+       "        }</style><table id=\"T_36d4d_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Model</th>        <th class=\"col_heading level0 col1\" >smape</th>        <th class=\"col_heading level0 col2\" >mape</th>        <th class=\"col_heading level0 col3\" >mae</th>        <th class=\"col_heading level0 col4\" >rmse</th>        <th class=\"col_heading level0 col5\" >TT (Sec)</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_36d4d_level0_row0\" class=\"row_heading level0 row0\" >rf_dts</th>\n",
+       "                        <td id=\"T_36d4d_row0_col0\" class=\"data row0 col0\" >RandomForestDTS</td>\n",
+       "                        <td id=\"T_36d4d_row0_col1\" class=\"data row0 col1\" >0.0744</td>\n",
+       "                        <td id=\"T_36d4d_row0_col2\" class=\"data row0 col2\" >0.0723</td>\n",
+       "                        <td id=\"T_36d4d_row0_col3\" class=\"data row0 col3\" >29.7546</td>\n",
+       "                        <td id=\"T_36d4d_row0_col4\" class=\"data row0 col4\" >1533.3301</td>\n",
+       "                        <td id=\"T_36d4d_row0_col5\" class=\"data row0 col5\" >0.1467</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_36d4d_level0_row1\" class=\"row_heading level0 row1\" >poly_trend</th>\n",
+       "                        <td id=\"T_36d4d_row1_col0\" class=\"data row1 col0\" >PolyTrend</td>\n",
+       "                        <td id=\"T_36d4d_row1_col1\" class=\"data row1 col1\" >0.1235</td>\n",
+       "                        <td id=\"T_36d4d_row1_col2\" class=\"data row1 col2\" >0.1202</td>\n",
+       "                        <td id=\"T_36d4d_row1_col3\" class=\"data row1 col3\" >49.3594</td>\n",
+       "                        <td id=\"T_36d4d_row1_col4\" class=\"data row1 col4\" >3970.8719</td>\n",
+       "                        <td id=\"T_36d4d_row1_col5\" class=\"data row1 col5\" >0.0133</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_36d4d_level0_row2\" class=\"row_heading level0 row2\" >theta</th>\n",
+       "                        <td id=\"T_36d4d_row2_col0\" class=\"data row2 col0\" >Theta</td>\n",
+       "                        <td id=\"T_36d4d_row2_col1\" class=\"data row2 col1\" >0.1600</td>\n",
+       "                        <td id=\"T_36d4d_row2_col2\" class=\"data row2 col2\" >0.1419</td>\n",
+       "                        <td id=\"T_36d4d_row2_col3\" class=\"data row2 col3\" >62.5320</td>\n",
+       "                        <td id=\"T_36d4d_row2_col4\" class=\"data row2 col4\" >7287.7015</td>\n",
+       "                        <td id=\"T_36d4d_row2_col5\" class=\"data row2 col5\" >0.0133</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_36d4d_level0_row3\" class=\"row_heading level0 row3\" >naive</th>\n",
+       "                        <td id=\"T_36d4d_row3_col0\" class=\"data row3 col0\" >Naive</td>\n",
+       "                        <td id=\"T_36d4d_row3_col1\" class=\"data row3 col1\" >0.1792</td>\n",
+       "                        <td id=\"T_36d4d_row3_col2\" class=\"data row3 col2\" >0.1569</td>\n",
+       "                        <td id=\"T_36d4d_row3_col3\" class=\"data row3 col3\" >69.0278</td>\n",
+       "                        <td id=\"T_36d4d_row3_col4\" class=\"data row3 col4\" >8540.5833</td>\n",
+       "                        <td id=\"T_36d4d_row3_col5\" class=\"data row3 col5\" >0.0100</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_36d4d_level0_row4\" class=\"row_heading level0 row4\" >auto_ets</th>\n",
+       "                        <td id=\"T_36d4d_row4_col0\" class=\"data row4 col0\" >AutoETS</td>\n",
