diff --git a/bigframes/ml/cluster.py b/bigframes/ml/cluster.py
index 772b90f666..c9f52ba0b6 100644
--- a/bigframes/ml/cluster.py
+++ b/bigframes/ml/cluster.py
@@ -17,7 +17,7 @@
 
 from __future__ import annotations
 
-from typing import cast, Dict, List, Optional, Union
+from typing import Dict, List, Optional, Union
 
 from google.cloud import bigquery
 
@@ -92,7 +92,7 @@ def predict(
 
         (X,) = utils.convert_to_dataframe(X)
 
-        return cast(bpd.DataFrame, self._bqml_model.predict(X)[["CENTROID_ID"]])
+        return self._bqml_model.predict(X)
 
     def to_gbq(self, model_name: str, replace: bool = False) -> KMeans:
         """Save the model to BigQuery.
diff --git a/bigframes/ml/decomposition.py b/bigframes/ml/decomposition.py
index 8e6be6d28c..7cda7a6993 100644
--- a/bigframes/ml/decomposition.py
+++ b/bigframes/ml/decomposition.py
@@ -17,7 +17,7 @@
 
 from __future__ import annotations
 
-from typing import cast, List, Optional, Union
+from typing import List, Optional, Union
 
 from google.cloud import bigquery
 
@@ -106,12 +106,7 @@ def predict(self, X: Union[bpd.DataFrame, bpd.Series]) -> bpd.DataFrame:
 
         (X,) = utils.convert_to_dataframe(X)
 
-        return cast(
-            bpd.DataFrame,
-            self._bqml_model.predict(X)[
-                ["principal_component_" + str(i + 1) for i in range(self.n_components)]
-            ],
-        )
+        return self._bqml_model.predict(X)
 
     def to_gbq(self, model_name: str, replace: bool = False) -> PCA:
         """Save the model to BigQuery.
diff --git a/bigframes/ml/ensemble.py b/bigframes/ml/ensemble.py
index 19ca8608ff..fcb3fe5343 100644
--- a/bigframes/ml/ensemble.py
+++ b/bigframes/ml/ensemble.py
@@ -17,7 +17,7 @@
 
 from __future__ import annotations
 
-from typing import cast, Dict, List, Literal, Optional, Union
+from typing import Dict, List, Literal, Optional, Union
 
 from google.cloud import bigquery
 
@@ -168,16 +168,7 @@ def predict(
             raise RuntimeError("A model must be fitted before predict")
         (X,) = utils.convert_to_dataframe(X)
 
-        df = self._bqml_model.predict(X)
-        return cast(
-            bpd.DataFrame,
-            df[
-                [
-                    cast(str, field.name)
-                    for field in self._bqml_model.model.label_columns
-                ]
-            ],
-        )
+        return self._bqml_model.predict(X)
 
     def score(
         self,
@@ -328,19 +319,9 @@ def _fit(
     def predict(self, X: Union[bpd.DataFrame, bpd.Series]) -> bpd.DataFrame:
         if not self._bqml_model:
             raise RuntimeError("A model must be fitted before predict")
-
         (X,) = utils.convert_to_dataframe(X)
 
-        df = self._bqml_model.predict(X)
-        return cast(
-            bpd.DataFrame,
-            df[
-                [
-                    cast(str, field.name)
-                    for field in self._bqml_model.model.label_columns
-                ]
-            ],
-        )
+        return self._bqml_model.predict(X)
 
     def score(
         self,
@@ -486,19 +467,9 @@ def predict(
     ) -> bpd.DataFrame:
         if not self._bqml_model:
             raise RuntimeError("A model must be fitted before predict")
-
         (X,) = utils.convert_to_dataframe(X)
 
-        df = self._bqml_model.predict(X)
-        return cast(
-            bpd.DataFrame,
-            df[
-                [
-                    cast(str, field.name)
-                    for field in self._bqml_model.model.label_columns
-                ]
-            ],
-        )
+        return self._bqml_model.predict(X)
 
     def score(
         self,
@@ -661,19 +632,9 @@ def predict(
     ) -> bpd.DataFrame:
         if not self._bqml_model:
             raise RuntimeError("A model must be fitted before predict")
-
         (X,) = utils.convert_to_dataframe(X)
 
-        df = self._bqml_model.predict(X)
-        return cast(
-            bpd.DataFrame,
-            df[
-                [
-                    cast(str, field.name)
-                    for field in self._bqml_model.model.label_columns
-                ]
-            ],
-        )
+        return self._bqml_model.predict(X)
 
     def score(
         self,
diff --git a/bigframes/ml/forecasting.py b/bigframes/ml/forecasting.py
index 8e309d5e73..cf23854fa0 100644
--- a/bigframes/ml/forecasting.py
+++ b/bigframes/ml/forecasting.py
@@ -16,7 +16,7 @@
 
 from __future__ import annotations
 
-from typing import cast, Dict, List, Optional, Union
+from typing import Dict, List, Optional, Union
 
 from google.cloud import bigquery
 
@@ -24,8 +24,6 @@
 from bigframes.ml import base, core, globals, utils
 import bigframes.pandas as bpd
 
-_PREDICT_OUTPUT_COLUMNS = ["forecast_timestamp", "forecast_value"]
-
 
 class ARIMAPlus(base.SupervisedTrainablePredictor):
     """Time Series ARIMA Plus model."""
@@ -100,10 +98,7 @@ def predict(self, X=None) -> bpd.DataFrame:
         if not self._bqml_model:
             raise RuntimeError("A model must be fitted before predict")
 
-        return cast(
-            bpd.DataFrame,
-            self._bqml_model.forecast()[_PREDICT_OUTPUT_COLUMNS],
-        )
+        return self._bqml_model.forecast()
 
     def score(
         self,
diff --git a/bigframes/ml/imported.py b/bigframes/ml/imported.py
index fb8aa98bef..f6afc9aa38 100644
--- a/bigframes/ml/imported.py
+++ b/bigframes/ml/imported.py
@@ -78,16 +78,7 @@ def predict(self, X: Union[bpd.DataFrame, bpd.Series]) -> bpd.DataFrame:
 
         (X,) = utils.convert_to_dataframe(X)
 
-        df = self._bqml_model.predict(X)
-        return cast(
-            bpd.DataFrame,
-            df[
-                [
-                    cast(str, field.name)
-                    for field in self._bqml_model.model.label_columns
-                ]
-            ],
-        )
+        return self._bqml_model.predict(X)
 
     def to_gbq(self, model_name: str, replace: bool = False) -> TensorFlowModel:
         """Save the model to BigQuery.
@@ -161,16 +152,7 @@ def predict(self, X: Union[bpd.DataFrame, bpd.Series]) -> bpd.DataFrame:
 
         (X,) = utils.convert_to_dataframe(X)
 
-        df = self._bqml_model.predict(X)
-        return cast(
-            bpd.DataFrame,
-            df[
-                [
-                    cast(str, field.name)
-                    for field in self._bqml_model.model.label_columns
-                ]
-            ],
-        )
+        return self._bqml_model.predict(X)
 
     def to_gbq(self, model_name: str, replace: bool = False) -> ONNXModel:
         """Save the model to BigQuery.
diff --git a/bigframes/ml/linear_model.py b/bigframes/ml/linear_model.py
index f11879500b..433d9fbc38 100644
--- a/bigframes/ml/linear_model.py
+++ b/bigframes/ml/linear_model.py
@@ -17,7 +17,7 @@
 
 from __future__ import annotations
 
-from typing import cast, Dict, List, Literal, Optional, Union
+from typing import Dict, List, Literal, Optional, Union
 
 from google.cloud import bigquery
 
@@ -145,16 +145,7 @@ def predict(self, X: Union[bpd.DataFrame, bpd.Series]) -> bpd.DataFrame:
 
         (X,) = utils.convert_to_dataframe(X)
 
-        df = self._bqml_model.predict(X)
-        return cast(
-            bpd.DataFrame,
-            df[
-                [
-                    cast(str, field.name)
-                    for field in self._bqml_model.model.label_columns
-                ]
-            ],
-        )
+        return self._bqml_model.predict(X)
 
     def score(
         self,
@@ -267,16 +258,7 @@ def predict(
 
         (X,) = utils.convert_to_dataframe(X)
 
-        df = self._bqml_model.predict(X)
-        return cast(
-            bpd.DataFrame,
-            df[
-                [
-                    cast(str, field.name)
-                    for field in self._bqml_model.model.label_columns
-                ]
-            ],
-        )
+        return self._bqml_model.predict(X)
 
     def score(
         self,
diff --git a/bigframes/ml/llm.py b/bigframes/ml/llm.py
index 3cfc28e61f..93e2ba825f 100644
--- a/bigframes/ml/llm.py
+++ b/bigframes/ml/llm.py
@@ -149,7 +149,8 @@ def predict(
 
 
         Returns:
-            bigframes.dataframe.DataFrame: Output DataFrame with only 1 column as the output text results."""
+            bigframes.dataframe.DataFrame: DataFrame of shape (n_samples, n_input_columns + n_prediction_columns). Returns predicted values.
+        """
 
         # Params reference: https://cloud.google.com/vertex-ai/docs/generative-ai/learn/models
         if temperature < 0.0 or temperature > 1.0:
@@ -181,11 +182,7 @@ def predict(
             "top_p": top_p,
             "flatten_json_output": True,
         }
-        df = self._bqml_model.generate_text(X, options)
-        return cast(
-            bpd.DataFrame,
-            df[[_TEXT_GENERATE_RESULT_COLUMN]],
-        )
+        return self._bqml_model.generate_text(X, options)
 
 
 class PaLM2TextEmbeddingGenerator(base.Predictor):
@@ -269,7 +266,7 @@ def predict(self, X: Union[bpd.DataFrame, bpd.Series]) -> bpd.DataFrame:
                 Input DataFrame, which needs to contain a column with name "content". Only the column will be used as input. Content can include preamble, questions, suggestions, instructions, or examples.
 
         Returns:
-            bigframes.dataframe.DataFrame: Output DataFrame with only 1 column as the output embedding results
+            bigframes.dataframe.DataFrame: DataFrame of shape (n_samples, n_input_columns + n_prediction_columns). Returns predicted values.
         """
 
