diff --git a/examples/visualize.ipynb b/examples/visualize.ipynb
index d69e73c7b..4ac4e1d18 100644
--- a/examples/visualize.ipynb
+++ b/examples/visualize.ipynb
@@ -65,7 +65,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "26fb276b",
    "metadata": {},
    "outputs": [],
@@ -77,7 +77,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "937f1476",
    "metadata": {},
    "outputs": [],
@@ -94,12 +94,175 @@
     "gds = GraphDataScience(NEO4J_URI, auth=NEO4J_AUTH, database=NEO4J_DB)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "a96b84b5",
+   "metadata": {},
+   "source": [
+    "## Built-in visualization"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aa1f778c",
+   "metadata": {},
+   "source": [
+    "### IMDB"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "68125987",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "G_imdb = gds.graph.load_imdb()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "acc92487",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "G_imdb.visualize()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "21b17ba8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "G_imdb.visualize(directed=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a2f6d726",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "G_imdb.visualize(directed=False, theme=\"light\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "29534589",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "G_imdb.visualize(directed=False, node_count=200)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b751ec2c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "G_imdb.drop()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c6713a9d",
+   "metadata": {},
+   "source": [
+    "### Cora"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fe00c465",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "G_cora = gds.graph.load_cora()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "258747fc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "G_cora.visualize()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6d5a0704",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "G_cora.visualize(color_property=\"subject\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7dfe9e57",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "G_cora.visualize(color_property=\"subject\", include_node_properties=[\"subject\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "db635dd6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gds.degree.mutate(G_cora, mutateProperty=\"deg\")\n",
+    "G_cora.visualize(color_property=\"subject\", size_property=\"deg\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b6bc16f4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "G_cora.visualize(color_property=\"subject\", center_nodes=[12350])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "447f1a2d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "G_cora.drop()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "56dc02c4",
+   "metadata": {},
+   "source": [
+    "## Using PyVis"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "b1a8ab78",
    "metadata": {},
    "source": [
-    "## Sampling Cora\n",
+    "### Sampling Cora\n",
     "\n",
     "Next we use the [built-in Cora loader](https://neo4j.com/docs/graph-data-science-client/current/common-datasets/#_cora) to get the data into GDS.\n",
     "The nodes in the Cora dataset is represented by academic papers, and the relationships connecting them are citations.\n",
@@ -109,7 +272,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "a575da60",
    "metadata": {},
    "outputs": [],
@@ -127,24 +290,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "428ac7b8",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Metadata for our loaded Cora graph `G`: Graph(name=cora, node_count=2708, relationship_count=5429)\n",
-      "Node labels present in `G`: ['Paper']\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(f\"Metadata for our loaded Cora graph `G`: {G}\")\n",
     "print(f\"Node labels present in `G`: {G.node_labels()}\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b6aceb0a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "G.visualize(color_property=\"subject\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "3e8b8a83",
@@ -159,7 +323,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "3d116738",
    "metadata": {},
    "outputs": [],
@@ -178,19 +342,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "d66ea2d5",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Number of nodes in our sample: 406\n",
-      "Number of relationships in our sample: 532\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(f\"Number of nodes in our sample: {G_sample.node_count()}\")\n",
     "print(f\"Number of relationships in our sample: {G_sample.relationship_count()}\")"
@@ -207,30 +362,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "3d80d653",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "mutateMillis                                                              0\n",
-       "nodePropertiesWritten                                                   406\n",
-       "ranIterations                                                            20\n",
-       "didConverge                                                           False\n",
-       "centralityDistribution    {'min': 0.14999961853027344, 'max': 2.27294921...\n",
-       "postProcessingMillis                                                      1\n",
-       "preProcessingMillis                                                       0\n",
-       "computeMillis                                                             7\n",
-       "configuration             {'mutateProperty': 'rank', 'jobId': '5ca450ff-...\n",
-       "Name: 0, dtype: object"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "gds.pageRank.mutate(G_sample, mutateProperty=\"rank\")"
    ]
@@ -240,7 +375,7 @@
    "id": "722caa7b",
    "metadata": {},
    "source": [
-    "## Exporting the sampled Cora graph\n",
+    "### Exporting the sampled Cora graph\n",
     "\n",
     "We can now export the topology and node properties of our sampled graph that we want to visualize.\n",
     "\n",
@@ -249,129 +384,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "d3c76b25",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>sourceNodeId</th>\n",