+       "                        <td id=\"T_36d4d_row4_col1\" class=\"data row4 col1\" >0.1792</td>\n",
+       "                        <td id=\"T_36d4d_row4_col2\" class=\"data row4 col2\" >0.1569</td>\n",
+       "                        <td id=\"T_36d4d_row4_col3\" class=\"data row4 col3\" >69.0301</td>\n",
+       "                        <td id=\"T_36d4d_row4_col4\" class=\"data row4 col4\" >8540.9863</td>\n",
+       "                        <td id=\"T_36d4d_row4_col5\" class=\"data row4 col5\" >0.0167</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_36d4d_level0_row5\" class=\"row_heading level0 row5\" >exp_smooth</th>\n",
+       "                        <td id=\"T_36d4d_row5_col0\" class=\"data row5 col0\" >ExponentialSmoothing</td>\n",
+       "                        <td id=\"T_36d4d_row5_col1\" class=\"data row5 col1\" >0.1794</td>\n",
+       "                        <td id=\"T_36d4d_row5_col2\" class=\"data row5 col2\" >0.1571</td>\n",
+       "                        <td id=\"T_36d4d_row5_col3\" class=\"data row5 col3\" >69.1088</td>\n",
+       "                        <td id=\"T_36d4d_row5_col4\" class=\"data row5 col4\" >8553.6666</td>\n",
+       "                        <td id=\"T_36d4d_row5_col5\" class=\"data row5 col5\" >0.0167</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_36d4d_level0_row6\" class=\"row_heading level0 row6\" >arima</th>\n",
+       "                        <td id=\"T_36d4d_row6_col0\" class=\"data row6 col0\" >ARIMA</td>\n",
+       "                        <td id=\"T_36d4d_row6_col1\" class=\"data row6 col1\" >0.2497</td>\n",
+       "                        <td id=\"T_36d4d_row6_col2\" class=\"data row6 col2\" >0.2128</td>\n",
+       "                        <td id=\"T_36d4d_row6_col3\" class=\"data row6 col3\" >91.3284</td>\n",
+       "                        <td id=\"T_36d4d_row6_col4\" class=\"data row6 col4\" >12864.4375</td>\n",
+       "                        <td id=\"T_36d4d_row6_col5\" class=\"data row6 col5\" >0.0433</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e5a280d0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[RandomForestDTS(degree=1, model='additive', sp=1, window_length=10),\n",
+       " PolynomialTrendForecaster(degree=1, regressor=None, with_intercept=True)]"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "exp.setup(data=y, fh=fh, fold=fold, fold_strategy='slidingwindow')\n",
+    "\n",
+    "best_models = exp.compare_models(fold=fold, sort='rmse', n_select=2)\n",
+    "best_models"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "    #T_ec6de_ th {\n",
+       "          text-align: left;\n",
+       "    }#T_ec6de_row0_col0,#T_ec6de_row1_col0,#T_ec6de_row1_col1,#T_ec6de_row1_col2,#T_ec6de_row1_col3,#T_ec6de_row1_col4,#T_ec6de_row2_col0,#T_ec6de_row2_col1,#T_ec6de_row2_col2,#T_ec6de_row2_col3,#T_ec6de_row2_col4,#T_ec6de_row3_col0,#T_ec6de_row3_col1,#T_ec6de_row3_col2,#T_ec6de_row3_col3,#T_ec6de_row3_col4,#T_ec6de_row4_col0,#T_ec6de_row4_col1,#T_ec6de_row4_col2,#T_ec6de_row4_col3,#T_ec6de_row4_col4,#T_ec6de_row5_col0,#T_ec6de_row5_col1,#T_ec6de_row5_col2,#T_ec6de_row5_col3,#T_ec6de_row5_col4,#T_ec6de_row6_col0,#T_ec6de_row6_col1,#T_ec6de_row6_col2,#T_ec6de_row6_col3,#T_ec6de_row6_col4{\n",
+       "            text-align:  left;\n",
+       "            text-align:  left;\n",
+       "        }#T_ec6de_row0_col1,#T_ec6de_row0_col2,#T_ec6de_row0_col3,#T_ec6de_row0_col4{\n",
+       "            text-align:  left;\n",
+       "            text-align:  left;\n",
+       "            background-color:  yellow;\n",