         # Params reference: https://cloud.google.com/vertex-ai/docs/generative-ai/learn/models
@@ -287,8 +284,4 @@ def predict(self, X: Union[bpd.DataFrame, bpd.Series]) -> bpd.DataFrame:
         options = {
             "flatten_json_output": True,
         }
-        df = self._bqml_model.generate_text_embedding(X, options)
-        return cast(
-            bpd.DataFrame,
-            df[[_EMBED_TEXT_RESULT_COLUMN]],
-        )
+        return self._bqml_model.generate_text_embedding(X, options)
diff --git a/notebooks/getting_started/ml_fundamentals.ipynb b/notebooks/getting_started/ml_fundamentals.ipynb
index 2f566dd704..165bd90f31 100644
--- a/notebooks/getting_started/ml_fundamentals.ipynb
+++ b/notebooks/getting_started/ml_fundamentals.ipynb
@@ -14,46 +14,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "0c8a8bc0b4d64448aef68d6a98fae666",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "HTML(value='Query job 28e903c6-e874-4b99-8f53-0755e0b0c188 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "8955d1977e4a4fd2aae991763cd7843a",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "HTML(value='Query job 32d772f8-3d61-43bf-a152-d930e3ecbf29 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e970e14dff4a434a9641abab6a7a7cf5",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 7ddb1bda-402a-4e8e-8476-7904010fb4ef is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:7ddb1bda-402a-4e8e-8476-7904010fb4ef&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 5a435e8f-9960-4fec-a8d8-1230e7b229a3 is DONE. 28.9 kB processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -61,13 +31,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9680fd748e0546b4a010fda0155c5027",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job e8aba858-7660-4274-8d90-8d2b0382f8f6 is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:e8aba858-7660-4274-8d90-8d2b0382f8f6&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 7950d6a7-3747-4454-bba2-9660e830647f is DONE. 31.7 kB processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -117,250 +85,250 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>36.6</td>\n",
-       "      <td>18.4</td>\n",
-       "      <td>184.0</td>\n",
-       "      <td>3475.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>40.1</td>\n",
+       "      <td>18.9</td>\n",
+       "      <td>188.0</td>\n",
+       "      <td>4300.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>39.8</td>\n",
-       "      <td>19.1</td>\n",
-       "      <td>184.0</td>\n",
-       "      <td>4650.0</td>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>39.1</td>\n",
+       "      <td>18.7</td>\n",
+       "      <td>181.0</td>\n",
+       "      <td>3750.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>40.9</td>\n",
-       "      <td>18.9</td>\n",
-       "      <td>184.0</td>\n",
-       "      <td>3900.0</td>\n",
-       "      <td>MALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>47.4</td>\n",
+       "      <td>14.6</td>\n",
+       "      <td>212.0</td>\n",
+       "      <td>4725.0</td>\n",
+       "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>46.5</td>\n",
-       "      <td>17.9</td>\n",
-       "      <td>192.0</td>\n",
-       "      <td>3500.0</td>\n",
+       "      <td>42.5</td>\n",
+       "      <td>16.7</td>\n",
+       "      <td>187.0</td>\n",
+       "      <td>3350.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>37.3</td>\n",
-       "      <td>16.8</td>\n",
-       "      <td>192.0</td>\n",
-       "      <td>3000.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>43.2</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>197.0</td>\n",
+       "      <td>4775.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>43.2</td>\n",
-       "      <td>18.5</td>\n",
-       "      <td>192.0</td>\n",
-       "      <td>4100.0</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>46.7</td>\n",
+       "      <td>15.3</td>\n",
+       "      <td>219.0</td>\n",
+       "      <td>5200.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>46.9</td>\n",
-       "      <td>16.6</td>\n",
-       "      <td>192.0</td>\n",
-       "      <td>2700.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>41.3</td>\n",
+       "      <td>21.1</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>4400.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>50.5</td>\n",
-       "      <td>18.4</td>\n",
-       "      <td>200.0</td>\n",
-       "      <td>3400.0</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>45.2</td>\n",
+       "      <td>13.8</td>\n",
+       "      <td>215.0</td>\n",
+       "      <td>4750.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>49.5</td>\n",
-       "      <td>19.0</td>\n",
-       "      <td>200.0</td>\n",
-       "      <td>3800.0</td>\n",
-       "      <td>MALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>46.5</td>\n",
+       "      <td>13.5</td>\n",
+       "      <td>210.0</td>\n",
+       "      <td>4550.0</td>\n",
+       "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>40.2</td>\n",
-       "      <td>20.1</td>\n",
-       "      <td>200.0</td>\n",
-       "      <td>3975.0</td>\n",
-       "      <td>MALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>50.5</td>\n",
+       "      <td>15.2</td>\n",
+       "      <td>216.0</td>\n",
+       "      <td>5000.0</td>\n",
+       "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>40.8</td>\n",
-       "      <td>18.9</td>\n",
-       "      <td>208.0</td>\n",
-       "      <td>4300.0</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>48.2</td>\n",
+       "      <td>15.6</td>\n",
+       "      <td>221.0</td>\n",
+       "      <td>5100.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>39.0</td>\n",
-       "      <td>18.7</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3650.0</td>\n",
-       "      <td>MALE</td>\n",
+       "      <td>38.1</td>\n",
+       "      <td>18.6</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>3700.0</td>\n",
+       "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>37.0</td>\n",
-       "      <td>16.9</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3000.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>50.7</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>223.0</td>\n",
+       "      <td>5550.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>47.0</td>\n",
-       "      <td>17.3</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3700.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>37.8</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>4250.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>34.0</td>\n",
-       "      <td>17.1</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3400.0</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>17.9</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>3450.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>37.0</td>\n",
-       "      <td>16.5</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3400.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>48.7</td>\n",
+       "      <td>15.7</td>\n",
+       "      <td>208.0</td>\n",
+       "      <td>5350.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>45.7</td>\n",
-       "      <td>17.3</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3600.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>34.6</td>\n",
+       "      <td>21.1</td>\n",
+       "      <td>198.0</td>\n",
+       "      <td>4400.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>50.6</td>\n",
-       "      <td>19.4</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3800.0</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>46.8</td>\n",
+       "      <td>15.4</td>\n",
+       "      <td>215.0</td>\n",
+       "      <td>5150.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>39.7</td>\n",
-       "      <td>17.9</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>4250.0</td>\n",
+       "      <td>50.3</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>197.0</td>\n",
+       "      <td>3300.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>37.8</td>\n",
+       "      <td>37.2</td>\n",
        "      <td>18.1</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3750.0</td>\n",
+       "      <td>178.0</td>\n",
+       "      <td>3900.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>20</th>\n",
        "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>46.6</td>\n",
-       "      <td>17.8</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3800.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>18.8</td>\n",
+       "      <td>203.0</td>\n",
+       "      <td>4100.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>21</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>51.3</td>\n",
-       "      <td>19.2</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3650.0</td>\n",
-       "      <td>MALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>40.5</td>\n",
+       "      <td>17.9</td>\n",
+       "      <td>187.0</td>\n",
+       "      <td>3200.0</td>\n",
+       "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>40.2</td>\n",
-       "      <td>17.1</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3400.0</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>45.5</td>\n",
+       "      <td>13.9</td>\n",
+       "      <td>210.0</td>\n",
+       "      <td>4200.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>23</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>36.8</td>\n",
+       "      <td>42.2</td>\n",
        "      <td>18.5</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3500.0</td>\n",
+       "      <td>180.0</td>\n",
+       "      <td>3550.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>24</th>\n",
        "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>49.6</td>\n",
-       "      <td>18.2</td>\n",
-       "      <td>193.0</td>\n",
+       "      <td>51.7</td>\n",
+       "      <td>20.3</td>\n",
+       "      <td>194.0</td>\n",
        "      <td>3775.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
@@ -370,86 +338,86 @@
        "</div>[334 rows x 7 columns in total]"
       ],
       "text/plain": [
-       "                                              species island  \\\n",
-       "penguin_id                                                     \n",
-       "0                 Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "1                 Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "2                 Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "3           Chinstrap penguin (Pygoscelis antarctica)  Dream   \n",
-       "4                 Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "5                 Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "6           Chinstrap penguin (Pygoscelis antarctica)  Dream   \n",
-       "7           Chinstrap penguin (Pygoscelis antarctica)  Dream   \n",
-       "8           Chinstrap penguin (Pygoscelis antarctica)  Dream   \n",
-       "9                 Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "10                Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "11                Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "12                Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "13          Chinstrap penguin (Pygoscelis antarctica)  Dream   \n",
-       "14                Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "15                Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "16          Chinstrap penguin (Pygoscelis antarctica)  Dream   \n",
-       "17          Chinstrap penguin (Pygoscelis antarctica)  Dream   \n",
-       "18                Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "19                Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "20          Chinstrap penguin (Pygoscelis antarctica)  Dream   \n",
-       "21          Chinstrap penguin (Pygoscelis antarctica)  Dream   \n",
-       "22                Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "23                Adelie Penguin (Pygoscelis adeliae)  Dream   \n",
-       "24          Chinstrap penguin (Pygoscelis antarctica)  Dream   \n",
+       "                                              species     island  \\\n",
+       "penguin_id                                                         \n",
+       "0                 Adelie Penguin (Pygoscelis adeliae)     Biscoe   \n",
+       "1                 Adelie Penguin (Pygoscelis adeliae)  Torgersen   \n",
+       "2                   Gentoo penguin (Pygoscelis papua)     Biscoe   \n",
+       "3           Chinstrap penguin (Pygoscelis antarctica)      Dream   \n",
+       "4                 Adelie Penguin (Pygoscelis adeliae)     Biscoe   \n",
+       "5                   Gentoo penguin (Pygoscelis papua)     Biscoe   \n",
+       "6                 Adelie Penguin (Pygoscelis adeliae)     Biscoe   \n",
+       "7                   Gentoo penguin (Pygoscelis papua)     Biscoe   \n",
+       "8                   Gentoo penguin (Pygoscelis papua)     Biscoe   \n",
+       "9                   Gentoo penguin (Pygoscelis papua)     Biscoe   \n",
+       "10                  Gentoo penguin (Pygoscelis papua)     Biscoe   \n",
+       "11                Adelie Penguin (Pygoscelis adeliae)      Dream   \n",
+       "12                  Gentoo penguin (Pygoscelis papua)     Biscoe   \n",
+       "13                Adelie Penguin (Pygoscelis adeliae)     Biscoe   \n",
+       "14                Adelie Penguin (Pygoscelis adeliae)     Biscoe   \n",
+       "15                  Gentoo penguin (Pygoscelis papua)     Biscoe   \n",
+       "16                Adelie Penguin (Pygoscelis adeliae)  Torgersen   \n",
+       "17                  Gentoo penguin (Pygoscelis papua)     Biscoe   \n",
+       "18          Chinstrap penguin (Pygoscelis antarctica)      Dream   \n",
+       "19                Adelie Penguin (Pygoscelis adeliae)      Dream   \n",
+       "20          Chinstrap penguin (Pygoscelis antarctica)      Dream   \n",
+       "21                Adelie Penguin (Pygoscelis adeliae)     Biscoe   \n",
+       "22                  Gentoo penguin (Pygoscelis papua)     Biscoe   \n",
+       "23                Adelie Penguin (Pygoscelis adeliae)      Dream   \n",
+       "24          Chinstrap penguin (Pygoscelis antarctica)      Dream   \n",
        "\n",
        "            culmen_length_mm  culmen_depth_mm  flipper_length_mm  body_mass_g  \\\n",
        "penguin_id                                                                      \n",
-       "0                       36.6             18.4              184.0       3475.0   \n",
-       "1                       39.8             19.1              184.0       4650.0   \n",
-       "2                       40.9             18.9              184.0       3900.0   \n",
-       "3                       46.5             17.9              192.0       3500.0   \n",
-       "4                       37.3             16.8              192.0       3000.0   \n",
-       "5                       43.2             18.5              192.0       4100.0   \n",
-       "6                       46.9             16.6              192.0       2700.0   \n",
-       "7                       50.5             18.4              200.0       3400.0   \n",
-       "8                       49.5             19.0              200.0       3800.0   \n",
-       "9                       40.2             20.1              200.0       3975.0   \n",
-       "10                      40.8             18.9              208.0       4300.0   \n",
-       "11                      39.0             18.7              185.0       3650.0   \n",
-       "12                      37.0             16.9              185.0       3000.0   \n",
-       "13                      47.0             17.3              185.0       3700.0   \n",
-       "14                      34.0             17.1              185.0       3400.0   \n",
-       "15                      37.0             16.5              185.0       3400.0   \n",
-       "16                      45.7             17.3              193.0       3600.0   \n",
-       "17                      50.6             19.4              193.0       3800.0   \n",
-       "18                      39.7             17.9              193.0       4250.0   \n",
-       "19                      37.8             18.1              193.0       3750.0   \n",
-       "20                      46.6             17.8              193.0       3800.0   \n",
-       "21                      51.3             19.2              193.0       3650.0   \n",
-       "22                      40.2             17.1              193.0       3400.0   \n",
-       "23                      36.8             18.5              193.0       3500.0   \n",
-       "24                      49.6             18.2              193.0       3775.0   \n",
+       "0                       40.1             18.9              188.0       4300.0   \n",
+       "1                       39.1             18.7              181.0       3750.0   \n",
+       "2                       47.4             14.6              212.0       4725.0   \n",
+       "3                       42.5             16.7              187.0       3350.0   \n",
+       "4                       43.2             19.0              197.0       4775.0   \n",
+       "5                       46.7             15.3              219.0       5200.0   \n",
+       "6                       41.3             21.1              195.0       4400.0   \n",
+       "7                       45.2             13.8              215.0       4750.0   \n",
+       "8                       46.5             13.5              210.0       4550.0   \n",
+       "9                       50.5             15.2              216.0       5000.0   \n",
+       "10                      48.2             15.6              221.0       5100.0   \n",
+       "11                      38.1             18.6              190.0       3700.0   \n",
+       "12                      50.7             15.0              223.0       5550.0   \n",
+       "13                      37.8             20.0              190.0       4250.0   \n",
+       "14                      35.0             17.9              190.0       3450.0   \n",
+       "15                      48.7             15.7              208.0       5350.0   \n",
+       "16                      34.6             21.1              198.0       4400.0   \n",
+       "17                      46.8             15.4              215.0       5150.0   \n",
+       "18                      50.3             20.0              197.0       3300.0   \n",
+       "19                      37.2             18.1              178.0       3900.0   \n",
+       "20                      51.0             18.8              203.0       4100.0   \n",
+       "21                      40.5             17.9              187.0       3200.0   \n",
+       "22                      45.5             13.9              210.0       4200.0   \n",
+       "23                      42.2             18.5              180.0       3550.0   \n",
+       "24                      51.7             20.3              194.0       3775.0   \n",
        "\n",
        "               sex  \n",
        "penguin_id          \n",
-       "0           FEMALE  \n",
+       "0             MALE  \n",
        "1             MALE  \n",
-       "2             MALE  \n",
+       "2           FEMALE  \n",
        "3           FEMALE  \n",
-       "4           FEMALE  \n",
+       "4             MALE  \n",
        "5             MALE  \n",
-       "6           FEMALE  \n",
+       "6             MALE  \n",
        "7           FEMALE  \n",
-       "8             MALE  \n",
-       "9             MALE  \n",
+       "8           FEMALE  \n",
+       "9           FEMALE  \n",
        "10            MALE  \n",
-       "11            MALE  \n",
-       "12          FEMALE  \n",
-       "13          FEMALE  \n",
+       "11          FEMALE  \n",
+       "12            MALE  \n",
+       "13            MALE  \n",
        "14          FEMALE  \n",
-       "15          FEMALE  \n",
-       "16          FEMALE  \n",
+       "15            MALE  \n",
+       "16            MALE  \n",
        "17            MALE  \n",
        "18            MALE  \n",
        "19            MALE  \n",
-       "20          FEMALE  \n",
-       "21            MALE  \n",
+       "20            MALE  \n",
+       "21          FEMALE  \n",
        "22          FEMALE  \n",
        "23          FEMALE  \n",
        "24            MALE  \n",
@@ -458,7 +426,7 @@
