diff --git a/notebooks/ePix100/Correction_ePix100_NBC.ipynb b/notebooks/ePix100/Correction_ePix100_NBC.ipynb
index baa4bc08c982e90ef187d5ae802cc34a6af0762c..ea7507c844aa59198a8b8ed0781c0641cc152884 100644
--- a/notebooks/ePix100/Correction_ePix100_NBC.ipynb
+++ b/notebooks/ePix100/Correction_ePix100_NBC.ipynb
@@ -793,20 +793,9 @@
    "outputs": [],
    "source": [
     "if absolute_gain :\n",
-    "    d=[]\n",
+    "    d = []\n",
     "    ho, eo, co, so = histCalAbsGainCor.get()\n",
-    "    d.append({\n",
-    "        'x': co,\n",
-    "        'y': ho,\n",
-    "        'y_err': np.sqrt(ho[:]),\n",
-    "        'drawstyle': 'steps-mid',\n",
-    "        'errorstyle': 'bars',\n",
-    "        'errorcoarsing': 2,\n",
-    "        'label': 'Absolute gain corr.'\n",
-    "    })\n",
-    "\n",
-    "    if pattern_classification:\n",
-    "        ho, eo, co, so = histCalGainCorClusters.get()\n",
+    "    if co is not None:  # avoid adding None array, if calculator is empty.\n",
     "        d.append({\n",
     "            'x': co,\n",
     "            'y': ho,\n",
@@ -814,19 +803,33 @@
     "            'drawstyle': 'steps-mid',\n",
     "            'errorstyle': 'bars',\n",
     "            'errorcoarsing': 2,\n",
-    "            'label': 'Charge sharing corr.'\n",
+    "            'label': 'Absolute gain corr.'\n",
     "        })\n",
+    "\n",
+    "    if pattern_classification:\n",
+    "        ho, eo, co, so = histCalGainCorClusters.get()\n",
+    "        if co is not None:  # avoid adding None array, if calculator is empty.\n",
+    "            d.append({\n",
+    "                'x': co,\n",
+    "                'y': ho,\n",
+    "                'y_err': np.sqrt(ho[:]),\n",
+    "                'drawstyle': 'steps-mid',\n",
+    "                'errorstyle': 'bars',\n",
+    "                'errorcoarsing': 2,\n",
+    "                'label': 'Charge sharing corr.'\n",
+    "            })\n",
     "        \n",
     "        ho, eo, co, so = histCalGainCorSingles.get()\n",
-    "        d.append({\n",
-    "            'x': co,\n",
-    "            'y': ho,\n",
-    "            'y_err': np.sqrt(ho[:]),\n",
-    "            'drawstyle': 'steps-mid',\n",
-    "            'errorstyle': 'bars',\n",
-    "            'errorcoarsing': 2,\n",
-    "            'label': 'Isolated photons (singles)'\n",
-    "        })\n",
+    "        if co is not None:  # avoid adding None array, if calculator is empty.\n",
+    "            d.append({\n",
+    "                'x': co,\n",
+    "                'y': ho,\n",
+    "                'y_err': np.sqrt(ho[:]),\n",
+    "                'drawstyle': 'steps-mid',\n",
+    "                'errorstyle': 'bars',\n",
+    "                'errorcoarsing': 2,\n",
+    "                'label': 'Isolated photons (singles)'\n",
+    "            })\n",
     "        \n",
     "    fig = xana.simplePlot(\n",
     "        d, aspect=1, x_label=f'Energy ({plot_unit})',\n",