+       "        }#T_ec6de_row0_col5,#T_ec6de_row1_col5,#T_ec6de_row2_col5,#T_ec6de_row4_col5,#T_ec6de_row5_col5,#T_ec6de_row6_col5{\n",
+       "            text-align:  left;\n",
+       "            text-align:  left;\n",
+       "            background-color:  lightgrey;\n",
+       "        }#T_ec6de_row3_col5{\n",
+       "            text-align:  left;\n",
+       "            text-align:  left;\n",
+       "            background-color:  yellow;\n",
+       "            background-color:  lightgrey;\n",
+       "        }</style><table id=\"T_ec6de_\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Model</th>        <th class=\"col_heading level0 col1\" >smape</th>        <th class=\"col_heading level0 col2\" >mape</th>        <th class=\"col_heading level0 col3\" >mae</th>        <th class=\"col_heading level0 col4\" >rmse</th>        <th class=\"col_heading level0 col5\" >TT (Sec)</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_ec6de_level0_row0\" class=\"row_heading level0 row0\" >rf_dts</th>\n",
+       "                        <td id=\"T_ec6de_row0_col0\" class=\"data row0 col0\" >RandomForestDTS</td>\n",
+       "                        <td id=\"T_ec6de_row0_col1\" class=\"data row0 col1\" >0.0652</td>\n",
+       "                        <td id=\"T_ec6de_row0_col2\" class=\"data row0 col2\" >0.0629</td>\n",
+       "                        <td id=\"T_ec6de_row0_col3\" class=\"data row0 col3\" >26.5238</td>\n",
+       "                        <td id=\"T_ec6de_row0_col4\" class=\"data row0 col4\" >1287.9684</td>\n",
+       "                        <td id=\"T_ec6de_row0_col5\" class=\"data row0 col5\" >0.1600</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_ec6de_level0_row1\" class=\"row_heading level0 row1\" >poly_trend</th>\n",
+       "                        <td id=\"T_ec6de_row1_col0\" class=\"data row1 col0\" >PolyTrend</td>\n",
+       "                        <td id=\"T_ec6de_row1_col1\" class=\"data row1 col1\" >0.1216</td>\n",
+       "                        <td id=\"T_ec6de_row1_col2\" class=\"data row1 col2\" >0.1170</td>\n",
+       "                        <td id=\"T_ec6de_row1_col3\" class=\"data row1 col3\" >48.6301</td>\n",
+       "                        <td id=\"T_ec6de_row1_col4\" class=\"data row1 col4\" >4031.3261</td>\n",
+       "                        <td id=\"T_ec6de_row1_col5\" class=\"data row1 col5\" >0.0100</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_ec6de_level0_row2\" class=\"row_heading level0 row2\" >theta</th>\n",
+       "                        <td id=\"T_ec6de_row2_col0\" class=\"data row2 col0\" >Theta</td>\n",
+       "                        <td id=\"T_ec6de_row2_col1\" class=\"data row2 col1\" >0.1607</td>\n",
+       "                        <td id=\"T_ec6de_row2_col2\" class=\"data row2 col2\" >0.1425</td>\n",
+       "                        <td id=\"T_ec6de_row2_col3\" class=\"data row2 col3\" >62.7733</td>\n",
+       "                        <td id=\"T_ec6de_row2_col4\" class=\"data row2 col4\" >7332.4303</td>\n",
+       "                        <td id=\"T_ec6de_row2_col5\" class=\"data row2 col5\" >0.0100</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_ec6de_level0_row3\" class=\"row_heading level0 row3\" >naive</th>\n",
+       "                        <td id=\"T_ec6de_row3_col0\" class=\"data row3 col0\" >Naive</td>\n",
+       "                        <td id=\"T_ec6de_row3_col1\" class=\"data row3 col1\" >0.1792</td>\n",
+       "                        <td id=\"T_ec6de_row3_col2\" class=\"data row3 col2\" >0.1569</td>\n",