        "[334 rows x 7 columns]"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -490,18 +458,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "171160f246eb43d1832aeefb055c0851",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job deda90a8-6ec7-419c-8067-e85777bd916f is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:deda90a8-6ec7-419c-8067-e85777bd916f&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 1408053d-cb80-4870-af28-e94b90a20a6d is DONE. 28.9 kB processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -509,13 +475,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "eaffac40f94745728e6bd618bebd2c53",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job efe8fa0a-d450-475a-99d5-36beeb985247 is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:efe8fa0a-d450-475a-99d5-36beeb985247&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 262885fe-973c-4338-a853-227f9db4835a is DONE. 31.7 kB processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -523,13 +487,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "68e7ecdc639f4d3ab482830bf6a9da04",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 5022c56d-e605-4cab-be1b-1ecf189588a1 is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:5022c56d-e605-4cab-be1b-1ecf189588a1&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job fb1dc831-7f6f-42ce-96da-1292d73919b4 is DONE. 31.7 kB processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -537,13 +499,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ebfe197fd88348129ebe2f7d288bf4b9",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 175bd293-d448-4510-b926-1d8cfb4eb5e7 is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:175bd293-d448-4510-b926-1d8cfb4eb5e7&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job e79add79-f1e4-4cf0-bb97-04d153222f19 is DONE. 31.7 kB processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -551,13 +511,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2ae69ea7da5247e8a1f7cd0e049629cb",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job a3a2e68c-f5f3-4237-99ad-44974f29d090 is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:a3a2e68c-f5f3-4237-99ad-44974f29d090&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job cb5ee343-f86e-4795-b0ce-d58854e72e5c is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -596,18 +554,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5ed4206cd3ad4cd485315605bf033df2",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job db3365fb-67ca-44cc-a117-88a80dc63cca is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:db3365fb-67ca-44cc-a117-88a80dc63cca&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job e65af31c-feda-468d-89c9-dec033574640 is DONE. 31.7 kB processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -615,13 +571,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ac72db21945542558fdd62093d9dc0c3",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job ab78f7ab-a115-448b-92d0-19c091a831ca is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:ab78f7ab-a115-448b-92d0-19c091a831ca&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 0455f252-2b94-457e-bad5-672b91d9b51f is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -667,47 +621,47 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>156</th>\n",
-       "      <td>Biscoe</td>\n",
-       "      <td>46.2</td>\n",
-       "      <td>14.5</td>\n",
-       "      <td>209.0</td>\n",
-       "      <td>FEMALE</td>\n",
-       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <th>249</th>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>41.1</td>\n",
+       "      <td>18.6</td>\n",
+       "      <td>189.0</td>\n",
+       "      <td>MALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>189</th>\n",
+       "      <th>36</th>\n",
        "      <td>Biscoe</td>\n",
-       "      <td>35.3</td>\n",
-       "      <td>18.9</td>\n",
-       "      <td>187.0</td>\n",
+       "      <td>43.4</td>\n",
+       "      <td>14.4</td>\n",
+       "      <td>218.0</td>\n",
        "      <td>FEMALE</td>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>279</th>\n",
+       "      <th>74</th>\n",
        "      <td>Biscoe</td>\n",
-       "      <td>45.1</td>\n",
-       "      <td>14.5</td>\n",
-       "      <td>215.0</td>\n",
+       "      <td>42.8</td>\n",
+       "      <td>14.2</td>\n",
+       "      <td>209.0</td>\n",
        "      <td>FEMALE</td>\n",
        "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>245</th>\n",
-       "      <td>Biscoe</td>\n",
-       "      <td>49.5</td>\n",
-       "      <td>16.2</td>\n",
-       "      <td>229.0</td>\n",
-       "      <td>MALE</td>\n",
-       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <th>235</th>\n",
+       "      <td>Dream</td>\n",
+       "      <td>34.0</td>\n",
+       "      <td>17.1</td>\n",
+       "      <td>185.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>343</th>\n",
-       "      <td>Torgersen</td>\n",
-       "      <td>37.3</td>\n",
-       "      <td>20.5</td>\n",
-       "      <td>199.0</td>\n",
+       "      <th>117</th>\n",
+       "      <td>Dream</td>\n",
+       "      <td>37.8</td>\n",
+       "      <td>18.1</td>\n",
+       "      <td>193.0</td>\n",
        "      <td>MALE</td>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
@@ -719,24 +673,24 @@
       "text/plain": [
        "               island  culmen_length_mm  culmen_depth_mm  flipper_length_mm  \\\n",
        "penguin_id                                                                    \n",
-       "156            Biscoe              46.2             14.5              209.0   \n",
-       "189            Biscoe              35.3             18.9              187.0   \n",
-       "279            Biscoe              45.1             14.5              215.0   \n",
-       "245            Biscoe              49.5             16.2              229.0   \n",
-       "343         Torgersen              37.3             20.5              199.0   \n",
+       "249         Torgersen              41.1             18.6              189.0   \n",
+       "36             Biscoe              43.4             14.4              218.0   \n",
+       "74             Biscoe              42.8             14.2              209.0   \n",
+       "235             Dream              34.0             17.1              185.0   \n",
+       "117             Dream              37.8             18.1              193.0   \n",
        "\n",
        "               sex                              species  \n",
        "penguin_id                                               \n",
-       "156         FEMALE    Gentoo penguin (Pygoscelis papua)  \n",
-       "189         FEMALE  Adelie Penguin (Pygoscelis adeliae)  \n",
-       "279         FEMALE    Gentoo penguin (Pygoscelis papua)  \n",
-       "245           MALE    Gentoo penguin (Pygoscelis papua)  \n",
-       "343           MALE  Adelie Penguin (Pygoscelis adeliae)  \n",
+       "249           MALE  Adelie Penguin (Pygoscelis adeliae)  \n",
+       "36          FEMALE    Gentoo penguin (Pygoscelis papua)  \n",
+       "74          FEMALE    Gentoo penguin (Pygoscelis papua)  \n",
+       "235         FEMALE  Adelie Penguin (Pygoscelis adeliae)  \n",
+       "117           MALE  Adelie Penguin (Pygoscelis adeliae)  \n",
        "\n",
        "[5 rows x 6 columns]"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -749,18 +703,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "d6dd794f89724099950dcc927d63d0f5",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 22a72cad-11a6-4f8e-b16d-f92853b8112e is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:22a72cad-11a6-4f8e-b16d-f92853b8112e&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job d5a173bd-a7dc-42fa-8468-b088d47ccfe0 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -768,13 +720,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a8ab7ca12e0d43a6803483480e837c6e",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job bc952727-8806-4fe2-abf2-c3a8a2bd9b6d is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:bc952727-8806-4fe2-abf2-c3a8a2bd9b6d&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job c6b6518b-2689-4dc1-a5b0-2a9ab75301eb is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -810,24 +760,24 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>156</th>\n",
-       "      <td>4800.0</td>\n",
+       "      <th>249</th>\n",
+       "      <td>3325.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>189</th>\n",
-       "      <td>3800.0</td>\n",
+       "      <th>36</th>\n",
+       "      <td>4600.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>279</th>\n",
-       "      <td>5000.0</td>\n",
+       "      <th>74</th>\n",
+       "      <td>4700.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>245</th>\n",
-       "      <td>5800.0</td>\n",
+       "      <th>235</th>\n",
+       "      <td>3400.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>343</th>\n",
-       "      <td>3775.0</td>\n",
+       "      <th>117</th>\n",
+       "      <td>3750.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -837,16 +787,16 @@
       "text/plain": [
        "            body_mass_g\n",
        "penguin_id             \n",
-       "156              4800.0\n",
-       "189              3800.0\n",
-       "279              5000.0\n",
-       "245              5800.0\n",
-       "343              3775.0\n",
+       "249              3325.0\n",
+       "36               4600.0\n",
+       "74               4700.0\n",
+       "235              3400.0\n",
+       "117              3750.0\n",
        "\n",
        "[5 rows x 1 columns]"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -880,18 +830,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "380c57dc3fe54fbd8ad2fb23f1e66e37",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job f239341e-785f-43e1-bfe0-683132d6f15f is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:f239341e-785f-43e1-bfe0-683132d6f15f&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 03a0eb1c-747e-4c2a-b7b5-d3e4e5a78134 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -899,13 +847,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3db47aadba854beca71960d846838dc4",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 2d5bbbb9-efc4-4f4e-a8dc-2c7b66b0e5e0 is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:2d5bbbb9-efc4-4f4e-a8dc-2c7b66b0e5e0&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 70608c84-dac8-4e77-8a9e-00d823b24f37 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -913,13 +859,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1de81f2944a44cbda3f16fa8a1fae813",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 66120e1c-2471-4a0c-8b82-aeb189c8866a is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:66120e1c-2471-4a0c-8b82-aeb189c8866a&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job d18fdc32-2152-45d3-8c62-bf9b1556ec47 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -927,13 +871,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b06cae61a4534388a4e9ed26ce442cc2",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 62825fc4-5b77-43e5-a3e4-525ebfd1285b is DONE. 2.1 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:62825fc4-5b77-43e5-a3e4-525ebfd1285b&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 2a022682-535f-4dc0-80ba-1640306ad9ef is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -941,13 +883,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "977c8eae2c9848e98c5478c41af82633",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 656d1d69-b4ff-4db6-9f2d-28dcf91e2fd7 is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:656d1d69-b4ff-4db6-9f2d-28dcf91e2fd7&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job c145b39d-7d02-4394-80f0-fc605b2ba256 is DONE. 0 Bytes processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -955,13 +895,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "aefc3085fee04c438d0327d400b4b72a",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 466507c8-1474-4725-93e5-baf8ee292e39 is DONE. 8.5 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:466507c8-1474-4725-93e5-baf8ee292e39&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job fc156a2b-db95-44a3-9ad1-d95b9d290080 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1002,153 +940,153 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>-1.344188</td>\n",
-       "      <td>0.642519</td>\n",
-       "      <td>-1.193942</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>-0.750047</td>\n",
-       "      <td>1.005876</td>\n",
-       "      <td>-1.193942</td>\n",
+       "      <td>-0.750505</td>\n",
+       "      <td>0.84903</td>\n",
+       "      <td>-0.937262</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>-0.545811</td>\n",
-       "      <td>0.90206</td>\n",
-       "      <td>-1.193942</td>\n",
+       "      <td>0.622496</td>\n",
+       "      <td>-1.322402</td>\n",
+       "      <td>0.804051</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>-1.214219</td>\n",
-       "      <td>-0.188011</td>\n",
-       "      <td>-0.619171</td>\n",
+       "      <th>3</th>\n",
+       "      <td>-0.299107</td>\n",
+       "      <td>-0.261935</td>\n",
+       "      <td>-1.009817</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>-0.118772</td>\n",
-       "      <td>0.694427</td>\n",
-       "      <td>-0.619171</td>\n",
+       "      <td>0.490839</td>\n",
+       "      <td>-0.968913</td>\n",
+       "      <td>1.311935</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
-       "      <td>0.568203</td>\n",
-       "      <td>-0.291828</td>\n",
-       "      <td>-0.619171</td>\n",
+       "      <td>-0.524806</td>\n",
+       "      <td>1.959995</td>\n",
+       "      <td>-0.429379</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
-       "      <td>1.236611</td>\n",
-       "      <td>0.642519</td>\n",
-       "      <td>-0.044401</td>\n",
+       "      <td>0.208715</td>\n",
+       "      <td>-1.726389</td>\n",
+       "      <td>1.021716</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
-       "      <td>-0.675779</td>\n",
-       "      <td>1.524957</td>\n",
-       "      <td>-0.044401</td>\n",
+       "      <td>1.205551</td>\n",
+       "      <td>-1.019412</td>\n",
+       "      <td>1.09427</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
-       "      <td>-0.564378</td>\n",
-       "      <td>0.90206</td>\n",
-       "      <td>0.530369</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>11</th>\n",
-       "      <td>-0.898582</td>\n",
-       "      <td>0.798243</td>\n",
-       "      <td>-1.122096</td>\n",
+       "      <td>0.772962</td>\n",
+       "      <td>-0.817418</td>\n",
+       "      <td>1.457044</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
-       "      <td>-1.26992</td>\n",
-       "      <td>-0.136103</td>\n",
-       "      <td>-1.122096</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>0.58677</td>\n",
-       "      <td>0.071529</td>\n",
-       "      <td>-1.122096</td>\n",
+       "      <td>1.243168</td>\n",
+       "      <td>-1.120408</td>\n",
+       "      <td>1.602153</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
-       "      <td>-1.826927</td>\n",
-       "      <td>-0.032287</td>\n",
-       "      <td>-1.122096</td>\n",
+       "      <td>-1.709725</td>\n",
+       "      <td>0.344046</td>\n",
+       "      <td>-0.792152</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>-1.26992</td>\n",
-       "      <td>-0.343736</td>\n",
-       "      <td>-1.122096</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>16</th>\n",
-       "      <td>0.3454</td>\n",
-       "      <td>0.071529</td>\n",
-       "      <td>-0.547325</td>\n",
+       "      <th>17</th>\n",
+       "      <td>0.509647</td>\n",
+       "      <td>-0.918415</td>\n",
+       "      <td>1.021716</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18</th>\n",
-       "      <td>-0.768614</td>\n",
-       "      <td>0.382978</td>\n",
-       "      <td>-0.547325</td>\n",
+       "      <td>1.167935</td>\n",
+       "      <td>1.404513</td>\n",
+       "      <td>-0.284269</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19</th>\n",
-       "      <td>-1.121385</td>\n",
-       "      <td>0.486795</td>\n",
-       "      <td>-0.547325</td>\n",
+       "      <td>-1.295944</td>\n",
+       "      <td>0.445043</td>\n",
+       "      <td>-1.662809</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>20</th>\n",
-       "      <td>0.512502</td>\n",
-       "      <td>0.33107</td>\n",
-       "      <td>-0.547325</td>\n",
+       "      <td>1.299593</td>\n",
+       "      <td>0.798532</td>\n",
+       "      <td>0.151059</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>21</th>\n",
-       "      <td>1.385146</td>\n",
-       "      <td>1.057784</td>\n",
-       "      <td>-0.547325</td>\n",
+       "      <td>-0.675272</td>\n",
+       "      <td>0.344046</td>\n",
+       "      <td>-1.009817</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22</th>\n",
-       "      <td>-0.675779</td>\n",
-       "      <td>-0.032287</td>\n",
-       "      <td>-0.547325</td>\n",
+       "      <td>0.26514</td>\n",
+       "      <td>-1.675891</td>\n",
+       "      <td>0.658942</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>24</th>\n",
-       "      <td>1.069509</td>\n",
-       "      <td>0.538703</td>\n",
-       "      <td>-0.547325</td>\n",
+       "      <td>1.43125</td>\n",
+       "      <td>1.556008</td>\n",
+       "      <td>-0.501934</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>0.302756</td>\n",
+       "      <td>0.041055</td>\n",
+       "      <td>-0.574488</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>26</th>\n",
-       "      <td>-0.43441</td>\n",
-       "      <td>0.694427</td>\n",
-       "      <td>0.027445</td>\n",
+       "      <td>0.302756</td>\n",
+       "      <td>-1.675891</td>\n",
+       "      <td>0.949161</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>0.227523</td>\n",
+       "      <td>-1.776888</td>\n",
+       "      <td>0.658942</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>28</th>\n",
-       "      <td>1.923586</td>\n",
-       "      <td>1.888314</td>\n",
-       "      <td>0.027445</td>\n",
+       "      <td>1.318401</td>\n",
+       "      <td>-0.362932</td>\n",
+       "      <td>1.747263</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>2.202388</td>\n",
+       "      <td>1.303516</td>\n",
+       "      <td>0.441278</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>30</th>\n",
-       "      <td>1.292312</td>\n",
-       "      <td>0.694427</td>\n",
-       "      <td>0.027445</td>\n",
+       "      <td>-0.919779</td>\n",
+       "      <td>1.959995</td>\n",
+       "      <td>-0.356824</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>31</th>\n",
-       "      <td>-1.994029</td>\n",
-       "      <td>-0.551368</td>\n",
-       "      <td>-1.62502</td>\n",
+       "      <td>1.036277</td>\n",
+       "      <td>-0.615424</td>\n",
+       "      <td>1.747263</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>-0.223874</td>\n",
+       "      <td>0.19255</td>\n",
+       "      <td>-0.356824</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1158,65 +1096,65 @@
       "text/plain": [
        "            standard_scaled_culmen_length_mm  standard_scaled_culmen_depth_mm  \\\n",
        "penguin_id                                                                      \n",
-       "0                                  -1.344188                         0.642519   \n",
-       "1                                  -0.750047                         1.005876   \n",
-       "2                                  -0.545811                          0.90206   \n",
-       "4                                  -1.214219                        -0.188011   \n",
-       "5                                  -0.118772                         0.694427   \n",
-       "6                                   0.568203                        -0.291828   \n",
-       "7                                   1.236611                         0.642519   \n",
-       "9                                  -0.675779                         1.524957   \n",
-       "10                                 -0.564378                          0.90206   \n",
-       "11                                 -0.898582                         0.798243   \n",
-       "12                                  -1.26992                        -0.136103   \n",
-       "13                                   0.58677                         0.071529   \n",
-       "14                                 -1.826927                        -0.032287   \n",
-       "15                                  -1.26992                        -0.343736   \n",
-       "16                                    0.3454                         0.071529   \n",
-       "18                                 -0.768614                         0.382978   \n",
-       "19                                 -1.121385                         0.486795   \n",
-       "20                                  0.512502                          0.33107   \n",
-       "21                                  1.385146                         1.057784   \n",
-       "22                                 -0.675779                        -0.032287   \n",
-       "24                                  1.069509                         0.538703   \n",
-       "26                                  -0.43441                         0.694427   \n",
-       "28                                  1.923586                         1.888314   \n",
-       "30                                  1.292312                         0.694427   \n",
-       "31                                 -1.994029                        -0.551368   \n",
+       "0                                  -0.750505                          0.84903   \n",
+       "2                                   0.622496                        -1.322402   \n",
+       "3                                  -0.299107                        -0.261935   \n",
+       "5                                   0.490839                        -0.968913   \n",
+       "6                                  -0.524806                         1.959995   \n",
+       "7                                   0.208715                        -1.726389   \n",
+       "9                                   1.205551                        -1.019412   \n",
+       "10                                  0.772962                        -0.817418   \n",
+       "12                                  1.243168                        -1.120408   \n",
+       "14                                 -1.709725                         0.344046   \n",
+       "17                                  0.509647                        -0.918415   \n",
+       "18                                  1.167935                         1.404513   \n",
+       "19                                 -1.295944                         0.445043   \n",
+       "20                                  1.299593                         0.798532   \n",
+       "21                                 -0.675272                         0.344046   \n",
+       "22                                   0.26514                        -1.675891   \n",
+       "24                                   1.43125                         1.556008   \n",
+       "25                                  0.302756                         0.041055   \n",
+       "26                                  0.302756                        -1.675891   \n",
+       "27                                  0.227523                        -1.776888   \n",
