diff --git a/notebooks/Jungfrau/Jungfrau_darks_Summary_NBC.ipynb b/notebooks/Jungfrau/Jungfrau_darks_Summary_NBC.ipynb
index 1db8e59f99a8317858a99e2f5966bc88f24a849f..55be915015324c3668b9e5f2d32590ee4d0ae485 100644
--- a/notebooks/Jungfrau/Jungfrau_darks_Summary_NBC.ipynb
+++ b/notebooks/Jungfrau/Jungfrau_darks_Summary_NBC.ipynb
@@ -196,7 +196,7 @@
     "gs = gridspec.GridSpec(2, 4)\n",
     "\n",
     "axes = {\n",
-    "    \"ax0\": {\n",
+    "    \"map\": {\n",
     "        \"gs\": gs[0, 1:3],\n",
     "        \"shrink\": 0.7,\n",
     "        \"pad\": 0.05,\n",
@@ -204,7 +204,7 @@
     "        \"title\": \"{}\",\n",
     "        \"location\": \"right\",\n",
     "        },\n",
-    "    \"ax1\": {\n",
+    "    \"diff\": {\n",
     "        \"gs\": gs[1, :2],\n",
     "        \"shrink\": 0.7,\n",
     "        \"pad\": 0.02,\n",
@@ -212,7 +212,7 @@
     "        \"location\": \"left\",\n",
     "        \"title\": \"Difference with previous {}\",\n",
     "        },\n",
-    "    \"ax2\": {\n",
+    "    \"diff_frac\": {\n",
     "        \"gs\": gs[1, 2:],\n",
     "        \"shrink\": 0.7,\n",
     "        \"pad\": 0.02,\n",
@@ -275,15 +275,25 @@
     "    # Prepare the stacked mean of constant,\n",
     "    # the difference with the previous constant\n",
     "    # and the fraction of that difference.\n",
+    "\n",
     "    mean_const = np.nanmean(const, axis=3)\n",
-    "    mean_diff = np.abs(np.nanmean(const, axis=3) - np.nanmean(prev_constants[cname], axis=3))  # noqa\n",
-    "    mean_frac = np.abs(mean_diff / mean_const) * 100\n",
-    "        \n",
+    "    mean_diff = np.abs(\n",
+    "        np.nanmean(const, axis=3) - np.nanmean(\n",
+    "            prev_constants[cname],\n",
+    "            axis=3)\n",
+    "        )\n",
+    "    mean_frac = np.divide(\n",
+    "        mean_diff,\n",
+    "        mean_const,\n",
+    "        out=np.zeros_like(mean_const),\n",
+    "        where=(mean_const != 0)\n",
+    "    ) * 100\n",
+    "\n",
     "    for gain in range(gainstages):\n",
     "        data_to_plot = {\n",
-    "            f'ax0': mean_const[..., gain],\n",
-    "            f'ax1': mean_diff[..., gain],\n",
-    "            f'ax2': mean_frac[..., gain],\n",
+    "            f'map': mean_const[..., gain],\n",
+    "            f'diff': mean_diff[..., gain],\n",
+    "            f'diff_frac': mean_frac[..., gain],\n",
     "            }\n",
     "\n",
     "        # Plotting constant overall modules.\n",
@@ -297,13 +307,11 @@
     "\n",
     "            # Avoid difference plots if previous constants\n",
     "            # are missing for the detector.\n",
-    "            if cname in exculded_constants and axname != \"ax0\":\n",
+    "            if cname in exculded_constants and axname != \"map\":\n",
     "                break\n",
     "            ax = fig.add_subplot(axv[\"gs\"])\n",
     "\n",
-    "            if axname == \"ax2\":  # Difference in percentage\n",
-    "                vmin, vmax = (0, 100)\n",
-    "            elif badpx(cname):\n",
+    "            if badpx(cname):\n",
     "                vmin, vmax = (0, sorted([bp.value for bp in badpixels])[-2])\n",
     "            else:\n",
     "                vmin, vmax = np.percentile(data_to_plot[axname], [5, 95])\n",
@@ -327,7 +335,7 @@
     "            ax.set_title(axv[\"title\"].format(\n",
     "                f\"{cname} {gain_names[gain]}\"), fontsize=15)\n",
     "            \n",
-    "            if axname == \"ax0\":\n",
+    "            if axname == \"map\":\n",
     "                ax.set_xlabel('Columns', fontsize=15)\n",
     "                ax.set_ylabel('Rows', fontsize=15)\n",
     "                ax.tick_params(labelsize=15)\n",