diff --git a/bindings/pydeck/examples/03 - Using pydeck to manipulate data.ipynb b/bindings/pydeck/examples/03 - Using pydeck to manipulate data.ipynb
index 23e98f4ace2..c392651b493 100644
--- a/bindings/pydeck/examples/03 - Using pydeck to manipulate data.ipynb	
+++ b/bindings/pydeck/examples/03 - Using pydeck to manipulate data.ipynb	
@@ -6,8 +6,6 @@
    "source": [
     "# Selecting data for use in Python: Singapore taxi location data\n",
     "\n",
-    "*(About 5-10 minutes to read)*\n",
-    "\n",
     "Often it's easier to use a visual application to draw a shape than define a geometry in code. Here we'll explore how pydeck can be used to select data and pass that selected data back to the Jupyter kernel for use in Pandas.\n",
     "\n",
     "## Contents\n",
@@ -28,7 +26,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -47,7 +45,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -72,24 +70,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3df28f07550a420a9cc4394b2481bc88",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "DeckGLWidget(json_input='{\"initialViewState\": {\"bearing\": 0, \"latitude\": 1.3466294511520216, \"longitude\": 103.…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "r.show()"
    ]
@@ -105,60 +88,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": null,
    "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>cellCount</th>\n",
-       "      <th>cellWeight</th>\n",
-       "      <th>maxCellWieght</th>\n",
-       "      <th>totalCount</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>161</td>\n",
-       "      <td>161</td>\n",
-       "      <td>203</td>\n",
-       "      <td>2662</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   cellCount  cellWeight  maxCellWieght  totalCount\n",
-       "0        161         161            203        2662"
-      ]
-     },
-     "execution_count": 71,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "pd.DataFrame([r.deck_widget.selected_data])"
+    "pd.DataFrame(r.selected_data)"
    ]
   }
  ],
@@ -178,7 +112,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.7.7"
   }
  },
  "nbformat": 4,