+       "28                                  1.318401                        -0.362932   \n",
+       "29                                  2.202388                         1.303516   \n",
+       "30                                 -0.919779                         1.959995   \n",
+       "31                                  1.036277                        -0.615424   \n",
+       "32                                 -0.223874                          0.19255   \n",
        "\n",
        "            standard_scaled_flipper_length_mm  \n",
        "penguin_id                                     \n",
-       "0                                   -1.193942  \n",
-       "1                                   -1.193942  \n",
-       "2                                   -1.193942  \n",
-       "4                                   -0.619171  \n",
-       "5                                   -0.619171  \n",
-       "6                                   -0.619171  \n",
-       "7                                   -0.044401  \n",
-       "9                                   -0.044401  \n",
-       "10                                   0.530369  \n",
-       "11                                  -1.122096  \n",
-       "12                                  -1.122096  \n",
-       "13                                  -1.122096  \n",
-       "14                                  -1.122096  \n",
-       "15                                  -1.122096  \n",
-       "16                                  -0.547325  \n",
-       "18                                  -0.547325  \n",
-       "19                                  -0.547325  \n",
-       "20                                  -0.547325  \n",
-       "21                                  -0.547325  \n",
-       "22                                  -0.547325  \n",
-       "24                                  -0.547325  \n",
-       "26                                   0.027445  \n",
-       "28                                   0.027445  \n",
-       "30                                   0.027445  \n",
-       "31                                   -1.62502  \n",
+       "0                                   -0.937262  \n",
+       "2                                    0.804051  \n",
+       "3                                   -1.009817  \n",
+       "5                                    1.311935  \n",
+       "6                                   -0.429379  \n",
+       "7                                    1.021716  \n",
+       "9                                     1.09427  \n",
+       "10                                   1.457044  \n",
+       "12                                   1.602153  \n",
+       "14                                  -0.792152  \n",
+       "17                                   1.021716  \n",
+       "18                                  -0.284269  \n",
+       "19                                  -1.662809  \n",
+       "20                                   0.151059  \n",
+       "21                                  -1.009817  \n",
+       "22                                   0.658942  \n",
+       "24                                  -0.501934  \n",
+       "25                                  -0.574488  \n",
+       "26                                   0.949161  \n",
+       "27                                   0.658942  \n",
+       "28                                   1.747263  \n",
+       "29                                   0.441278  \n",
+       "30                                  -0.356824  \n",
+       "31                                   1.747263  \n",
+       "32                                  -0.356824  \n",
        "...\n",
        "\n",
        "[267 rows x 3 columns]"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1237,32 +1175,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "74f3c24c0a434e12bf6a56dc4809b501",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "HTML(value='Query job c6268b07-0d3d-4fe0-971d-cc99fd98cd7e is RUNNING. <a target=\"_blank\" href=\"https://consol…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b6b5999749114de9971d9dcb6c9d1098",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 845c6cff-ac6c-46c1-8e9b-061519f1fa1a is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:845c6cff-ac6c-46c1-8e9b-061519f1fa1a&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 31550d88-fc7b-4fcb-9975-9ed24bf2e009 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1270,13 +1192,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5a04e46a7d0248b1ae523f2ca6903ee8",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 1e17f5f7-2956-4bdd-baa9-c07591481341 is DONE. 536 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:1e17f5f7-2956-4bdd-baa9-c07591481341&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 5ec7c8b1-037c-466c-a51e-963f8274e76b is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1284,13 +1204,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "62563820bfb245be85bbc1bf3dfb993c",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job e2fde7a6-67b4-45a4-91d4-1cb9eff66ae5 is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:e2fde7a6-67b4-45a4-91d4-1cb9eff66ae5&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 4e860716-bc41-4ef6-83ff-310d085ed7cc is DONE. 0 Bytes processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1298,13 +1216,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "98aff3bfded44868bf120451c89df9f5",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job e0683619-23c5-44fd-8930-9d3c9d02729a is DONE. 2.1 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:e0683619-23c5-44fd-8930-9d3c9d02729a&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 6b96a757-42fe-4b65-92fd-a3ae339fe769 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1344,154 +1260,154 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>0.493935</td>\n",
-       "      <td>0.382978</td>\n",
-       "      <td>-0.619171</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>1.050942</td>\n",
-       "      <td>0.953968</td>\n",
-       "      <td>-0.044401</td>\n",
+       "      <th>1</th>\n",
+       "      <td>-0.938587</td>\n",
+       "      <td>0.748033</td>\n",
+       "      <td>-1.445145</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>1.255178</td>\n",
-       "      <td>1.1616</td>\n",
-       "      <td>-0.547325</td>\n",
+       "      <th>4</th>\n",
+       "      <td>-0.16745</td>\n",
+       "      <td>0.899528</td>\n",
+       "      <td>-0.284269</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>-1.307054</td>\n",
-       "      <td>0.694427</td>\n",
-       "      <td>-0.547325</td>\n",
+       "      <th>8</th>\n",
+       "      <td>0.453222</td>\n",
+       "      <td>-1.877885</td>\n",
+       "      <td>0.658942</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25</th>\n",
-       "      <td>1.515114</td>\n",
-       "      <td>0.486795</td>\n",
-       "      <td>0.027445</td>\n",
+       "      <th>11</th>\n",
+       "      <td>-1.12667</td>\n",
+       "      <td>0.697535</td>\n",
+       "      <td>-0.792152</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>1.236611</td>\n",
-       "      <td>1.265417</td>\n",
-       "      <td>0.027445</td>\n",
+       "      <th>13</th>\n",
+       "      <td>-1.183094</td>\n",
+       "      <td>1.404513</td>\n",
+       "      <td>-0.792152</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>1.403713</td>\n",
-       "      <td>0.953968</td>\n",
-       "      <td>0.027445</td>\n",
+       "      <th>15</th>\n",
+       "      <td>0.867003</td>\n",
+       "      <td>-0.766919</td>\n",
+       "      <td>0.513833</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>34</th>\n",
-       "      <td>0.419668</td>\n",
-       "      <td>0.538703</td>\n",
-       "      <td>-1.62502</td>\n",
+       "      <th>16</th>\n",
+       "      <td>-1.784958</td>\n",
+       "      <td>1.959995</td>\n",
+       "      <td>-0.211715</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>35</th>\n",
-       "      <td>-1.455589</td>\n",
-       "      <td>0.694427</td>\n",
-       "      <td>-1.050249</td>\n",
+       "      <th>23</th>\n",
+       "      <td>-0.355532</td>\n",
+       "      <td>0.647036</td>\n",
+       "      <td>-1.5177</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>39</th>\n",
-       "      <td>0.326833</td>\n",
-       "      <td>1.1616</td>\n",
-       "      <td>-0.475479</td>\n",
+       "      <th>34</th>\n",
+       "      <td>-0.600039</td>\n",
+       "      <td>-1.776888</td>\n",
+       "      <td>0.949161</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>51</th>\n",
-       "      <td>-1.065684</td>\n",
-       "      <td>0.227254</td>\n",
-       "      <td>-0.978403</td>\n",
+       "      <th>36</th>\n",
+       "      <td>-0.129833</td>\n",
+       "      <td>-1.423399</td>\n",
+       "      <td>1.23938</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>52</th>\n",
-       "      <td>-0.248741</td>\n",
-       "      <td>0.071529</td>\n",
-       "      <td>-0.978403</td>\n",
+       "      <th>42</th>\n",
+       "      <td>-1.615684</td>\n",
+       "      <td>-0.514427</td>\n",
+       "      <td>-0.429379</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>60</th>\n",
-       "      <td>0.531069</td>\n",
-       "      <td>0.382978</td>\n",
-       "      <td>-0.403633</td>\n",
+       "      <th>48</th>\n",
+       "      <td>0.415606</td>\n",
+       "      <td>-0.716421</td>\n",
+       "      <td>1.021716</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>61</th>\n",
-       "      <td>0.401101</td>\n",
-       "      <td>0.90206</td>\n",
-       "      <td>-0.403633</td>\n",
+       "      <td>0.396797</td>\n",
+       "      <td>-1.170907</td>\n",
+       "      <td>1.457044</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>64</th>\n",
-       "      <td>-1.455589</td>\n",
-       "      <td>0.33107</td>\n",
-       "      <td>-0.403633</td>\n",
+       "      <td>0.434414</td>\n",
+       "      <td>-1.120408</td>\n",
+       "      <td>1.09427</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>65</th>\n",
-       "      <td>-0.564378</td>\n",
-       "      <td>0.642519</td>\n",
-       "      <td>-0.403633</td>\n",
+       "      <td>-1.220711</td>\n",
+       "      <td>1.051024</td>\n",
+       "      <td>-1.445145</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>67</th>\n",
-       "      <td>1.273745</td>\n",
-       "      <td>1.317325</td>\n",
-       "      <td>0.171138</td>\n",
+       "      <th>68</th>\n",
+       "      <td>-1.484026</td>\n",
+       "      <td>-0.009443</td>\n",
+       "      <td>-1.009817</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>83</th>\n",
-       "      <td>2.629128</td>\n",
-       "      <td>0.33107</td>\n",
-       "      <td>-1.409481</td>\n",
+       "      <th>70</th>\n",
+       "      <td>1.638141</td>\n",
+       "      <td>1.404513</td>\n",
+       "      <td>0.296168</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>85</th>\n",
-       "      <td>-1.288487</td>\n",
-       "      <td>0.746335</td>\n",
-       "      <td>-0.83471</td>\n",
+       "      <th>72</th>\n",
+       "      <td>0.829387</td>\n",
+       "      <td>0.142052</td>\n",
+       "      <td>-0.719598</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>93</th>\n",
-       "      <td>-0.508677</td>\n",
-       "      <td>0.486795</td>\n",
-       "      <td>0.314831</td>\n",
+       "      <th>74</th>\n",
+       "      <td>-0.242683</td>\n",
+       "      <td>-1.524396</td>\n",
+       "      <td>0.586387</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>104</th>\n",
-       "      <td>0.382534</td>\n",
-       "      <td>-0.032287</td>\n",
-       "      <td>-0.762864</td>\n",
+       "      <th>77</th>\n",
+       "      <td>-1.277136</td>\n",
+       "      <td>-0.211437</td>\n",
+       "      <td>-0.647043</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>105</th>\n",
-       "      <td>-1.065684</td>\n",
-       "      <td>0.746335</td>\n",
-       "      <td>-0.762864</td>\n",
+       "      <th>81</th>\n",
+       "      <td>0.208715</td>\n",
+       "      <td>-1.221405</td>\n",
+       "      <td>0.804051</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>91</th>\n",
+       "      <td>1.261976</td>\n",
+       "      <td>0.647036</td>\n",
+       "      <td>0.005949</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>108</th>\n",
-       "      <td>1.162343</td>\n",
-       "      <td>0.382978</td>\n",
-       "      <td>-0.762864</td>\n",
+       "      <th>96</th>\n",
+       "      <td>0.246331</td>\n",
+       "      <td>-1.322402</td>\n",
+       "      <td>0.731497</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>113</th>\n",
-       "      <td>1.496547</td>\n",
-       "      <td>1.213509</td>\n",
-       "      <td>0.386677</td>\n",
+       "      <th>105</th>\n",
+       "      <td>-1.803766</td>\n",
+       "      <td>0.445043</td>\n",
+       "      <td>-1.009817</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>130</th>\n",
-       "      <td>-0.341575</td>\n",
-       "      <td>1.213509</td>\n",
-       "      <td>-0.044401</td>\n",
+       "      <th>111</th>\n",
+       "      <td>-1.164286</td>\n",
+       "      <td>0.697535</td>\n",
+       "      <td>-2.098138</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -1501,65 +1417,65 @@
       "text/plain": [
        "            standard_scaled_culmen_length_mm  standard_scaled_culmen_depth_mm  \\\n",
        "penguin_id                                                                      \n",
-       "3                                   0.493935                         0.382978   \n",
-       "8                                   1.050942                         0.953968   \n",
-       "17                                  1.255178                           1.1616   \n",
-       "23                                 -1.307054                         0.694427   \n",
-       "25                                  1.515114                         0.486795   \n",
-       "27                                  1.236611                         1.265417   \n",
-       "29                                  1.403713                         0.953968   \n",
-       "34                                  0.419668                         0.538703   \n",
-       "35                                 -1.455589                         0.694427   \n",
-       "39                                  0.326833                           1.1616   \n",
-       "51                                 -1.065684                         0.227254   \n",
-       "52                                 -0.248741                         0.071529   \n",
-       "60                                  0.531069                         0.382978   \n",
-       "61                                  0.401101                          0.90206   \n",
-       "64                                 -1.455589                          0.33107   \n",
-       "65                                 -0.564378                         0.642519   \n",
-       "67                                  1.273745                         1.317325   \n",
-       "83                                  2.629128                          0.33107   \n",
-       "85                                 -1.288487                         0.746335   \n",
-       "93                                 -0.508677                         0.486795   \n",
-       "104                                 0.382534                        -0.032287   \n",
-       "105                                -1.065684                         0.746335   \n",
-       "108                                 1.162343                         0.382978   \n",
-       "113                                 1.496547                         1.213509   \n",
-       "130                                -0.341575                         1.213509   \n",
+       "1                                  -0.938587                         0.748033   \n",
+       "4                                   -0.16745                         0.899528   \n",
+       "8                                   0.453222                        -1.877885   \n",
+       "11                                  -1.12667                         0.697535   \n",
+       "13                                 -1.183094                         1.404513   \n",
+       "15                                  0.867003                        -0.766919   \n",
+       "16                                 -1.784958                         1.959995   \n",
+       "23                                 -0.355532                         0.647036   \n",
+       "34                                 -0.600039                        -1.776888   \n",
+       "36                                 -0.129833                        -1.423399   \n",
+       "42                                 -1.615684                        -0.514427   \n",
+       "48                                  0.415606                        -0.716421   \n",
+       "61                                  0.396797                        -1.170907   \n",
+       "64                                  0.434414                        -1.120408   \n",
+       "65                                 -1.220711                         1.051024   \n",
+       "68                                 -1.484026                        -0.009443   \n",
+       "70                                  1.638141                         1.404513   \n",
+       "72                                  0.829387                         0.142052   \n",
+       "74                                 -0.242683                        -1.524396   \n",
+       "77                                 -1.277136                        -0.211437   \n",
+       "81                                  0.208715                        -1.221405   \n",
+       "91                                  1.261976                         0.647036   \n",
+       "96                                  0.246331                        -1.322402   \n",
+       "105                                -1.803766                         0.445043   \n",
+       "111                                -1.164286                         0.697535   \n",
        "\n",
        "            standard_scaled_flipper_length_mm  \n",
        "penguin_id                                     \n",
-       "3                                   -0.619171  \n",
-       "8                                   -0.044401  \n",
-       "17                                  -0.547325  \n",
-       "23                                  -0.547325  \n",
-       "25                                   0.027445  \n",
-       "27                                   0.027445  \n",
-       "29                                   0.027445  \n",
-       "34                                   -1.62502  \n",
-       "35                                  -1.050249  \n",
-       "39                                  -0.475479  \n",
-       "51                                  -0.978403  \n",
-       "52                                  -0.978403  \n",
-       "60                                  -0.403633  \n",
-       "61                                  -0.403633  \n",
-       "64                                  -0.403633  \n",
-       "65                                  -0.403633  \n",
-       "67                                   0.171138  \n",
-       "83                                  -1.409481  \n",
-       "85                                   -0.83471  \n",
-       "93                                   0.314831  \n",
-       "104                                 -0.762864  \n",
-       "105                                 -0.762864  \n",
-       "108                                 -0.762864  \n",
-       "113                                  0.386677  \n",
-       "130                                 -0.044401  \n",
+       "1                                   -1.445145  \n",
+       "4                                   -0.284269  \n",
+       "8                                    0.658942  \n",
+       "11                                  -0.792152  \n",
+       "13                                  -0.792152  \n",
+       "15                                   0.513833  \n",
+       "16                                  -0.211715  \n",
+       "23                                    -1.5177  \n",
+       "34                                   0.949161  \n",
+       "36                                    1.23938  \n",
+       "42                                  -0.429379  \n",
+       "48                                   1.021716  \n",
+       "61                                   1.457044  \n",
+       "64                                    1.09427  \n",
+       "65                                  -1.445145  \n",
+       "68                                  -1.009817  \n",
+       "70                                   0.296168  \n",
+       "72                                  -0.719598  \n",
+       "74                                   0.586387  \n",
+       "77                                  -0.647043  \n",
+       "81                                   0.804051  \n",
+       "91                                   0.005949  \n",
+       "96                                   0.731497  \n",
+       "105                                 -1.009817  \n",
+       "111                                 -2.098138  \n",
        "...\n",
        "\n",
        "[67 rows x 3 columns]"
       ]
      },
-     "execution_count": 23,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1581,32 +1497,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
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-       "version_minor": 0
-      },
-      "text/plain": [
