diff --git a/Dockerfile b/Dockerfile
index ce145d9f04626095a7bdf52ca93be61364a9fc12..d5489c0845cb0f18d870eb53d9f6aa013b0a5bfc 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -29,7 +29,7 @@ USER ${NB_UID}
 WORKDIR "${HOME}"
 
 # https://jupyter-docker-stacks.readthedocs.io/en/latest/using/common.html
-# ENV DOCKER_STACKS_JUPYTER_CMD="nbclassic"
+ENV DOCKER_STACKS_JUPYTER_CMD="nbclassic"
 # ENV DOCKER_STACKS_JUPYTER_CMD="notebook"
 
 COPY --chown=${NB_UID}:${NB_GID} assets ./assets
diff --git a/cbs_with_qrf.ipynb b/cbs_with_qrf.ipynb
index e2622611b5a83a288c6834ae519dabb930b215f7..74fcd9e12da44c476c878c8d1747609171be7749 100644
--- a/cbs_with_qrf.ipynb
+++ b/cbs_with_qrf.ipynb
@@ -1454,41 +1454,19 @@
     "# This code works to create a nested dataframe where the first key is the model we choose and the second\n",
     "# is the metric. This is useful is we are curious in multiple metrics. At the moment we only use the\n",
     "# symmetric absolute percentage error and it is a bit overkill.\n",
-    "model_df_aims = pd.DataFrame({})\n",
-    "for i in range(len(ape_qrf_aims)):\n",
-    "    df = {'model': 'QRF', 'ape': ape_qrf_aims[i],\n",
-    "\n",
-    "         }\n",
-    "    model_df_aims = model_df_aims.append(df, ignore_index = True)\n",
-    "for i in range(len(ape_stoich_aims)):\n",
-    "    df = {\n",
-    "        'model': 'Stoichiometric', 'ape': ape_stoich_aims[i],\n",
-    "    }\n",
-    "\n",
-    "    model_df_aims = model_df_aims.append(df, ignore_index = True)\n",
-    "for i in range(len(ape_combined_aims)):\n",
-    "    df = {\n",
-    "        'model': 'SISSO', 'ape': ape_combined_aims[i],\n",
-    "    }\n",
-    "\n",
-    "    model_df_aims = model_df_aims.append(df, ignore_index = True)\n",
-    "\n",
-    "model_df_exciting = pd.DataFrame({})\n",
-    "for i in range(len(ape_qrf_exciting)):\n",
-    "    df = {\n",
-    "        'model': 'QRF',\n",
-    "        'ape': ape_qrf_exciting[i],\n",
-    "    }\n",
-    "    model_df_exciting = model_df_exciting.append(df, ignore_index = True)\n",
-    "\n",
-    "for i in range(len(ape_stoich_exciting)):\n",
-    "    df = {'model': 'Stoichiometric', 'ape': ape_stoich_exciting[i]\n",
-    "         }\n",
-    "    model_df_exciting = model_df_exciting.append(df, ignore_index = True)\n",
-    "for i in range(len(ape_combined_exciting)):\n",
-    "    df = {'model': 'SISSO', 'ape': ape_combined_exciting[i]\n",
-    "         }\n",
-    "    model_df_exciting = model_df_exciting.append(df, ignore_index = True)"
+    "data = []\n",
+    "data.extend(['QRF', val] for val in ape_qrf_aims)\n",
+    "data.extend(['Stoichiometric', val] for val in ape_stoich_aims)\n",
+    "data.extend(['SISSO', val] for val in ape_combined_aims)\n",
+    "\n",
+    "model_df_aims = pd.DataFrame(data, columns=['model', 'ape'])\n",
+    "\n",
+    "data = []\n",
+    "data.extend(['QRF', val] for val in ape_qrf_exciting)\n",
+    "data.extend(['Stoichiometric', val] for val in ape_stoich_exciting)\n",
+    "data.extend(['SISSO', val] for val in ape_combined_exciting)\n",
+    "\n",
+    "model_df_exciting = pd.DataFrame(data, columns=['model', 'ape'])"
    ]
   },
   {
@@ -1667,10 +1645,10 @@
     "ax1.set_ylim(0, 200)\n",
     "ax2.set_ylim(0, 200)\n",
     "ax2.set_xlabel('Model', fontsize=14)\n",
-    "adjust_box_widths(ax1, 0.5) #If only one set 0.5 to 0.25\n",
+    "# adjust_box_widths(ax1, 0.5) #If only one set 0.5 to 0.25\n",
     "ax1.grid(False)\n",
     "\n",
-    "adjust_box_widths(ax2, .5) #If only one set 0.5 to 0.25\n",
+    "# adjust_box_widths(ax2, .5) #If only one set 0.5 to 0.25\n",
     "ax2.grid(False)\n",
     "\n",
     "\n",