docs: run the notebook

Author: tswast

notebooks/getting_started/pandas_extensions.ipynb

@@ -4,20 +4,19 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Pandas Extension for BigQuery DataFrames\n",
+    "# BigQuery extension for pandas\n",
     "\n",
     "BigQuery DataFrames provides a pandas extension to execute BigQuery SQL scalar functions directly on pandas DataFrames."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
     "import pandas as pd\n",
-    "import bigframes.pandas as bpd\n",
-    "import bigframes"
+    "import bigframes  # This import registers the bigquery accessor."
    ]
   },
   {
@@ -31,9 +30,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    Query processed 0 Bytes in a moment of slot time.\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0    2.0\n",
+       "1    3.0\n",
+       "2    4.0\n",
+       "dtype: Float64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "df = pd.DataFrame({\"a\": [1.5, 2.5, 3.5]})\n",
     "result = df.bigquery.sql_scalar(\"ROUND({0}, 0)\")\n",
@@ -49,9 +76,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "    Query processed 0 Bytes in a moment of slot time.\n",
+       "    "
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "0    11\n",
+       "1    22\n",
+       "2    33\n",
+       "dtype: Int64"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "df = pd.DataFrame({\"a\": [1, 2, 3], \"b\": [10, 20, 30]})\n",
     "result = df.bigquery.sql_scalar(\"{0} + {1}\")\n",
@@ -61,7 +116,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "venv",
    "language": "python",
    "name": "python3"
   },