-       "HTML(value='Query job a8d8afa4-d91e-487e-8709-8727a73ab453 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "693297c9ca8245f58f7e10071a6278b4",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 75c1ce67-e5d7-4f4c-947e-381fc5298236 is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:75c1ce67-e5d7-4f4c-947e-381fc5298236&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job b9afd624-4345-4160-8809-05786563ce35 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1614,13 +1514,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "09217776c2294e8b929a56e7a73fbfa8",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 41962e2e-4d14-4053-9297-3ce61699551a is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:41962e2e-4d14-4053-9297-3ce61699551a&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job c918fc7c-a956-4259-b5c5-09c2eac615cd is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1628,13 +1526,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9c1581fc9fcb49739d1d81b73506b894",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 5d3c22c9-c972-4213-8557-726c9e0aca37 is DONE. 22.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:5d3c22c9-c972-4213-8557-726c9e0aca37&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 1d855341-282f-4d10-9ba9-3ce6683b729a is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1642,13 +1538,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "d7749eb7cf554697a60c90f3718ad582",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 9cb7b33f-ea05-4cf4-9f92-bb3aa4ea8d10 is DONE. 2.1 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:9cb7b33f-ea05-4cf4-9f92-bb3aa4ea8d10&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job c257ff78-3e15-4296-82f5-ba6c2eb6a6ff is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1656,13 +1550,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e900465918224249bccc781d992aadbb",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job fe1f35d6-d82c-4aab-a284-637b72554f5b is DONE. 29.2 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:fe1f35d6-d82c-4aab-a284-637b72554f5b&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job a17eec0c-10d0-4943-95be-60fced57d5cb is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1670,13 +1562,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b0272ee35c5745a491b7c5883b3fbb1b",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 37bc90ff-59cb-4b0c-8f9d-73bcda43524a is DONE. 536 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:37bc90ff-59cb-4b0c-8f9d-73bcda43524a&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 1db53c8a-cf45-4c69-a443-6b7a49fc3a07 is DONE. 536 Bytes processed. <a target=\"_blank\" hr…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1684,13 +1574,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "00f9d4b55bb94997aaebdae298cefab3",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job e23f4724-fdd8-45a9-8c87-defd8d471035 is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:e23f4724-fdd8-45a9-8c87-defd8d471035&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job ae870ee3-e633-4556-94e6-6669fa0bfde2 is DONE. 0 Bytes processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1698,13 +1586,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9cd8e791be5844669cba10dc53f862ae",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 257378db-0569-42d7-965a-7757154c710b is DONE. 21.4 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:257378db-0569-42d7-965a-7757154c710b&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job baa7c70c-eabc-49e1-bae9-fdd4891cdb6e is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1751,226 +1637,226 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-1.344188</td>\n",
-       "      <td>0.642519</td>\n",
-       "      <td>-1.193942</td>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
+       "      <td>-0.750505</td>\n",
+       "      <td>0.84903</td>\n",
+       "      <td>-0.937262</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-0.750047</td>\n",
-       "      <td>1.005876</td>\n",
-       "      <td>-1.193942</td>\n",
-       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-0.545811</td>\n",
-       "      <td>0.90206</td>\n",
-       "      <td>-1.193942</td>\n",
-       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.622496</td>\n",
+       "      <td>-1.322402</td>\n",
+       "      <td>0.804051</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-1.214219</td>\n",
-       "      <td>-0.188011</td>\n",
-       "      <td>-0.619171</td>\n",
+       "      <th>3</th>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>-0.299107</td>\n",
+       "      <td>-0.261935</td>\n",
+       "      <td>-1.009817</td>\n",
        "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.490839</td>\n",
+       "      <td>-0.968913</td>\n",
+       "      <td>1.311935</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-0.118772</td>\n",
-       "      <td>0.694427</td>\n",
-       "      <td>-0.619171</td>\n",
        "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
-       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-0.524806</td>\n",
+       "      <td>1.959995</td>\n",
+       "      <td>-0.429379</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>0.568203</td>\n",
-       "      <td>-0.291828</td>\n",
-       "      <td>-0.619171</td>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>1.236611</td>\n",
-       "      <td>0.642519</td>\n",
-       "      <td>-0.044401</td>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.208715</td>\n",
+       "      <td>-1.726389</td>\n",
+       "      <td>1.021716</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-0.675779</td>\n",
-       "      <td>1.524957</td>\n",
-       "      <td>-0.044401</td>\n",
-       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>1.205551</td>\n",
+       "      <td>-1.019412</td>\n",
+       "      <td>1.09427</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.772962</td>\n",
+       "      <td>-0.817418</td>\n",
+       "      <td>1.457044</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-0.564378</td>\n",
-       "      <td>0.90206</td>\n",
-       "      <td>0.530369</td>\n",
        "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
-       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>11</th>\n",
+       "      <th>12</th>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>1.243168</td>\n",
+       "      <td>-1.120408</td>\n",
+       "      <td>1.602153</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-0.898582</td>\n",
-       "      <td>0.798243</td>\n",
-       "      <td>-1.122096</td>\n",
        "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
-       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-1.26992</td>\n",
-       "      <td>-0.136103</td>\n",
-       "      <td>-1.122096</td>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <th>14</th>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-1.709725</td>\n",
+       "      <td>0.344046</td>\n",
+       "      <td>-0.792152</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>13</th>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>0.58677</td>\n",
-       "      <td>0.071529</td>\n",
-       "      <td>-1.122096</td>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <th>17</th>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.509647</td>\n",
+       "      <td>-0.918415</td>\n",
+       "      <td>1.021716</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>14</th>\n",
+       "      <th>18</th>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>1.167935</td>\n",
+       "      <td>1.404513</td>\n",
+       "      <td>-0.284269</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-1.826927</td>\n",
-       "      <td>-0.032287</td>\n",
-       "      <td>-1.122096</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>15</th>\n",
+       "      <th>19</th>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-1.26992</td>\n",
-       "      <td>-0.343736</td>\n",
-       "      <td>-1.122096</td>\n",
+       "      <td>-1.295944</td>\n",
+       "      <td>0.445043</td>\n",
+       "      <td>-1.662809</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>16</th>\n",
+       "      <th>20</th>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>0.3454</td>\n",
-       "      <td>0.071529</td>\n",
-       "      <td>-0.547325</td>\n",
+       "      <td>1.299593</td>\n",
+       "      <td>0.798532</td>\n",
+       "      <td>0.151059</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>18</th>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-0.768614</td>\n",
-       "      <td>0.382978</td>\n",
-       "      <td>-0.547325</td>\n",
-       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
+       "      <th>21</th>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-0.675272</td>\n",
+       "      <td>0.344046</td>\n",
+       "      <td>-1.009817</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>19</th>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-1.121385</td>\n",
-       "      <td>0.486795</td>\n",
-       "      <td>-0.547325</td>\n",
-       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
+       "      <th>22</th>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.26514</td>\n",
+       "      <td>-1.675891</td>\n",
+       "      <td>0.658942</td>\n",
        "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>20</th>\n",
+       "      <th>24</th>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>0.512502</td>\n",
-       "      <td>0.33107</td>\n",
-       "      <td>-0.547325</td>\n",
+       "      <td>1.43125</td>\n",
+       "      <td>1.556008</td>\n",
+       "      <td>-0.501934</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>21</th>\n",
+       "      <th>25</th>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>1.385146</td>\n",
-       "      <td>1.057784</td>\n",
-       "      <td>-0.547325</td>\n",
-       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
+       "      <td>0.302756</td>\n",
+       "      <td>0.041055</td>\n",
+       "      <td>-0.574488</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>22</th>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-0.675779</td>\n",
-       "      <td>-0.032287</td>\n",
-       "      <td>-0.547325</td>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <th>26</th>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.302756</td>\n",
+       "      <td>-1.675891</td>\n",
+       "      <td>0.949161</td>\n",
        "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>24</th>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>1.069509</td>\n",
-       "      <td>0.538703</td>\n",
-       "      <td>-0.547325</td>\n",
+       "      <th>27</th>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.227523</td>\n",
+       "      <td>-1.776888</td>\n",
+       "      <td>0.658942</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
-       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>26</th>\n",
+       "      <th>28</th>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>1.318401</td>\n",
+       "      <td>-0.362932</td>\n",
+       "      <td>1.747263</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-0.43441</td>\n",
-       "      <td>0.694427</td>\n",
-       "      <td>0.027445</td>\n",
        "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
-       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>28</th>\n",
+       "      <th>29</th>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>2.202388</td>\n",
+       "      <td>1.303516</td>\n",
+       "      <td>0.441278</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>1.923586</td>\n",
-       "      <td>1.888314</td>\n",
-       "      <td>0.027445</td>\n",
-       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>30</th>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>1.292312</td>\n",
-       "      <td>0.694427</td>\n",
-       "      <td>0.027445</td>\n",
-       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
+       "      <td>-0.919779</td>\n",
+       "      <td>1.959995</td>\n",
+       "      <td>-0.356824</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>31</th>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>1.036277</td>\n",
+       "      <td>-0.615424</td>\n",
+       "      <td>1.747263</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
-       "      <td>-1.994029</td>\n",
-       "      <td>-0.551368</td>\n",
-       "      <td>-1.62502</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
+       "      <td>-0.223874</td>\n",
+       "      <td>0.19255</td>\n",
+       "      <td>-0.356824</td>\n",
        "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
@@ -1982,121 +1868,121 @@
       "text/plain": [
        "                    onehotencoded_island  standard_scaled_culmen_length_mm  \\\n",
        "penguin_id                                                                   \n",
-       "0           [{'index': 2, 'value': 1.0}]                         -1.344188   \n",
-       "1           [{'index': 2, 'value': 1.0}]                         -0.750047   \n",
-       "2           [{'index': 2, 'value': 1.0}]                         -0.545811   \n",
-       "4           [{'index': 2, 'value': 1.0}]                         -1.214219   \n",
-       "5           [{'index': 2, 'value': 1.0}]                         -0.118772   \n",
-       "6           [{'index': 2, 'value': 1.0}]                          0.568203   \n",
-       "7           [{'index': 2, 'value': 1.0}]                          1.236611   \n",
-       "9           [{'index': 2, 'value': 1.0}]                         -0.675779   \n",
-       "10          [{'index': 2, 'value': 1.0}]                         -0.564378   \n",
-       "11          [{'index': 2, 'value': 1.0}]                         -0.898582   \n",
-       "12          [{'index': 2, 'value': 1.0}]                          -1.26992   \n",
-       "13          [{'index': 2, 'value': 1.0}]                           0.58677   \n",
-       "14          [{'index': 2, 'value': 1.0}]                         -1.826927   \n",
-       "15          [{'index': 2, 'value': 1.0}]                          -1.26992   \n",
-       "16          [{'index': 2, 'value': 1.0}]                            0.3454   \n",
-       "18          [{'index': 2, 'value': 1.0}]                         -0.768614   \n",
-       "19          [{'index': 2, 'value': 1.0}]                         -1.121385   \n",
-       "20          [{'index': 2, 'value': 1.0}]                          0.512502   \n",
-       "21          [{'index': 2, 'value': 1.0}]                          1.385146   \n",
-       "22          [{'index': 2, 'value': 1.0}]                         -0.675779   \n",
-       "24          [{'index': 2, 'value': 1.0}]                          1.069509   \n",
-       "26          [{'index': 2, 'value': 1.0}]                          -0.43441   \n",
-       "28          [{'index': 2, 'value': 1.0}]                          1.923586   \n",
-       "30          [{'index': 2, 'value': 1.0}]                          1.292312   \n",
-       "31          [{'index': 2, 'value': 1.0}]                         -1.994029   \n",
+       "0           [{'index': 1, 'value': 1.0}]                         -0.750505   \n",
+       "2           [{'index': 1, 'value': 1.0}]                          0.622496   \n",
+       "3           [{'index': 2, 'value': 1.0}]                         -0.299107   \n",
+       "5           [{'index': 1, 'value': 1.0}]                          0.490839   \n",
+       "6           [{'index': 1, 'value': 1.0}]                         -0.524806   \n",
+       "7           [{'index': 1, 'value': 1.0}]                          0.208715   \n",
+       "9           [{'index': 1, 'value': 1.0}]                          1.205551   \n",
+       "10          [{'index': 1, 'value': 1.0}]                          0.772962   \n",
+       "12          [{'index': 1, 'value': 1.0}]                          1.243168   \n",
+       "14          [{'index': 1, 'value': 1.0}]                         -1.709725   \n",
+       "17          [{'index': 1, 'value': 1.0}]                          0.509647   \n",
+       "18          [{'index': 2, 'value': 1.0}]                          1.167935   \n",
+       "19          [{'index': 2, 'value': 1.0}]                         -1.295944   \n",
+       "20          [{'index': 2, 'value': 1.0}]                          1.299593   \n",
+       "21          [{'index': 1, 'value': 1.0}]                         -0.675272   \n",
+       "22          [{'index': 1, 'value': 1.0}]                           0.26514   \n",
+       "24          [{'index': 2, 'value': 1.0}]                           1.43125   \n",
+       "25          [{'index': 2, 'value': 1.0}]                          0.302756   \n",
+       "26          [{'index': 1, 'value': 1.0}]                          0.302756   \n",
+       "27          [{'index': 1, 'value': 1.0}]                          0.227523   \n",
+       "28          [{'index': 1, 'value': 1.0}]                          1.318401   \n",
+       "29          [{'index': 2, 'value': 1.0}]                          2.202388   \n",
+       "30          [{'index': 2, 'value': 1.0}]                         -0.919779   \n",
+       "31          [{'index': 1, 'value': 1.0}]                          1.036277   \n",
+       "32          [{'index': 3, 'value': 1.0}]                         -0.223874   \n",
        "\n",
        "            standard_scaled_culmen_depth_mm  \\\n",
        "penguin_id                                    \n",
-       "0                                  0.642519   \n",
-       "1                                  1.005876   \n",
-       "2                                   0.90206   \n",
-       "4                                 -0.188011   \n",
-       "5                                  0.694427   \n",
-       "6                                 -0.291828   \n",
-       "7                                  0.642519   \n",
-       "9                                  1.524957   \n",
-       "10                                  0.90206   \n",
-       "11                                 0.798243   \n",
-       "12                                -0.136103   \n",
-       "13                                 0.071529   \n",
-       "14                                -0.032287   \n",
-       "15                                -0.343736   \n",
-       "16                                 0.071529   \n",
-       "18                                 0.382978   \n",
-       "19                                 0.486795   \n",
-       "20                                  0.33107   \n",
-       "21                                 1.057784   \n",
-       "22                                -0.032287   \n",
-       "24                                 0.538703   \n",
-       "26                                 0.694427   \n",
-       "28                                 1.888314   \n",
-       "30                                 0.694427   \n",
-       "31                                -0.551368   \n",
+       "0                                   0.84903   \n",
+       "2                                 -1.322402   \n",
+       "3                                 -0.261935   \n",
+       "5                                 -0.968913   \n",
+       "6                                  1.959995   \n",
+       "7                                 -1.726389   \n",
+       "9                                 -1.019412   \n",
+       "10                                -0.817418   \n",
+       "12                                -1.120408   \n",
+       "14                                 0.344046   \n",
+       "17                                -0.918415   \n",
+       "18                                 1.404513   \n",
+       "19                                 0.445043   \n",
+       "20                                 0.798532   \n",
+       "21                                 0.344046   \n",
+       "22                                -1.675891   \n",
+       "24                                 1.556008   \n",
+       "25                                 0.041055   \n",
+       "26                                -1.675891   \n",
+       "27                                -1.776888   \n",
+       "28                                -0.362932   \n",
+       "29                                 1.303516   \n",
+       "30                                 1.959995   \n",
+       "31                                -0.615424   \n",
+       "32                                  0.19255   \n",
        "\n",
        "            standard_scaled_flipper_length_mm             onehotencoded_sex  \\\n",
        "penguin_id                                                                    \n",
-       "0                                   -1.193942  [{'index': 2, 'value': 1.0}]   \n",
-       "1                                   -1.193942  [{'index': 3, 'value': 1.0}]   \n",
-       "2                                   -1.193942  [{'index': 3, 'value': 1.0}]   \n",
-       "4                                   -0.619171  [{'index': 2, 'value': 1.0}]   \n",
-       "5                                   -0.619171  [{'index': 3, 'value': 1.0}]   \n",
-       "6                                   -0.619171  [{'index': 2, 'value': 1.0}]   \n",
-       "7                                   -0.044401  [{'index': 2, 'value': 1.0}]   \n",
-       "9                                   -0.044401  [{'index': 3, 'value': 1.0}]   \n",
-       "10                                   0.530369  [{'index': 3, 'value': 1.0}]   \n",
-       "11                                  -1.122096  [{'index': 3, 'value': 1.0}]   \n",
-       "12                                  -1.122096  [{'index': 2, 'value': 1.0}]   \n",
-       "13                                  -1.122096  [{'index': 2, 'value': 1.0}]   \n",
-       "14                                  -1.122096  [{'index': 2, 'value': 1.0}]   \n",
-       "15                                  -1.122096  [{'index': 2, 'value': 1.0}]   \n",
-       "16                                  -0.547325  [{'index': 2, 'value': 1.0}]   \n",
-       "18                                  -0.547325  [{'index': 3, 'value': 1.0}]   \n",
-       "19                                  -0.547325  [{'index': 3, 'value': 1.0}]   \n",
-       "20                                  -0.547325  [{'index': 2, 'value': 1.0}]   \n",
-       "21                                  -0.547325  [{'index': 3, 'value': 1.0}]   \n",
