diff --git a/notebooks/demo/nxcg_wikipedia_e2e.ipynb b/notebooks/demo/nxcg_wikipedia_e2e.ipynb
index d8c0656627..ca1c9d3ef5 100644
--- a/notebooks/demo/nxcg_wikipedia_e2e.ipynb
+++ b/notebooks/demo/nxcg_wikipedia_e2e.ipynb
@@ -75,7 +75,16 @@
     "    sep=\" \",\n",
     "    names=[\"src\", \"dst\"],\n",
     "    dtype=\"int32\",\n",
-    ")\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%time\n",
     "\n",
     "# Read the Wikipedia Page metadata from `nodedata_csv`\n",
     "nodedata_df = pd.read_csv(\n",
@@ -83,7 +92,16 @@
     "    sep=\"\\t\",\n",
     "    names=[\"nodeid\", \"title\"],\n",
     "    dtype={\"nodeid\": \"int32\", \"title\": \"str\"},\n",
-    ")\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%time\n",
     "\n",
     "# Create a NetworkX graph from the connectivity info\n",
     "G = nx.from_pandas_edgelist(\n",
@@ -91,16 +109,43 @@
     "    source=\"src\",\n",
     "    target=\"dst\",\n",
     "    create_using=nx.DiGraph,\n",
-    ")\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%time\n",
     "\n",
     "# Run pagerank on NetworkX\n",
-    "nx_pr_vals = nx.pagerank(G)\n",
+    "nx_pr_vals = nx.pagerank(G)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%time\n",
     "\n",
     "# Create a DataFrame containing the results\n",
     "pagerank_df = pd.DataFrame({\n",
     "    \"nodeid\": nx_pr_vals.keys(),\n",
     "    \"pagerank\": nx_pr_vals.values()\n",
-    "})\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%time\n",
     "\n",
     "# Add NetworkX results to `nodedata` as new columns\n",
     "nodedata_df = nodedata_df.merge(pagerank_df, how=\"left\", on=\"nodeid\")\n",