+       "                        <td id=\"T_ec6de_row3_col3\" class=\"data row3 col3\" >69.0278</td>\n",
+       "                        <td id=\"T_ec6de_row3_col4\" class=\"data row3 col4\" >8540.5833</td>\n",
+       "                        <td id=\"T_ec6de_row3_col5\" class=\"data row3 col5\" >0.0067</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_ec6de_level0_row4\" class=\"row_heading level0 row4\" >auto_ets</th>\n",
+       "                        <td id=\"T_ec6de_row4_col0\" class=\"data row4 col0\" >AutoETS</td>\n",
+       "                        <td id=\"T_ec6de_row4_col1\" class=\"data row4 col1\" >0.1792</td>\n",
+       "                        <td id=\"T_ec6de_row4_col2\" class=\"data row4 col2\" >0.1569</td>\n",
+       "                        <td id=\"T_ec6de_row4_col3\" class=\"data row4 col3\" >69.0301</td>\n",
+       "                        <td id=\"T_ec6de_row4_col4\" class=\"data row4 col4\" >8540.9863</td>\n",
+       "                        <td id=\"T_ec6de_row4_col5\" class=\"data row4 col5\" >0.0100</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_ec6de_level0_row5\" class=\"row_heading level0 row5\" >exp_smooth</th>\n",
+       "                        <td id=\"T_ec6de_row5_col0\" class=\"data row5 col0\" >ExponentialSmoothing</td>\n",
+       "                        <td id=\"T_ec6de_row5_col1\" class=\"data row5 col1\" >0.1793</td>\n",
+       "                        <td id=\"T_ec6de_row5_col2\" class=\"data row5 col2\" >0.1570</td>\n",
+       "                        <td id=\"T_ec6de_row5_col3\" class=\"data row5 col3\" >69.0724</td>\n",
+       "                        <td id=\"T_ec6de_row5_col4\" class=\"data row5 col4\" >8548.7344</td>\n",
+       "                        <td id=\"T_ec6de_row5_col5\" class=\"data row5 col5\" >0.0100</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_ec6de_level0_row6\" class=\"row_heading level0 row6\" >arima</th>\n",
+       "                        <td id=\"T_ec6de_row6_col0\" class=\"data row6 col0\" >ARIMA</td>\n",
+       "                        <td id=\"T_ec6de_row6_col1\" class=\"data row6 col1\" >0.2479</td>\n",
+       "                        <td id=\"T_ec6de_row6_col2\" class=\"data row6 col2\" >0.2114</td>\n",
+       "                        <td id=\"T_ec6de_row6_col3\" class=\"data row6 col3\" >90.7569</td>\n",
+       "                        <td id=\"T_ec6de_row6_col4\" class=\"data row6 col4\" >12749.2146</td>\n",
+       "                        <td id=\"T_ec6de_row6_col5\" class=\"data row6 col5\" >0.0367</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fe1e59d0050>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "[RandomForestDTS(degree=1, model='additive', sp=1, window_length=10),\n",
+       " PolynomialTrendForecaster(degree=1, regressor=None, with_intercept=True)]"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "exp.setup(data=y, fh=fh, fold=fold, fold_strategy='expandingwindow')\n",
+    "\n",
+    "best_models = exp.compare_models(fold=fold, sort='rmse', n_select=2)\n",
+    "best_models"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -1134,8 +2811,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "name": "python379jvsc74a57bd02e79732785b968a887869d670772af3eb35a449ef73721b650f9c2f4a3fd4bbe",
-   "display_name": "Python 3.7.9 64-bit ('pycaret_dev': conda)"
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1147,9 +2825,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.9"
+   "version": "3.7.6"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
\ No newline at end of file
+}