-       "22                                  -0.547325  [{'index': 2, 'value': 1.0}]   \n",
-       "24                                  -0.547325  [{'index': 3, 'value': 1.0}]   \n",
-       "26                                   0.027445  [{'index': 3, 'value': 1.0}]   \n",
-       "28                                   0.027445  [{'index': 3, 'value': 1.0}]   \n",
-       "30                                   0.027445  [{'index': 3, 'value': 1.0}]   \n",
-       "31                                   -1.62502  [{'index': 2, 'value': 1.0}]   \n",
+       "0                                   -0.937262  [{'index': 2, 'value': 1.0}]   \n",
+       "2                                    0.804051  [{'index': 1, 'value': 1.0}]   \n",
+       "3                                   -1.009817  [{'index': 1, 'value': 1.0}]   \n",
+       "5                                    1.311935  [{'index': 2, 'value': 1.0}]   \n",
+       "6                                   -0.429379  [{'index': 2, 'value': 1.0}]   \n",
+       "7                                    1.021716  [{'index': 1, 'value': 1.0}]   \n",
+       "9                                     1.09427  [{'index': 1, 'value': 1.0}]   \n",
+       "10                                   1.457044  [{'index': 2, 'value': 1.0}]   \n",
+       "12                                   1.602153  [{'index': 2, 'value': 1.0}]   \n",
+       "14                                  -0.792152  [{'index': 1, 'value': 1.0}]   \n",
+       "17                                   1.021716  [{'index': 2, 'value': 1.0}]   \n",
+       "18                                  -0.284269  [{'index': 2, 'value': 1.0}]   \n",
+       "19                                  -1.662809  [{'index': 2, 'value': 1.0}]   \n",
+       "20                                   0.151059  [{'index': 2, 'value': 1.0}]   \n",
+       "21                                  -1.009817  [{'index': 1, 'value': 1.0}]   \n",
+       "22                                   0.658942  [{'index': 1, 'value': 1.0}]   \n",
+       "24                                  -0.501934  [{'index': 2, 'value': 1.0}]   \n",
+       "25                                  -0.574488  [{'index': 1, 'value': 1.0}]   \n",
+       "26                                   0.949161  [{'index': 1, 'value': 1.0}]   \n",
+       "27                                   0.658942  [{'index': 1, 'value': 1.0}]   \n",
+       "28                                   1.747263  [{'index': 2, 'value': 1.0}]   \n",
+       "29                                   0.441278  [{'index': 2, 'value': 1.0}]   \n",
+       "30                                  -0.356824  [{'index': 2, 'value': 1.0}]   \n",
+       "31                                   1.747263  [{'index': 2, 'value': 1.0}]   \n",
+       "32                                  -0.356824  [{'index': 2, 'value': 1.0}]   \n",
        "\n",
        "                   onehotencoded_species  \n",
        "penguin_id                                \n",
        "0           [{'index': 1, 'value': 1.0}]  \n",
-       "1           [{'index': 1, 'value': 1.0}]  \n",
-       "2           [{'index': 1, 'value': 1.0}]  \n",
-       "4           [{'index': 1, 'value': 1.0}]  \n",
-       "5           [{'index': 1, 'value': 1.0}]  \n",
-       "6           [{'index': 2, 'value': 1.0}]  \n",
-       "7           [{'index': 2, 'value': 1.0}]  \n",
-       "9           [{'index': 1, 'value': 1.0}]  \n",
-       "10          [{'index': 1, 'value': 1.0}]  \n",
-       "11          [{'index': 1, 'value': 1.0}]  \n",
-       "12          [{'index': 1, 'value': 1.0}]  \n",
-       "13          [{'index': 2, 'value': 1.0}]  \n",
+       "2           [{'index': 3, 'value': 1.0}]  \n",
+       "3           [{'index': 2, 'value': 1.0}]  \n",
+       "5           [{'index': 3, 'value': 1.0}]  \n",
+       "6           [{'index': 1, 'value': 1.0}]  \n",
+       "7           [{'index': 3, 'value': 1.0}]  \n",
+       "9           [{'index': 3, 'value': 1.0}]  \n",
+       "10          [{'index': 3, 'value': 1.0}]  \n",
+       "12          [{'index': 3, 'value': 1.0}]  \n",
        "14          [{'index': 1, 'value': 1.0}]  \n",
-       "15          [{'index': 1, 'value': 1.0}]  \n",
-       "16          [{'index': 2, 'value': 1.0}]  \n",
-       "18          [{'index': 1, 'value': 1.0}]  \n",
+       "17          [{'index': 3, 'value': 1.0}]  \n",
+       "18          [{'index': 2, 'value': 1.0}]  \n",
        "19          [{'index': 1, 'value': 1.0}]  \n",
        "20          [{'index': 2, 'value': 1.0}]  \n",
-       "21          [{'index': 2, 'value': 1.0}]  \n",
-       "22          [{'index': 1, 'value': 1.0}]  \n",
+       "21          [{'index': 1, 'value': 1.0}]  \n",
+       "22          [{'index': 3, 'value': 1.0}]  \n",
        "24          [{'index': 2, 'value': 1.0}]  \n",
-       "26          [{'index': 1, 'value': 1.0}]  \n",
-       "28          [{'index': 2, 'value': 1.0}]  \n",
-       "30          [{'index': 2, 'value': 1.0}]  \n",
-       "31          [{'index': 1, 'value': 1.0}]  \n",
+       "25          [{'index': 2, 'value': 1.0}]  \n",
+       "26          [{'index': 3, 'value': 1.0}]  \n",
+       "27          [{'index': 3, 'value': 1.0}]  \n",
+       "28          [{'index': 3, 'value': 1.0}]  \n",
+       "29          [{'index': 2, 'value': 1.0}]  \n",
+       "30          [{'index': 1, 'value': 1.0}]  \n",
+       "31          [{'index': 3, 'value': 1.0}]  \n",
+       "32          [{'index': 1, 'value': 1.0}]  \n",
        "...\n",
        "\n",
        "[267 rows x 6 columns]"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2138,18 +2024,28 @@
   },
   {
    "cell_type": "code",
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+   "execution_count": 8,
    "metadata": {},
    "outputs": [
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-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 7d9c9f8b-6b4c-451f-ae3d-06fb7090d148 is DONE. 21.4 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:7d9c9f8b-6b4c-451f-ae3d-06fb7090d148&page=queryresults\">Open Job</a>"
+      ],
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+       "<IPython.core.display.HTML object>"
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+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Query job be87ccfa-72ab-4858-9d4a-b2f5f8b2a5e6 is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:be87ccfa-72ab-4858-9d4a-b2f5f8b2a5e6&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job ceced0cc-13a7-4b14-b42c-4d5f69e7e49a is RUNNING. <a target=\"_blank\" href=\"https://consol…"
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-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 2d651fac-11bf-42da-8c18-bd33207379ca is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:2d651fac-11bf-42da-8c18-bd33207379ca&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job a708b8df-6040-49b1-a6da-d2c0d162f247 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
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-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 58836ccc-242b-4574-bc48-4c269e74dbf1 is DONE. 5.7 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:58836ccc-242b-4574-bc48-4c269e74dbf1&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job e9b9cbb5-f6a4-4d85-ba78-1edae77dce94 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
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-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 1bf531f0-0fde-489b-ab36-6040a2a12377 is DONE. 536 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:1bf531f0-0fde-489b-ab36-6040a2a12377&page=queryresults\">Open Job</a>"
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-       "HTML(value='Query job 6c0a41a7-a732-413a-b074-ba82f175eab8 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
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-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 4245f4e6-4d5b-404f-81d7-50f0553e2456 is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:4245f4e6-4d5b-404f-81d7-50f0553e2456&page=queryresults\">Open Job</a>"
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-       "HTML(value='Query job 2d08b79d-9c36-4db7-824a-332fdd02e9fc is DONE. 0 Bytes processed. <a target=\"_blank\" href…"
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-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job ed951699-c005-450e-a8b6-0916ec234e7f is DONE. 5.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:ed951699-c005-450e-a8b6-0916ec234e7f&page=queryresults\">Open Job</a>"
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       "text/plain": [
-       "HTML(value='Query job 7fa0bf53-1022-45ee-b3ac-78fa5c155585 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
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      "metadata": {},
@@ -2247,152 +2133,397 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>predicted_body_mass_g</th>\n",
+       "      <th>onehotencoded_island</th>\n",
+       "      <th>standard_scaled_culmen_length_mm</th>\n",
+       "      <th>standard_scaled_culmen_depth_mm</th>\n",
+       "      <th>standard_scaled_flipper_length_mm</th>\n",
+       "      <th>onehotencoded_sex</th>\n",
+       "      <th>onehotencoded_species</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>penguin_id</th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>3394.118128</td>\n",
+       "      <th>1</th>\n",
+       "      <td>3781.402407</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
+       "      <td>-0.938587</td>\n",
+       "      <td>0.748033</td>\n",
+       "      <td>-1.445145</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>4048.685642</td>\n",
+       "      <th>4</th>\n",
+       "      <td>4124.107944</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-0.16745</td>\n",
+       "      <td>0.899528</td>\n",
+       "      <td>-0.284269</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>3976.454093</td>\n",
+       "      <th>8</th>\n",
+       "      <td>4670.344196</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.453222</td>\n",
+       "      <td>-1.877885</td>\n",
+       "      <td>0.658942</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>3541.582194</td>\n",
+       "      <th>11</th>\n",
+       "      <td>3529.417214</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>-1.12667</td>\n",
+       "      <td>0.697535</td>\n",
+       "      <td>-0.792152</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25</th>\n",
-       "      <td>4032.844186</td>\n",
+       "      <th>13</th>\n",
+       "      <td>4014.101714</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-1.183094</td>\n",
+       "      <td>1.404513</td>\n",
+       "      <td>-0.792152</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>4118.351772</td>\n",
+       "      <th>15</th>\n",
+       "      <td>5212.41288</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.867003</td>\n",
+       "      <td>-0.766919</td>\n",
+       "      <td>0.513833</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>4087.767826</td>\n",
+       "      <th>16</th>\n",
+       "      <td>4163.595615</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
+       "      <td>-1.784958</td>\n",
+       "      <td>1.959995</td>\n",
+       "      <td>-0.211715</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>34</th>\n",
-       "      <td>3183.755249</td>\n",
+       "      <th>23</th>\n",
+       "      <td>3392.453069</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>-0.355532</td>\n",
+       "      <td>0.647036</td>\n",
+       "      <td>-1.5177</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>35</th>\n",
-       "      <td>3418.802274</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>39</th>\n",
-       "      <td>3519.186468</td>\n",
+       "      <th>34</th>\n",
+       "      <td>4698.305397</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-0.600039</td>\n",
+       "      <td>-1.776888</td>\n",
+       "      <td>0.949161</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>51</th>\n",
-       "      <td>3398.135365</td>\n",
+       "      <th>36</th>\n",
+       "      <td>4828.226949</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-0.129833</td>\n",
+       "      <td>-1.423399</td>\n",
+       "      <td>1.23938</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>52</th>\n",
-       "      <td>3223.615957</td>\n",
+       "      <th>42</th>\n",
+       "      <td>3430.58866</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-1.615684</td>\n",
+       "      <td>-0.514427</td>\n",
+       "      <td>-0.429379</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>60</th>\n",
-       "      <td>3445.014718</td>\n",
+       "      <th>48</th>\n",
+       "      <td>5314.260221</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.415606</td>\n",
+       "      <td>-0.716421</td>\n",
+       "      <td>1.021716</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>61</th>\n",
-       "      <td>3505.638864</td>\n",
+       "      <td>5363.205372</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.396797</td>\n",
+       "      <td>-1.170907</td>\n",
+       "      <td>1.457044</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>64</th>\n",
-       "      <td>3515.905786</td>\n",
+       "      <td>4855.908314</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.434414</td>\n",
+       "      <td>-1.120408</td>\n",
+       "      <td>1.09427</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>65</th>\n",
-       "      <td>4028.363185</td>\n",
+       "      <td>3413.100524</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>-1.220711</td>\n",
+       "      <td>1.051024</td>\n",
+       "      <td>-1.445145</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>67</th>\n",
-       "      <td>4159.993943</td>\n",
+       "      <th>68</th>\n",
+       "      <td>3340.219002</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
+       "      <td>-1.484026</td>\n",
+       "      <td>-0.009443</td>\n",
+       "      <td>-1.009817</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>83</th>\n",
-       "      <td>3348.16883</td>\n",
+       "      <th>70</th>\n",
+       "      <td>4228.73157</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>1.638141</td>\n",
+       "      <td>1.404513</td>\n",
+       "      <td>0.296168</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>85</th>\n",
-       "      <td>3485.050273</td>\n",
+       "      <th>72</th>\n",
+       "      <td>3811.538478</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>0.829387</td>\n",
+       "      <td>0.142052</td>\n",
+       "      <td>-0.719598</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>93</th>\n",
-       "      <td>4172.874548</td>\n",
+       "      <th>74</th>\n",
+       "      <td>4659.770763</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-0.242683</td>\n",
+       "      <td>-1.524396</td>\n",
+       "      <td>0.586387</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>104</th>\n",
-       "      <td>3299.302424</td>\n",
+       "      <th>77</th>\n",
+       "      <td>3453.388804</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>-1.277136</td>\n",
+       "      <td>-0.211437</td>\n",
+       "      <td>-0.647043</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>105</th>\n",
-       "      <td>3515.687917</td>\n",
+       "      <th>81</th>\n",
+       "      <td>4766.245033</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.208715</td>\n",
+       "      <td>-1.221405</td>\n",
+       "      <td>0.804051</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>91</th>\n",
+       "      <td>4057.807281</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>1.261976</td>\n",
+       "      <td>0.647036</td>\n",
+       "      <td>0.005949</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>108</th>\n",
-       "      <td>3405.224618</td>\n",
+       "      <th>96</th>\n",
+       "      <td>4739.827445</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.246331</td>\n",
+       "      <td>-1.322402</td>\n",
+       "      <td>0.731497</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>113</th>\n",
-       "      <td>4209.140425</td>\n",
+       "      <th>105</th>\n",
+       "      <td>3394.891976</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-1.803766</td>\n",
+       "      <td>0.445043</td>\n",
+       "      <td>-1.009817</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>130</th>\n",
-       "      <td>4197.905737</td>\n",
+       "      <th>111</th>\n",
+       "      <td>3201.493683</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-1.164286</td>\n",
+       "      <td>0.697535</td>\n",
+       "      <td>-2.098138</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>25 rows × 1 columns</p>\n",
-       "</div>[67 rows x 1 columns in total]"
-      ],
-      "text/plain": [
-       "            predicted_body_mass_g\n",
-       "penguin_id                       \n",
-       "3                     3394.118128\n",
-       "8                     4048.685642\n",
-       "17                    3976.454093\n",
-       "23                    3541.582194\n",
-       "25                    4032.844186\n",
-       "27                    4118.351772\n",
-       "29                    4087.767826\n",
-       "34                    3183.755249\n",
-       "35                    3418.802274\n",
-       "39                    3519.186468\n",
-       "51                    3398.135365\n",
-       "52                    3223.615957\n",
-       "60                    3445.014718\n",
-       "61                    3505.638864\n",
-       "64                    3515.905786\n",
-       "65                    4028.363185\n",
-       "67                    4159.993943\n",
-       "83                     3348.16883\n",
-       "85                    3485.050273\n",
-       "93                    4172.874548\n",
-       "104                   3299.302424\n",
-       "105                   3515.687917\n",
-       "108                   3405.224618\n",
-       "113                   4209.140425\n",
-       "130                   4197.905737\n",
-       "...\n",
+       "<p>25 rows × 7 columns</p>\n",
+       "</div>[67 rows x 7 columns in total]"
+      ],
+      "text/plain": [
+       "            predicted_body_mass_g          onehotencoded_island  \\\n",
+       "penguin_id                                                        \n",
+       "1                     3781.402407  [{'index': 3, 'value': 1.0}]   \n",
+       "4                     4124.107944  [{'index': 1, 'value': 1.0}]   \n",
+       "8                     4670.344196  [{'index': 1, 'value': 1.0}]   \n",
+       "11                    3529.417214  [{'index': 2, 'value': 1.0}]   \n",
+       "13                    4014.101714  [{'index': 1, 'value': 1.0}]   \n",
+       "15                     5212.41288  [{'index': 1, 'value': 1.0}]   \n",
+       "16                    4163.595615  [{'index': 3, 'value': 1.0}]   \n",
+       "23                    3392.453069  [{'index': 2, 'value': 1.0}]   \n",
+       "34                    4698.305397  [{'index': 1, 'value': 1.0}]   \n",
+       "36                    4828.226949  [{'index': 1, 'value': 1.0}]   \n",
+       "42                     3430.58866  [{'index': 1, 'value': 1.0}]   \n",
+       "48                    5314.260221  [{'index': 1, 'value': 1.0}]   \n",
+       "61                    5363.205372  [{'index': 1, 'value': 1.0}]   \n",
+       "64                    4855.908314  [{'index': 1, 'value': 1.0}]   \n",
+       "65                    3413.100524  [{'index': 2, 'value': 1.0}]   \n",
+       "68                    3340.219002  [{'index': 3, 'value': 1.0}]   \n",
+       "70                     4228.73157  [{'index': 2, 'value': 1.0}]   \n",
+       "72                    3811.538478  [{'index': 2, 'value': 1.0}]   \n",
+       "74                    4659.770763  [{'index': 1, 'value': 1.0}]   \n",
+       "77                    3453.388804  [{'index': 2, 'value': 1.0}]   \n",
+       "81                    4766.245033  [{'index': 1, 'value': 1.0}]   \n",
+       "91                    4057.807281  [{'index': 2, 'value': 1.0}]   \n",
+       "96                    4739.827445  [{'index': 1, 'value': 1.0}]   \n",
+       "105                   3394.891976  [{'index': 1, 'value': 1.0}]   \n",
+       "111                   3201.493683  [{'index': 1, 'value': 1.0}]   \n",
        "\n",
-       "[67 rows x 1 columns]"
+       "            standard_scaled_culmen_length_mm  standard_scaled_culmen_depth_mm  \\\n",
+       "penguin_id                                                                      \n",
+       "1                                  -0.938587                         0.748033   \n",
+       "4                                   -0.16745                         0.899528   \n",
+       "8                                   0.453222                        -1.877885   \n",
+       "11                                  -1.12667                         0.697535   \n",
+       "13                                 -1.183094                         1.404513   \n",
+       "15                                  0.867003                        -0.766919   \n",
+       "16                                 -1.784958                         1.959995   \n",
+       "23                                 -0.355532                         0.647036   \n",
+       "34                                 -0.600039                        -1.776888   \n",
+       "36                                 -0.129833                        -1.423399   \n",
+       "42                                 -1.615684                        -0.514427   \n",
+       "48                                  0.415606                        -0.716421   \n",
+       "61                                  0.396797                        -1.170907   \n",
+       "64                                  0.434414                        -1.120408   \n",
+       "65                                 -1.220711                         1.051024   \n",
+       "68                                 -1.484026                        -0.009443   \n",
