diff --git a/notebooks/COS/ExceptionReport/ExceptionReport.ipynb b/notebooks/COS/ExceptionReport/ExceptionReport.ipynb
index 772a1772d..6a8524f36 100644
--- a/notebooks/COS/ExceptionReport/ExceptionReport.ipynb
+++ b/notebooks/COS/ExceptionReport/ExceptionReport.ipynb
@@ -89,7 +89,6 @@
     "\n",
     "import shutil\n",
     "import os\n",
-    "import glob\n",
     "from pathlib import Path\n",
     "\n",
     "import cos_functions as cf\n",
@@ -244,52 +243,6 @@
     "print_exposure_summary(successful_raw_a)"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# query = Observations.query_criteria(\n",
-    "#     obs_id=\"LDI707030\",\n",
-    "#     filters=\"G130M\"\n",
-    "# )\n",
-    "\n",
-    "# prods = Observations.get_product_list(\n",
-    "#     query,\n",
-    "# )\n",
-    "\n",
-    "# prods = Observations.filter_products(\n",
-    "#     prods,\n",
-    "#     productSubGroupDescription=[\"RAWTAG_A\", \"RAWTAG_B\", \"X1D\"]\n",
-    "# )\n",
-    "\n",
-    "# Observations.download_products(prods[:3],\n",
-    "#                                download_dir=\".\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# path = \"/Users/sigomez/Documents/exception-report/ExceptionReport/files.fits\"\n",
-    "\n",
-    "# from astropy.table import Table\n",
-    "\n",
-    "# table = Table.read(path)\n",
-    "\n",
-    "# table.remove_rows([0, 1, 2])\n",
-    "\n",
-    "# for row in prods[:3]:\n",
-    "#     table.add_row(row)\n",
-    "\n",
-    "# table.write(\"files.fits\", \n",
-    "#             format='fits', \n",
-    "#             overwrite=True)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -505,13 +458,13 @@
     "    Output:\n",
     "    SNR is plotted.\n",
     "    '''\n",
-    "    fig = plt.Figure(figsize=(12, 10))\n",
+    "    plt.Figure(figsize=(12, 10))\n",
     "\n",
     "    for file in sorted(filelist):\n",
     "        with fits.open(file) as hdul:\n",
     "            if \"x1dsum\" in file:\n",
     "                exptime = hdul[1].header[\"EXPTIME\"]\n",
-    "                label=f\"X1DSUM - {exptime} sec\"\n",
+    "                label = f\"X1DSUM - {exptime} sec\"\n",
     "\n",
     "            else:\n",
     "                fppos = hdul[0].header[\"FPPOS\"]\n",
@@ -530,8 +483,8 @@
     "            weighted=True,\n",
     "        )\n",
     "\n",
-    "        plt.plot(np.concatenate([snr_est[1][1][0],snr_est[1][0][0]], axis=0), \n",
-    "                 np.concatenate([snr_est[1][1][1],snr_est[1][0][1]], axis=0),\n",
+    "        plt.plot(np.concatenate([snr_est[1][1][0], snr_est[1][0][0]], axis=0), \n",
+    "                 np.concatenate([snr_est[1][1][1], snr_est[1][0][1]], axis=0),\n",
     "                 label=label,\n",
     "                 lw=1,\n",
     "                 alpha=0.6)\n",
@@ -794,9 +747,9 @@
     "        )\n",
     "\n",
     "        conf_im = confirm.imshow(hdul[4].data,\n",
-    "                                vmin=0, \n",
-    "                                vmax=0.1, \n",
-    "                                aspect=\"auto\")\n",
+    "                                 vmin=0, \n",
+    "                                 vmax=0.1, \n",
+    "                                 aspect=\"auto\")\n",
     "\n",
     "        confirm.plot(\n",
     "            header[\"ACQCENTX\"],\n",
@@ -921,10 +874,11 @@
     "    )\n",
     "\n",
     "    for subplot, column in zip(ax, [\"XDISP_OFFSET\", \"DISP_OFFSET\"]):\n",
+    "\n",
     "        subplot.set_xlabel(column,\n",
-    "                        fontweight=\"bold\")\n",
+    "                           fontweight=\"bold\")\n",
     "        subplot.set_ylabel(\"DWELL POINT\",\n",
-    "                        fontweight=\"bold\")\n",
+    "                           fontweight=\"bold\")\n",
     "\n",
     "        subplot.axvline(0, 0, 6,\n",
     "                        linestyle=\"dashed\",\n",
@@ -940,7 +894,7 @@
     "    \n",
     "    cbd = fig.colorbar(cd, ax=ax[1])\n",
     "    cbd.set_label(\"Counts\",\n",
-    "                fontweight=\"bold\")\n",
+    "                  fontweight=\"bold\")\n",
     "\n",
     "    ax[0].set_title(f'PEAKXD for {fits.getval(peakxd, \"ROOTNAME\")}',\n",
     "                    fontweight=\"bold\")\n",
@@ -1308,9 +1262,9 @@
     "    if rss:\n",
     "        return v2_stdev, v3_stdev\n",
     "\n",
-    "    fig = plt.Figure(figsize=(12, 12))\n",
+    "    plt.Figure(figsize=(12, 12))\n",
     "\n",
-    "    hist = plt.hist2d(\n",
+    "    plt.hist2d(\n",
     "        x=v2_avg, \n",
     "        y=v3_avg,\n",
     "        bins=n_bins\n",
@@ -1333,7 +1287,7 @@
     "    label_y = ellipse_center[1] + n_sigma * v3_stdev / 2\n",
     "\n",
     "    ax.text(label_x, label_y,\n",
-    "            f'{n_sigma}$\\sigma$ contour',\n",
+    "            f'{n_sigma} sigma contour',\n",
     "            color='black',\n",
     "            bbox=dict(facecolor=\"white\",\n",
     "                      alpha=0.7),\n",