-       "      <th>targetNodeId</th>\n",
-       "      <th>relationshipType</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>31336</td>\n",
-       "      <td>31349</td>\n",
-       "      <td>CITES</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>31336</td>\n",
-       "      <td>686532</td>\n",
-       "      <td>CITES</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>31336</td>\n",
-       "      <td>1129442</td>\n",
-       "      <td>CITES</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>31349</td>\n",
-       "      <td>686532</td>\n",
-       "      <td>CITES</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>31353</td>\n",
-       "      <td>31336</td>\n",
-       "      <td>CITES</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>527</th>\n",
-       "      <td>34961</td>\n",
-       "      <td>31043</td>\n",
-       "      <td>CITES</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>528</th>\n",
-       "      <td>34961</td>\n",
-       "      <td>22883</td>\n",
-       "      <td>CITES</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>529</th>\n",
-       "      <td>102879</td>\n",
-       "      <td>9513</td>\n",
-       "      <td>CITES</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>530</th>\n",
-       "      <td>102884</td>\n",
-       "      <td>9513</td>\n",
-       "      <td>CITES</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>531</th>\n",
-       "      <td>767763</td>\n",
-       "      <td>1136631</td>\n",
-       "      <td>CITES</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>532 rows × 3 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     sourceNodeId  targetNodeId relationshipType\n",
-       "0           31336         31349            CITES\n",
-       "1           31336        686532            CITES\n",
-       "2           31336       1129442            CITES\n",
-       "3           31349        686532            CITES\n",
-       "4           31353         31336            CITES\n",
-       "..            ...           ...              ...\n",
-       "527         34961         31043            CITES\n",
-       "528         34961         22883            CITES\n",
-       "529        102879          9513            CITES\n",
-       "530        102884          9513            CITES\n",
-       "531        767763       1136631            CITES\n",
-       "\n",
-       "[532 rows x 3 columns]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "sample_topology_df = gds.graph.relationships.stream(G_sample)\n",
     "display(sample_topology_df)"
@@ -392,129 +408,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "1c52e3b2",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>nodeId</th>\n",
-       "      <th>rank</th>\n",
-       "      <th>subject</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>164</td>\n",
-       "      <td>0.245964</td>\n",
-       "      <td>4.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>434</td>\n",
-       "      <td>0.158500</td>\n",
-       "      <td>2.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>1694</td>\n",
-       "      <td>0.961240</td>\n",
-       "      <td>5.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1949</td>\n",
-       "      <td>0.224912</td>\n",
-       "      <td>6.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>1952</td>\n",
-       "      <td>0.150000</td>\n",
-       "      <td>6.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>401</th>\n",
-       "      <td>1154103</td>\n",
-       "      <td>0.319498</td>\n",
-       "      <td>3.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>402</th>\n",
-       "      <td>1154124</td>\n",
-       "      <td>0.627706</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>403</th>\n",
-       "      <td>1154169</td>\n",
-       "      <td>0.154784</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>404</th>\n",
-       "      <td>1154251</td>\n",
-       "      <td>0.187675</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>405</th>\n",
-       "      <td>1154276</td>\n",
-       "      <td>0.277500</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>406 rows × 3 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      nodeId      rank  subject\n",
-       "0        164  0.245964      4.0\n",
-       "1        434  0.158500      2.0\n",
-       "2       1694  0.961240      5.0\n",
-       "3       1949  0.224912      6.0\n",
-       "4       1952  0.150000      6.0\n",
-       "..       ...       ...      ...\n",
-       "401  1154103  0.319498      3.0\n",
-       "402  1154124  0.627706      0.0\n",
-       "403  1154169  0.154784      0.0\n",
-       "404  1154251  0.187675      0.0\n",
-       "405  1154276  0.277500      0.0\n",
-       "\n",
-       "[406 rows x 3 columns]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "sample_node_properties_df = gds.graph.nodeProperties.stream(\n",
     "    G_sample,\n",
@@ -529,46 +426,18 @@
    "id": "ff81f977",
    "metadata": {},
    "source": [
+    "### Render visualization\n",
+    "\n",
     "Now that we have all the data we want to visualize, we can create a network with PyVis.\n",
     "We color each node according to its \"subject\", and size it according to its \"rank\"."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "93cb3bdf",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "cora-sample.html\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "        <iframe\n",
-       "            width=\"100%\"\n",
-       "            height=\"750px\"\n",
-       "            src=\"cora-sample.html\"\n",
-       "            frameborder=\"0\"\n",
-       "            allowfullscreen\n",
-       "            \n",
-       "        ></iframe>\n",
-       "        "
-      ],
-      "text/plain": [
-       "<IPython.lib.display.IFrame at 0x128adaee0>"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "net = Network(notebook = True,\n",
     "cdn_resources=\"remote\",\n",
@@ -619,7 +488,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "33523a0b",
    "metadata": {},
    "outputs": [],
@@ -630,22 +499,8 @@
   }
  ],
  "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
   "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "name": "python"
   }
  },
  "nbformat": 4,