+       "70                                  1.638141                         1.404513   \n",
+       "72                                  0.829387                         0.142052   \n",
+       "74                                 -0.242683                        -1.524396   \n",
+       "77                                 -1.277136                        -0.211437   \n",
+       "81                                  0.208715                        -1.221405   \n",
+       "91                                  1.261976                         0.647036   \n",
+       "96                                  0.246331                        -1.322402   \n",
+       "105                                -1.803766                         0.445043   \n",
+       "111                                -1.164286                         0.697535   \n",
+       "\n",
+       "            standard_scaled_flipper_length_mm             onehotencoded_sex  \\\n",
+       "penguin_id                                                                    \n",
+       "1                                   -1.445145  [{'index': 2, 'value': 1.0}]   \n",
+       "4                                   -0.284269  [{'index': 2, 'value': 1.0}]   \n",
+       "8                                    0.658942  [{'index': 1, 'value': 1.0}]   \n",
+       "11                                  -0.792152  [{'index': 1, 'value': 1.0}]   \n",
+       "13                                  -0.792152  [{'index': 2, 'value': 1.0}]   \n",
+       "15                                   0.513833  [{'index': 2, 'value': 1.0}]   \n",
+       "16                                  -0.211715  [{'index': 2, 'value': 1.0}]   \n",
+       "23                                    -1.5177  [{'index': 1, 'value': 1.0}]   \n",
+       "34                                   0.949161  [{'index': 1, 'value': 1.0}]   \n",
+       "36                                    1.23938  [{'index': 1, 'value': 1.0}]   \n",
+       "42                                  -0.429379  [{'index': 1, 'value': 1.0}]   \n",
+       "48                                   1.021716  [{'index': 2, 'value': 1.0}]   \n",
+       "61                                   1.457044  [{'index': 2, 'value': 1.0}]   \n",
+       "64                                    1.09427  [{'index': 1, 'value': 1.0}]   \n",
+       "65                                  -1.445145  [{'index': 1, 'value': 1.0}]   \n",
+       "68                                  -1.009817  [{'index': 1, 'value': 1.0}]   \n",
+       "70                                   0.296168  [{'index': 2, 'value': 1.0}]   \n",
+       "72                                  -0.719598  [{'index': 2, 'value': 1.0}]   \n",
+       "74                                   0.586387  [{'index': 1, 'value': 1.0}]   \n",
+       "77                                  -0.647043  [{'index': 1, 'value': 1.0}]   \n",
+       "81                                   0.804051  [{'index': 1, 'value': 1.0}]   \n",
+       "91                                   0.005949  [{'index': 2, 'value': 1.0}]   \n",
+       "96                                   0.731497  [{'index': 1, 'value': 1.0}]   \n",
+       "105                                 -1.009817  [{'index': 1, 'value': 1.0}]   \n",
+       "111                                 -2.098138  [{'index': 1, 'value': 1.0}]   \n",
+       "\n",
+       "                   onehotencoded_species  \n",
+       "penguin_id                                \n",
+       "1           [{'index': 1, 'value': 1.0}]  \n",
+       "4           [{'index': 1, 'value': 1.0}]  \n",
+       "8           [{'index': 3, 'value': 1.0}]  \n",
+       "11          [{'index': 1, 'value': 1.0}]  \n",
+       "13          [{'index': 1, 'value': 1.0}]  \n",
+       "15          [{'index': 3, 'value': 1.0}]  \n",
+       "16          [{'index': 1, 'value': 1.0}]  \n",
+       "23          [{'index': 1, 'value': 1.0}]  \n",
+       "34          [{'index': 3, 'value': 1.0}]  \n",
+       "36          [{'index': 3, 'value': 1.0}]  \n",
+       "42          [{'index': 1, 'value': 1.0}]  \n",
+       "48          [{'index': 3, 'value': 1.0}]  \n",
+       "61          [{'index': 3, 'value': 1.0}]  \n",
+       "64          [{'index': 3, 'value': 1.0}]  \n",
+       "65          [{'index': 1, 'value': 1.0}]  \n",
+       "68          [{'index': 1, 'value': 1.0}]  \n",
+       "70          [{'index': 2, 'value': 1.0}]  \n",
+       "72          [{'index': 2, 'value': 1.0}]  \n",
+       "74          [{'index': 3, 'value': 1.0}]  \n",
+       "77          [{'index': 1, 'value': 1.0}]  \n",
+       "81          [{'index': 3, 'value': 1.0}]  \n",
+       "91          [{'index': 2, 'value': 1.0}]  \n",
+       "96          [{'index': 3, 'value': 1.0}]  \n",
+       "105         [{'index': 1, 'value': 1.0}]  \n",
+       "111         [{'index': 1, 'value': 1.0}]  \n",
+       "\n",
+       "[67 rows x 7 columns]"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2423,18 +2554,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "d7a16e04253a42b7a5ce247d8f63b656",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 027042f1-9a18-43d8-a378-ab9410e395b1 is DONE. 23.5 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:027042f1-9a18-43d8-a378-ab9410e395b1&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 6f19614c-82c0-4f8b-b74b-9d91a894efdd is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -2442,13 +2571,11 @@
     },
     {
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-       "model_id": "4a99ac15431e433595de1040872a4558",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 6c8484a0-a504-4e50-93d6-3d247c9ff558 is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:6c8484a0-a504-4e50-93d6-3d247c9ff558&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 51899e2d-f6ef-4e62-98b6-c11550f74f4b is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -2456,13 +2583,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "90909b620e084f59b0f9da266257593f",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job e81ca2de-df2e-41ec-af86-14f8dcec1b44 is DONE. 6.2 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:e81ca2de-df2e-41ec-af86-14f8dcec1b44&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 44d3fddc-74bc-4de0-a458-2c73b38f74fb is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -2470,13 +2595,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2a9c2c05041a4fb691809bab5310bb05",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 3e6d413c-f8c4-4390-95eb-3a1f5bc59aed is DONE. 536 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:3e6d413c-f8c4-4390-95eb-3a1f5bc59aed&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 33584475-f02b-4c98-9a51-e29996f4f950 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -2484,13 +2607,11 @@
     },
     {
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-       "model_id": "6b0677c228d54b409c66e5dfa98d7e00",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job e448220d-0c50-45b7-bcbe-d1159b3d18ce is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:e448220d-0c50-45b7-bcbe-d1159b3d18ce&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job df25ba49-280e-424d-a357-dde71a9b35dd is DONE. 0 Bytes processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -2498,13 +2619,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "379ae6497fb34f969d21b2cd664e8bfa",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job e167a234-828d-4f05-8654-63cf97e50ba3 is DONE. 10.2 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:e167a234-828d-4f05-8654-63cf97e50ba3&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 6f92a04e-af7e-41d6-9303-6366c1751294 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -2532,152 +2651,452 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>CENTROID_ID</th>\n",
+       "      <th>NEAREST_CENTROIDS_DISTANCE</th>\n",
+       "      <th>onehotencoded_island</th>\n",
+       "      <th>standard_scaled_culmen_length_mm</th>\n",
+       "      <th>standard_scaled_culmen_depth_mm</th>\n",
+       "      <th>standard_scaled_flipper_length_mm</th>\n",
+       "      <th>onehotencoded_sex</th>\n",
+       "      <th>onehotencoded_species</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>penguin_id</th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>3</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
+       "      <th>1</th>\n",
        "      <td>3</td>\n",
+       "      <td>[{'CENTROID_ID': 3, 'DISTANCE': 1.236380597035...</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
+       "      <td>-0.938587</td>\n",
+       "      <td>0.748033</td>\n",
+       "      <td>-1.445145</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>17</th>\n",
+       "      <th>4</th>\n",
        "      <td>3</td>\n",
+       "      <td>[{'CENTROID_ID': 3, 'DISTANCE': 1.039497631856...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-0.16745</td>\n",
+       "      <td>0.899528</td>\n",
+       "      <td>-0.284269</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>23</th>\n",
+       "      <th>8</th>\n",
        "      <td>1</td>\n",
+       "      <td>[{'CENTROID_ID': 1, 'DISTANCE': 1.171040485975...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.453222</td>\n",
+       "      <td>-1.877885</td>\n",
+       "      <td>0.658942</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25</th>\n",
-       "      <td>3</td>\n",
+       "      <th>11</th>\n",
+       "      <td>2</td>\n",
+       "      <td>[{'CENTROID_ID': 2, 'DISTANCE': 0.969102754012...</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>-1.12667</td>\n",
+       "      <td>0.697535</td>\n",
+       "      <td>-0.792152</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>27</th>\n",
+       "      <th>13</th>\n",
        "      <td>3</td>\n",
+       "      <td>[{'CENTROID_ID': 3, 'DISTANCE': 1.113138945949...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-1.183094</td>\n",
+       "      <td>1.404513</td>\n",
+       "      <td>-0.792152</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>3</td>\n",
+       "      <th>15</th>\n",
+       "      <td>1</td>\n",
+       "      <td>[{'CENTROID_ID': 1, 'DISTANCE': 1.070996026772...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.867003</td>\n",
+       "      <td>-0.766919</td>\n",
+       "      <td>0.513833</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>34</th>\n",
+       "      <th>16</th>\n",
        "      <td>3</td>\n",
+       "      <td>[{'CENTROID_ID': 3, 'DISTANCE': 1.780136190720...</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
+       "      <td>-1.784958</td>\n",
+       "      <td>1.959995</td>\n",
+       "      <td>-0.211715</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>35</th>\n",
-       "      <td>1</td>\n",
+       "      <th>23</th>\n",
+       "      <td>2</td>\n",
+       "      <td>[{'CENTROID_ID': 2, 'DISTANCE': 1.382540667483...</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>-0.355532</td>\n",
+       "      <td>0.647036</td>\n",
+       "      <td>-1.5177</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>39</th>\n",
-       "      <td>3</td>\n",
+       "      <th>34</th>\n",
+       "      <td>1</td>\n",
+       "      <td>[{'CENTROID_ID': 1, 'DISTANCE': 1.598627908302...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-0.600039</td>\n",
+       "      <td>-1.776888</td>\n",
+       "      <td>0.949161</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>51</th>\n",
+       "      <th>36</th>\n",
        "      <td>1</td>\n",
+       "      <td>[{'CENTROID_ID': 1, 'DISTANCE': 1.095162305190...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-0.129833</td>\n",
+       "      <td>-1.423399</td>\n",
+       "      <td>1.23938</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>52</th>\n",
-       "      <td>3</td>\n",
+       "      <th>42</th>\n",
+       "      <td>2</td>\n",
+       "      <td>[{'CENTROID_ID': 2, 'DISTANCE': 1.275841743930...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-1.615684</td>\n",
+       "      <td>-0.514427</td>\n",
+       "      <td>-0.429379</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>60</th>\n",
-       "      <td>3</td>\n",
+       "      <th>48</th>\n",
+       "      <td>1</td>\n",
+       "      <td>[{'CENTROID_ID': 1, 'DISTANCE': 0.882209023196...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.415606</td>\n",
+       "      <td>-0.716421</td>\n",
+       "      <td>1.021716</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>61</th>\n",
-       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>[{'CENTROID_ID': 1, 'DISTANCE': 0.816202832282...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.396797</td>\n",
+       "      <td>-1.170907</td>\n",
+       "      <td>1.457044</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>64</th>\n",
        "      <td>1</td>\n",
+       "      <td>[{'CENTROID_ID': 1, 'DISTANCE': 0.735435721625...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.434414</td>\n",
+       "      <td>-1.120408</td>\n",
+       "      <td>1.09427</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>65</th>\n",
-       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>[{'CENTROID_ID': 2, 'DISTANCE': 1.292559869148...</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>-1.220711</td>\n",
+       "      <td>1.051024</td>\n",
+       "      <td>-1.445145</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>67</th>\n",
-       "      <td>3</td>\n",
+       "      <th>68</th>\n",
+       "      <td>2</td>\n",
+       "      <td>[{'CENTROID_ID': 2, 'DISTANCE': 0.876430138449...</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
+       "      <td>-1.484026</td>\n",
+       "      <td>-0.009443</td>\n",
+       "      <td>-1.009817</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>83</th>\n",
-       "      <td>3</td>\n",
+       "      <th>70</th>\n",
+       "      <td>4</td>\n",
+       "      <td>[{'CENTROID_ID': 4, 'DISTANCE': 1.314229913955...</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>1.638141</td>\n",
+       "      <td>1.404513</td>\n",
+       "      <td>0.296168</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>85</th>\n",
-       "      <td>1</td>\n",
+       "      <th>72</th>\n",
+       "      <td>4</td>\n",
+       "      <td>[{'CENTROID_ID': 4, 'DISTANCE': 0.938569518009...</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>0.829387</td>\n",
+       "      <td>0.142052</td>\n",
+       "      <td>-0.719598</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>93</th>\n",
+       "      <th>74</th>\n",
        "      <td>1</td>\n",
+       "      <td>[{'CENTROID_ID': 1, 'DISTANCE': 1.350320088546...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-0.242683</td>\n",
+       "      <td>-1.524396</td>\n",
+       "      <td>0.586387</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>104</th>\n",
-       "      <td>3</td>\n",
+       "      <th>77</th>\n",
+       "      <td>2</td>\n",
+       "      <td>[{'CENTROID_ID': 2, 'DISTANCE': 0.904806634663...</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>-1.277136</td>\n",
+       "      <td>-0.211437</td>\n",
+       "      <td>-0.647043</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>105</th>\n",
+       "      <th>81</th>\n",
        "      <td>1</td>\n",
+       "      <td>[{'CENTROID_ID': 1, 'DISTANCE': 0.919082578073...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.208715</td>\n",
+       "      <td>-1.221405</td>\n",
+       "      <td>0.804051</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>108</th>\n",
-       "      <td>3</td>\n",
+       "      <th>91</th>\n",
+       "      <td>4</td>\n",
+       "      <td>[{'CENTROID_ID': 4, 'DISTANCE': 0.760360038086...</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>1.261976</td>\n",
+       "      <td>0.647036</td>\n",
+       "      <td>0.005949</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 2, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>113</th>\n",
-       "      <td>3</td>\n",
+       "      <th>96</th>\n",
+       "      <td>1</td>\n",
+       "      <td>[{'CENTROID_ID': 1, 'DISTANCE': 0.950188657227...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>0.246331</td>\n",
+       "      <td>-1.322402</td>\n",
+       "      <td>0.731497</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 3, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>130</th>\n",
-       "      <td>1</td>\n",
+       "      <th>105</th>\n",
+       "      <td>2</td>\n",
+       "      <td>[{'CENTROID_ID': 2, 'DISTANCE': 1.101316467029...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-1.803766</td>\n",
+       "      <td>0.445043</td>\n",
+       "      <td>-1.009817</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>111</th>\n",
+       "      <td>2</td>\n",
+       "      <td>[{'CENTROID_ID': 2, 'DISTANCE': 1.549061068385...</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>-1.164286</td>\n",
+       "      <td>0.697535</td>\n",
+       "      <td>-2.098138</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
+       "      <td>[{'index': 1, 'value': 1.0}]</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>25 rows × 1 columns</p>\n",
-       "</div>[67 rows x 1 columns in total]"
+       "<p>25 rows × 8 columns</p>\n",
+       "</div>[67 rows x 8 columns in total]"
       ],
       "text/plain": [
-       "            CENTROID_ID\n",
-       "penguin_id             \n",
-       "3                     3\n",
-       "8                     3\n",
-       "17                    3\n",
-       "23                    1\n",
-       "25                    3\n",
-       "27                    3\n",
-       "29                    3\n",
-       "34                    3\n",
-       "35                    1\n",
-       "39                    3\n",
-       "51                    1\n",
-       "52                    3\n",
-       "60                    3\n",
-       "61                    3\n",
-       "64                    1\n",
-       "65                    1\n",
-       "67                    3\n",
-       "83                    3\n",
-       "85                    1\n",
-       "93                    1\n",
-       "104                   3\n",
-       "105                   1\n",
-       "108                   3\n",
-       "113                   3\n",
-       "130                   1\n",
-       "...\n",
+       "            CENTROID_ID                         NEAREST_CENTROIDS_DISTANCE  \\\n",
+       "penguin_id                                                                   \n",
+       "1                     3  [{'CENTROID_ID': 3, 'DISTANCE': 1.236380597035...   \n",
+       "4                     3  [{'CENTROID_ID': 3, 'DISTANCE': 1.039497631856...   \n",
+       "8                     1  [{'CENTROID_ID': 1, 'DISTANCE': 1.171040485975...   \n",
+       "11                    2  [{'CENTROID_ID': 2, 'DISTANCE': 0.969102754012...   \n",
+       "13                    3  [{'CENTROID_ID': 3, 'DISTANCE': 1.113138945949...   \n",
+       "15                    1  [{'CENTROID_ID': 1, 'DISTANCE': 1.070996026772...   \n",
+       "16                    3  [{'CENTROID_ID': 3, 'DISTANCE': 1.780136190720...   \n",
+       "23                    2  [{'CENTROID_ID': 2, 'DISTANCE': 1.382540667483...   \n",
+       "34                    1  [{'CENTROID_ID': 1, 'DISTANCE': 1.598627908302...   \n",
+       "36                    1  [{'CENTROID_ID': 1, 'DISTANCE': 1.095162305190...   \n",
+       "42                    2  [{'CENTROID_ID': 2, 'DISTANCE': 1.275841743930...   \n",
+       "48                    1  [{'CENTROID_ID': 1, 'DISTANCE': 0.882209023196...   \n",
+       "61                    1  [{'CENTROID_ID': 1, 'DISTANCE': 0.816202832282...   \n",
+       "64                    1  [{'CENTROID_ID': 1, 'DISTANCE': 0.735435721625...   \n",
+       "65                    2  [{'CENTROID_ID': 2, 'DISTANCE': 1.292559869148...   \n",
+       "68                    2  [{'CENTROID_ID': 2, 'DISTANCE': 0.876430138449...   \n",
+       "70                    4  [{'CENTROID_ID': 4, 'DISTANCE': 1.314229913955...   \n",
+       "72                    4  [{'CENTROID_ID': 4, 'DISTANCE': 0.938569518009...   \n",
+       "74                    1  [{'CENTROID_ID': 1, 'DISTANCE': 1.350320088546...   \n",
+       "77                    2  [{'CENTROID_ID': 2, 'DISTANCE': 0.904806634663...   \n",
+       "81                    1  [{'CENTROID_ID': 1, 'DISTANCE': 0.919082578073...   \n",
+       "91                    4  [{'CENTROID_ID': 4, 'DISTANCE': 0.760360038086...   \n",
+       "96                    1  [{'CENTROID_ID': 1, 'DISTANCE': 0.950188657227...   \n",
+       "105                   2  [{'CENTROID_ID': 2, 'DISTANCE': 1.101316467029...   \n",
+       "111                   2  [{'CENTROID_ID': 2, 'DISTANCE': 1.549061068385...   \n",
        "\n",
-       "[67 rows x 1 columns]"
+       "                    onehotencoded_island  standard_scaled_culmen_length_mm  \\\n",
+       "penguin_id                                                                   \n",
+       "1           [{'index': 3, 'value': 1.0}]                         -0.938587   \n",
+       "4           [{'index': 1, 'value': 1.0}]                          -0.16745   \n",
+       "8           [{'index': 1, 'value': 1.0}]                          0.453222   \n",
+       "11          [{'index': 2, 'value': 1.0}]                          -1.12667   \n",
+       "13          [{'index': 1, 'value': 1.0}]                         -1.183094   \n",
+       "15          [{'index': 1, 'value': 1.0}]                          0.867003   \n",
+       "16          [{'index': 3, 'value': 1.0}]                         -1.784958   \n",
+       "23          [{'index': 2, 'value': 1.0}]                         -0.355532   \n",
+       "34          [{'index': 1, 'value': 1.0}]                         -0.600039   \n",
+       "36          [{'index': 1, 'value': 1.0}]                         -0.129833   \n",
+       "42          [{'index': 1, 'value': 1.0}]                         -1.615684   \n",
+       "48          [{'index': 1, 'value': 1.0}]                          0.415606   \n",
