[FEAT] NeuralForecast Compatibility and Example Notebook (#188)

* added median checking in reconcile

* updated drop_cols logic

* added MLFrameworksExample notebook

* updated MLFrameworksExamble nb documentation

* removed extra -median check

* updated sidebar.yml with new example nb

hierarchicalforecast/core.py

@@ -45,7 +45,12 @@ def _reverse_engineer_sigmah(Y_hat_df, y_hat, model_name):
     In the future, we might deprecate this function in favor of a 
     direct usage of an estimated $\hat{sigma}_{h}$
     """
-    drop_cols = ['ds', 'y'] if 'y' in Y_hat_df.columns else ['ds']
+
+    drop_cols = ['ds']
+    if 'y' in Y_hat_df.columns:
+        drop_cols.append('y')
+    if model_name+'-median' in Y_hat_df.columns:
+        drop_cols.append(model_name+'-median')
     model_names = Y_hat_df.drop(columns=drop_cols, axis=1).columns.to_list()
     pi_model_names = [name for name in model_names if ('-lo' in name or '-hi' in name)]
     pi_model_name = [pi_name for pi_name in pi_model_names if model_name in pi_name]
@@ -143,7 +148,7 @@ def _prepare_fit(self,
         if Y_hat_df[model_names].isnull().values.any():
             raise Exception('`Y_hat_df` contains null values')
 
-        pi_model_names = [name for name in model_names if ('-lo' in name or '-hi' in name)]
+        pi_model_names = [name for name in model_names if ('-lo' in name or '-hi' in name or '-median' in name)]
         model_names = [name for name in model_names if name not in pi_model_names]
 
         # TODO: Complete y_hat_insample protection

nbs/core.ipynb

@@ -138,7 +138,12 @@
     "    In the future, we might deprecate this function in favor of a \n",
     "    direct usage of an estimated $\\hat{sigma}_{h}$\n",
     "    \"\"\"\n",
-    "    drop_cols = ['ds', 'y'] if 'y' in Y_hat_df.columns else ['ds']\n",
+    "\n",
+    "    drop_cols = ['ds']\n",
+    "    if 'y' in Y_hat_df.columns:\n",
+    "        drop_cols.append('y')\n",
+    "    if model_name+'-median' in Y_hat_df.columns:\n",
+    "        drop_cols.append(model_name+'-median')\n",
     "    model_names = Y_hat_df.drop(columns=drop_cols, axis=1).columns.to_list()\n",
     "    pi_model_names = [name for name in model_names if ('-lo' in name or '-hi' in name)]\n",
     "    pi_model_name = [pi_name for pi_name in pi_model_names if model_name in pi_name]\n",
@@ -243,7 +248,7 @@
     "        if Y_hat_df[model_names].isnull().values.any():\n",
     "            raise Exception('`Y_hat_df` contains null values')\n",
     "        \n",
-    "        pi_model_names = [name for name in model_names if ('-lo' in name or '-hi' in name)]\n",
+    "        pi_model_names = [name for name in model_names if ('-lo' in name or '-hi' in name or '-median' in name)]\n",
     "        model_names = [name for name in model_names if name not in pi_model_names]\n",
     "        \n",
     "        # TODO: Complete y_hat_insample protection\n",