diff --git a/notebooks/AGIPD/Characterize_AGIPD_Gain_FlatFields_NBC.ipynb b/notebooks/AGIPD/Characterize_AGIPD_Gain_FlatFields_NBC.ipynb
index e817a84a2daa2a94643a12a282389b171f2751c1..71be49924ec70ea4c9786bc5a783037cd384c211 100644
--- a/notebooks/AGIPD/Characterize_AGIPD_Gain_FlatFields_NBC.ipynb
+++ b/notebooks/AGIPD/Characterize_AGIPD_Gain_FlatFields_NBC.ipynb
@@ -536,14 +536,14 @@
    "outputs": [],
    "source": [
     "fig = plt.figure(figsize=(10, 5))\n",
-    "ax0 = fig.add_subplot(111)\n",
-    "a = ax0.hist(hist_std.flatten(), bins=100, range=(0,100) )\n",
-    "ax0.plot([intensity_lim, intensity_lim], [0, np.nanmax(a[0])], linewidth=1.5, color='red' ) \n",
-    "ax0.set_xlabel('Histogram width [ADU]', fontsize=14)\n",
-    "ax0.set_ylabel('Number of histograms', fontsize=14)\n",
-    "ax0.set_title(f'{hist_std[hist_std<intensity_lim].shape[0]} histograms below threshold in {intensity_lim} ADU',\n",
+    "ax = fig.add_subplot(111)\n",
+    "a = ax.hist(hist_std.flatten(), bins=100, range=(0,100) )\n",
+    "ax.plot([intensity_lim, intensity_lim], [0, np.nanmax(a[0])], linewidth=1.5, color='red' ) \n",
+    "ax.set_xlabel('Histogram width [ADU]', fontsize=14)\n",
+    "ax.set_ylabel('Number of histograms', fontsize=14)\n",
+    "ax.set_title(f'{hist_std[hist_std<intensity_lim].shape[0]} histograms below threshold in {intensity_lim} ADU',\n",
     "              fontsize=14, fontweight='bold')\n",
-    "ax0.grid()\n",
+    "ax.grid()\n",
     "plt.yscale('log')"
    ]
   },
@@ -634,7 +634,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def plot_error_band(key, x, ax0):\n",
+    "def plot_error_band(key, x, ax):\n",
     "    \n",
     "    cdata = np.copy(fit_result[key])\n",
     "    cdata[fit_result['mask']>0] = np.nan\n",
@@ -644,14 +644,14 @@
     "    std = np.nanstd(cdata, axis=(1,2))\n",
     "    mad = np.nanmedian(np.abs(cdata - median[:,None,None]), axis=(1,2))\n",
     "\n",
-    "    ax0.plot(x, mean, 'k', color='#3F7F4C', label=\" mean value \")\n",
-    "    ax0.plot(x, median, 'o', color='red', label=\" median value \")\n",
-    "    ax0.fill_between(x, mean-std, mean+std,\n",
+    "    ax.plot(x, mean, 'k', color='#3F7F4C', label=\" mean value \")\n",
+    "    ax.plot(x, median, 'o', color='red', label=\" median value \")\n",
+    "    ax.fill_between(x, mean-std, mean+std,\n",
     "                     alpha=0.6, edgecolor='#3F7F4C', facecolor='#7EFF99',\n",
     "                     linewidth=1, linestyle='dashdot', antialiased=True,\n",
     "                     label=\" mean value $ \\pm $ std \")\n",
     "\n",
-    "    ax0.fill_between(x, median-mad, median+mad,\n",
+    "    ax.fill_between(x, median-mad, median+mad,\n",
     "                     alpha=0.3, edgecolor='red', facecolor='red',\n",
     "                     linewidth=1, linestyle='dashdot', antialiased=True,\n",
     "                     label=\" median value $ \\pm $ mad \")\n",
@@ -661,7 +661,7 @@
     "        cerr[fit_result['mask']>0] = np.nan\n",
     "        \n",
     "        meanerr = np.nanmean(cerr, axis=(1,2))\n",
-    "        ax0.fill_between(x, mean-meanerr, mean+meanerr,\n",
+    "        ax.fill_between(x, mean-meanerr, mean+meanerr,\n",
     "                 alpha=0.6, edgecolor='#089FFF', facecolor='#089FFF',\n",
     "                 linewidth=1, linestyle='dashdot', antialiased=True,\n",
     "                 label=\" mean fit error \")\n",
@@ -672,13 +672,13 @@
     "for i, key in enumerate(['g0mean', 'g1mean', 'gain', 'chi2_ndof']):\n",
     "\n",
     "    fig = plt.figure(figsize=(10, 5))\n",
-    "    ax0 = fig.add_subplot(111)\n",
-    "    plot_error_band(key, x, ax0)\n",
+    "    ax = fig.add_subplot(111)\n",
+    "    plot_error_band(key, x, ax)\n",
     "\n",
-    "    ax0.set_xlabel('Memory Cell ID', fontsize=14)\n",
-    "    ax0.set_ylabel(labels[i], fontsize=14)\n",
-    "    ax0.grid()\n",
-    "    ax0.legend()"
+    "    ax.set_xlabel('Memory Cell ID', fontsize=14)\n",
+    "    ax.set_ylabel(labels[i], fontsize=14)\n",
+    "    ax.grid()\n",
+    "    ax.legend()"
    ]
   },
   {