diff --git a/Jobs-and-Users-ReqMemCPU.ipynb b/Jobs-and-Users-ReqMemCPU.ipynb
index 3a50d534dd6c1cf513c8d6cf2f2c2522061c812f..0d23eb1d7e0cb1feca5a5295a860f846259d2f56 100644
--- a/Jobs-and-Users-ReqMemCPU.ipynb
+++ b/Jobs-and-Users-ReqMemCPU.ipynb
@@ -93,15 +93,6 @@
     "df['ReqMemCPU'] = df['ReqMemCPU'].div(1024**3)"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['Elapsed'] = df['Elapsed'].div(3600)"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -370,125 +361,6 @@
     "#plt.yscale(\"log\")"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# ReqMemCPU,Corecount,Runtime"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "UpperlimitGB1 = 50"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_4 = df_completed.loc[:,['ReqMemCPU', 'Elapsed', 'AllocCPUS']]\n",
-    "df_4.head(5)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_4['ReqMemCPU'] = df_4['ReqMemCPU'].apply(np.ceil)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_4['Elapsed'] = df_4['Elapsed'].apply(np.ceil)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_4.sort_values(by='AllocCPUS', ascending=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_4_cutoff = df_4[(df_4['ReqMemCPU'] <= UpperlimitGB1)]\n",
-    "df_4_cutoff"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "style.default_axes_and_ticks()\n",
-    "style.figsize()\n",
-    "\n",
-    "user_graph5 = sns.scatterplot(x=\"ReqMemCPU\", y=\"Elapsed\",data=df_4_cutoff)\n",
-    "                              #hue=\"AllocCPUS\")\n",
-    "                              #, size=\"AllocCPUS\")\n",
-    "\n",
-    "#plt.title('Average Requested RAM per CPU by User for all Users Running %i Jobs or less'%UpperlimitJobCount)\n",
-    "\n",
-    "plt.xlabel('ReqMemCPU')\n",
-    "plt.ylabel('Runtime')\n",
-    "#plt.yscale(\"log\")\n",
-    "\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df_runtime_graph_cluster = df_4[(df_4['ReqMemCPU'] <= UpperlimitGB1)]\n",
-    "#df_runtime_graph_cluster.head(5)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "kmeans = KMeans(n_clusters=4, random_state=111)\n",
-    "kmeans.fit(df_runtime_graph_cluster)\n",
-    "print(kmeans.cluster_centers_)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "plt.scatter(df_runtime_graph_cluster['ReqMemCPU'],df_runtime_graph_cluster['Elapsed'], c=kmeans.labels_, cmap='rainbow')\n",
-    "plt.scatter(kmeans.cluster_centers_[:,0] ,kmeans.cluster_centers_[:,1], color='grey')\n",
-    "#plt.yscale(\"log\")\n",
-    "plt.xlabel('ReqMemCPU')\n",
-    "plt.ylabel('Runtime')"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},