+       "61          [{'index': 1, 'value': 1.0}]                          0.396797   \n",
+       "64          [{'index': 1, 'value': 1.0}]                          0.434414   \n",
+       "65          [{'index': 2, 'value': 1.0}]                         -1.220711   \n",
+       "68          [{'index': 3, 'value': 1.0}]                         -1.484026   \n",
+       "70          [{'index': 2, 'value': 1.0}]                          1.638141   \n",
+       "72          [{'index': 2, 'value': 1.0}]                          0.829387   \n",
+       "74          [{'index': 1, 'value': 1.0}]                         -0.242683   \n",
+       "77          [{'index': 2, 'value': 1.0}]                         -1.277136   \n",
+       "81          [{'index': 1, 'value': 1.0}]                          0.208715   \n",
+       "91          [{'index': 2, 'value': 1.0}]                          1.261976   \n",
+       "96          [{'index': 1, 'value': 1.0}]                          0.246331   \n",
+       "105         [{'index': 1, 'value': 1.0}]                         -1.803766   \n",
+       "111         [{'index': 1, 'value': 1.0}]                         -1.164286   \n",
+       "\n",
+       "            standard_scaled_culmen_depth_mm  \\\n",
+       "penguin_id                                    \n",
+       "1                                  0.748033   \n",
+       "4                                  0.899528   \n",
+       "8                                 -1.877885   \n",
+       "11                                 0.697535   \n",
+       "13                                 1.404513   \n",
+       "15                                -0.766919   \n",
+       "16                                 1.959995   \n",
+       "23                                 0.647036   \n",
+       "34                                -1.776888   \n",
+       "36                                -1.423399   \n",
+       "42                                -0.514427   \n",
+       "48                                -0.716421   \n",
+       "61                                -1.170907   \n",
+       "64                                -1.120408   \n",
+       "65                                 1.051024   \n",
+       "68                                -0.009443   \n",
+       "70                                 1.404513   \n",
+       "72                                 0.142052   \n",
+       "74                                -1.524396   \n",
+       "77                                -0.211437   \n",
+       "81                                -1.221405   \n",
+       "91                                 0.647036   \n",
+       "96                                -1.322402   \n",
+       "105                                0.445043   \n",
+       "111                                0.697535   \n",
+       "\n",
+       "            standard_scaled_flipper_length_mm             onehotencoded_sex  \\\n",
+       "penguin_id                                                                    \n",
+       "1                                   -1.445145  [{'index': 2, 'value': 1.0}]   \n",
+       "4                                   -0.284269  [{'index': 2, 'value': 1.0}]   \n",
+       "8                                    0.658942  [{'index': 1, 'value': 1.0}]   \n",
+       "11                                  -0.792152  [{'index': 1, 'value': 1.0}]   \n",
+       "13                                  -0.792152  [{'index': 2, 'value': 1.0}]   \n",
+       "15                                   0.513833  [{'index': 2, 'value': 1.0}]   \n",
+       "16                                  -0.211715  [{'index': 2, 'value': 1.0}]   \n",
+       "23                                    -1.5177  [{'index': 1, 'value': 1.0}]   \n",
+       "34                                   0.949161  [{'index': 1, 'value': 1.0}]   \n",
+       "36                                    1.23938  [{'index': 1, 'value': 1.0}]   \n",
+       "42                                  -0.429379  [{'index': 1, 'value': 1.0}]   \n",
+       "48                                   1.021716  [{'index': 2, 'value': 1.0}]   \n",
+       "61                                   1.457044  [{'index': 2, 'value': 1.0}]   \n",
+       "64                                    1.09427  [{'index': 1, 'value': 1.0}]   \n",
+       "65                                  -1.445145  [{'index': 1, 'value': 1.0}]   \n",
+       "68                                  -1.009817  [{'index': 1, 'value': 1.0}]   \n",
+       "70                                   0.296168  [{'index': 2, 'value': 1.0}]   \n",
+       "72                                  -0.719598  [{'index': 2, 'value': 1.0}]   \n",
+       "74                                   0.586387  [{'index': 1, 'value': 1.0}]   \n",
+       "77                                  -0.647043  [{'index': 1, 'value': 1.0}]   \n",
+       "81                                   0.804051  [{'index': 1, 'value': 1.0}]   \n",
+       "91                                   0.005949  [{'index': 2, 'value': 1.0}]   \n",
+       "96                                   0.731497  [{'index': 1, 'value': 1.0}]   \n",
+       "105                                 -1.009817  [{'index': 1, 'value': 1.0}]   \n",
+       "111                                 -2.098138  [{'index': 1, 'value': 1.0}]   \n",
+       "\n",
+       "                   onehotencoded_species  \n",
+       "penguin_id                                \n",
+       "1           [{'index': 1, 'value': 1.0}]  \n",
+       "4           [{'index': 1, 'value': 1.0}]  \n",
+       "8           [{'index': 3, 'value': 1.0}]  \n",
+       "11          [{'index': 1, 'value': 1.0}]  \n",
+       "13          [{'index': 1, 'value': 1.0}]  \n",
+       "15          [{'index': 3, 'value': 1.0}]  \n",
+       "16          [{'index': 1, 'value': 1.0}]  \n",
+       "23          [{'index': 1, 'value': 1.0}]  \n",
+       "34          [{'index': 3, 'value': 1.0}]  \n",
+       "36          [{'index': 3, 'value': 1.0}]  \n",
+       "42          [{'index': 1, 'value': 1.0}]  \n",
+       "48          [{'index': 3, 'value': 1.0}]  \n",
+       "61          [{'index': 3, 'value': 1.0}]  \n",
+       "64          [{'index': 3, 'value': 1.0}]  \n",
+       "65          [{'index': 1, 'value': 1.0}]  \n",
+       "68          [{'index': 1, 'value': 1.0}]  \n",
+       "70          [{'index': 2, 'value': 1.0}]  \n",
+       "72          [{'index': 2, 'value': 1.0}]  \n",
+       "74          [{'index': 3, 'value': 1.0}]  \n",
+       "77          [{'index': 1, 'value': 1.0}]  \n",
+       "81          [{'index': 3, 'value': 1.0}]  \n",
+       "91          [{'index': 2, 'value': 1.0}]  \n",
+       "96          [{'index': 3, 'value': 1.0}]  \n",
+       "105         [{'index': 1, 'value': 1.0}]  \n",
+       "111         [{'index': 1, 'value': 1.0}]  \n",
+       "\n",
+       "[67 rows x 8 columns]"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2704,7 +3123,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -2721,7 +3140,7 @@
        "                ('linreg', LinearRegression())])"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2748,18 +3167,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
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-       "model_id": "887bf58cebf14bdba95db828390fd33d",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job b11be0d8-e6f1-41cb-8cb2-25a38e7ef311 is DONE. 24.7 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:b11be0d8-e6f1-41cb-8cb2-25a38e7ef311&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job ed42cbb3-3d25-47ca-96c5-71a84e426a8c is RUNNING. <a target=\"_blank\" href=\"https://consol…"
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@@ -2767,13 +3184,11 @@
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-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job f32ea25c-be39-4726-a8f5-604ae83849a6 is DONE. 8.5 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:f32ea25c-be39-4726-a8f5-604ae83849a6&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 3fc74930-03b9-4a49-8ed3-c3edc4dd6e51 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
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@@ -2781,13 +3196,11 @@
     },
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-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 86e29b78-76f5-4937-8bde-407b99af04a2 is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:86e29b78-76f5-4937-8bde-407b99af04a2&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 38a4ce3b-5c2a-4d44-b826-f24529d6500b is RUNNING. <a target=\"_blank\" href=\"https://consol…"
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@@ -2795,13 +3208,11 @@
     },
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-       "model_id": "4bc2c53aeb7d4a8280f9fbbe373f4b55",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job ca819734-0d41-4d9e-b743-09edae8c7fee is DONE. 29.6 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:ca819734-0d41-4d9e-b743-09edae8c7fee&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job ecad776d-77c8-4d94-8186-d5571b512b62 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
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@@ -2809,13 +3220,11 @@
     },
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-       "model_id": "f4f695cb0a224102b6e26adeb1827981",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 49bb5bed-cc84-47e0-9a90-08ab01e00548 is DONE. 536 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:49bb5bed-cc84-47e0-9a90-08ab01e00548&page=queryresults\">Open Job</a>"
+      ],
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-       "HTML(value='Query job c9bfc58f-ce2c-47a9-bbc7-b10d9de9b5a6 is DONE. 0 Bytes processed. <a target=\"_blank\" href…"
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@@ -2823,13 +3232,23 @@
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-       "model_id": "cb1df595006d485288a1060299970e5e",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 1e40a085-2289-47dd-afd8-820413186b9f is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:1e40a085-2289-47dd-afd8-820413186b9f&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 8fd8036e-3753-433d-975b-c7b42406f648 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Query job 60319296-a480-4f51-b7ad-190ac6de963a is DONE. 6.2 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:60319296-a480-4f51-b7ad-190ac6de963a&page=queryresults\">Open Job</a>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -2857,152 +3276,369 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>predicted_body_mass_g</th>\n",
+       "      <th>island</th>\n",
+       "      <th>culmen_length_mm</th>\n",
+       "      <th>culmen_depth_mm</th>\n",
+       "      <th>flipper_length_mm</th>\n",
+       "      <th>sex</th>\n",
+       "      <th>species</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>penguin_id</th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>3394.116212</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>4048.683645</td>\n",
+       "      <th>1</th>\n",
+       "      <td>3781.396682</td>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>39.1</td>\n",
+       "      <td>18.7</td>\n",
+       "      <td>181.0</td>\n",
+       "      <td>MALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>3976.452358</td>\n",
+       "      <th>4</th>\n",
+       "      <td>4124.102574</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>43.2</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>197.0</td>\n",
+       "      <td>MALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>3541.580346</td>\n",
+       "      <th>8</th>\n",
+       "      <td>4670.338389</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>46.5</td>\n",
+       "      <td>13.5</td>\n",
+       "      <td>210.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>25</th>\n",
-       "      <td>4032.842027</td>\n",
+       "      <th>11</th>\n",
+       "      <td>3529.411644</td>\n",
+       "      <td>Dream</td>\n",
+       "      <td>38.1</td>\n",
+       "      <td>18.6</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>4118.34983</td>\n",
+       "      <th>13</th>\n",
+       "      <td>4014.09632</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>37.8</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>MALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>4087.765797</td>\n",
+       "      <th>15</th>\n",
+       "      <td>5212.407319</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>48.7</td>\n",
+       "      <td>15.7</td>\n",
+       "      <td>208.0</td>\n",
+       "      <td>MALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>34</th>\n",
-       "      <td>3183.75379</td>\n",
+       "      <th>16</th>\n",
+       "      <td>4163.590502</td>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>34.6</td>\n",
+       "      <td>21.1</td>\n",
+       "      <td>198.0</td>\n",
+       "      <td>MALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>35</th>\n",
-       "      <td>3418.800633</td>\n",
+       "      <th>23</th>\n",
+       "      <td>3392.44731</td>\n",
+       "      <td>Dream</td>\n",
+       "      <td>42.2</td>\n",
+       "      <td>18.5</td>\n",
+       "      <td>180.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>39</th>\n",
-       "      <td>3519.18471</td>\n",
+       "      <th>34</th>\n",
+       "      <td>4698.299674</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>40.9</td>\n",
+       "      <td>13.7</td>\n",
+       "      <td>214.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>51</th>\n",
-       "      <td>3398.133564</td>\n",
+       "      <th>36</th>\n",
+       "      <td>4828.221398</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>43.4</td>\n",
+       "      <td>14.4</td>\n",
+       "      <td>218.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>52</th>\n",
-       "      <td>3223.614107</td>\n",
+       "      <th>42</th>\n",
+       "      <td>3430.582874</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>35.5</td>\n",
+       "      <td>16.2</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>60</th>\n",
-       "      <td>3445.012713</td>\n",
+       "      <th>48</th>\n",
+       "      <td>5314.254798</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>46.3</td>\n",
+       "      <td>15.8</td>\n",
+       "      <td>215.0</td>\n",
+       "      <td>MALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>61</th>\n",
-       "      <td>3505.637004</td>\n",
+       "      <td>5363.19995</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>46.2</td>\n",
+       "      <td>14.9</td>\n",
+       "      <td>221.0</td>\n",
+       "      <td>MALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>64</th>\n",
-       "      <td>3515.903779</td>\n",
+       "      <td>4855.90281</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>46.4</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>216.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>65</th>\n",
-       "      <td>4028.361259</td>\n",
+       "      <td>3413.094869</td>\n",
+       "      <td>Dream</td>\n",
+       "      <td>37.6</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>181.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>67</th>\n",
-       "      <td>4159.991956</td>\n",
+       "      <th>68</th>\n",
+       "      <td>3340.213193</td>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>36.2</td>\n",
+       "      <td>17.2</td>\n",
+       "      <td>187.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>83</th>\n",
-       "      <td>3348.167212</td>\n",
+       "      <th>70</th>\n",
+       "      <td>4228.726508</td>\n",
+       "      <td>Dream</td>\n",
+       "      <td>52.8</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>205.0</td>\n",
+       "      <td>MALE</td>\n",
+       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>85</th>\n",
-       "      <td>3485.048557</td>\n",
+       "      <th>72</th>\n",
+       "      <td>3811.532821</td>\n",
+       "      <td>Dream</td>\n",
+       "      <td>48.5</td>\n",
+       "      <td>17.5</td>\n",
+       "      <td>191.0</td>\n",
+       "      <td>MALE</td>\n",
+       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>93</th>\n",
-       "      <td>4172.872284</td>\n",
+       "      <th>74</th>\n",
+       "      <td>4659.765013</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>42.8</td>\n",
+       "      <td>14.2</td>\n",
+       "      <td>209.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>104</th>\n",
-       "      <td>3299.300454</td>\n",
+       "      <th>77</th>\n",
+       "      <td>3453.383042</td>\n",
+       "      <td>Dream</td>\n",
+       "      <td>37.3</td>\n",
+       "      <td>16.8</td>\n",
+       "      <td>192.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>105</th>\n",
-       "      <td>3515.68617</td>\n",
+       "      <th>81</th>\n",
+       "      <td>4766.239424</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>45.2</td>\n",
+       "      <td>14.8</td>\n",
+       "      <td>212.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>108</th>\n",
-       "      <td>3405.222757</td>\n",
+       "      <th>91</th>\n",
+       "      <td>4057.801947</td>\n",
+       "      <td>Dream</td>\n",
+       "      <td>50.8</td>\n",
+       "      <td>18.5</td>\n",
+       "      <td>201.0</td>\n",
+       "      <td>MALE</td>\n",
+       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>96</th>\n",
+       "      <td>4739.821792</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>45.4</td>\n",
+       "      <td>14.6</td>\n",
+       "      <td>211.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>113</th>\n",
-       "      <td>4209.13832</td>\n",
+       "      <th>105</th>\n",
+       "      <td>3394.886275</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>34.5</td>\n",
+       "      <td>18.1</td>\n",
+       "      <td>187.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>130</th>\n",
-       "      <td>4197.90382</td>\n",
+       "      <th>111</th>\n",
+       "      <td>3201.48777</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>37.9</td>\n",
+       "      <td>18.6</td>\n",
+       "      <td>172.0</td>\n",
+       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>25 rows × 1 columns</p>\n",
-       "</div>[67 rows x 1 columns in total]"
-      ],
-      "text/plain": [
-       "            predicted_body_mass_g\n",
-       "penguin_id                       \n",
-       "3                     3394.116212\n",
-       "8                     4048.683645\n",
-       "17                    3976.452358\n",
-       "23                    3541.580346\n",
-       "25                    4032.842027\n",
-       "27                     4118.34983\n",
-       "29                    4087.765797\n",
-       "34                     3183.75379\n",
-       "35                    3418.800633\n",
-       "39                     3519.18471\n",
-       "51                    3398.133564\n",
-       "52                    3223.614107\n",
-       "60                    3445.012713\n",
-       "61                    3505.637004\n",
-       "64                    3515.903779\n",
-       "65                    4028.361259\n",
-       "67                    4159.991956\n",
-       "83                    3348.167212\n",
-       "85                    3485.048557\n",
-       "93                    4172.872284\n",
-       "104                   3299.300454\n",
-       "105                    3515.68617\n",
-       "108                   3405.222757\n",
-       "113                    4209.13832\n",
-       "130                    4197.90382\n",
-       "...\n",
+       "<p>25 rows × 7 columns</p>\n",
+       "</div>[67 rows x 7 columns in total]"
+      ],
+      "text/plain": [
+       "            predicted_body_mass_g     island  culmen_length_mm  \\\n",
+       "penguin_id                                                       \n",
+       "1                     3781.396682  Torgersen              39.1   \n",
+       "4                     4124.102574     Biscoe              43.2   \n",
+       "8                     4670.338389     Biscoe              46.5   \n",
+       "11                    3529.411644      Dream              38.1   \n",
+       "13                     4014.09632     Biscoe              37.8   \n",
+       "15                    5212.407319     Biscoe              48.7   \n",
+       "16                    4163.590502  Torgersen              34.6   \n",
+       "23                     3392.44731      Dream              42.2   \n",
+       "34                    4698.299674     Biscoe              40.9   \n",
+       "36                    4828.221398     Biscoe              43.4   \n",
+       "42                    3430.582874     Biscoe              35.5   \n",
+       "48                    5314.254798     Biscoe              46.3   \n",
+       "61                     5363.19995     Biscoe              46.2   \n",
+       "64                     4855.90281     Biscoe              46.4   \n",
+       "65                    3413.094869      Dream              37.6   \n",
+       "68                    3340.213193  Torgersen              36.2   \n",
+       "70                    4228.726508      Dream              52.8   \n",
+       "72                    3811.532821      Dream              48.5   \n",
+       "74                    4659.765013     Biscoe              42.8   \n",
+       "77                    3453.383042      Dream              37.3   \n",
+       "81                    4766.239424     Biscoe              45.2   \n",
+       "91                    4057.801947      Dream              50.8   \n",
+       "96                    4739.821792     Biscoe              45.4   \n",
+       "105                   3394.886275     Biscoe              34.5   \n",
+       "111                    3201.48777     Biscoe              37.9   \n",
        "\n",
-       "[67 rows x 1 columns]"
+       "            culmen_depth_mm  flipper_length_mm     sex  \\\n",
+       "penguin_id                                               \n",
+       "1                      18.7              181.0    MALE   \n",
+       "4                      19.0              197.0    MALE   \n",
+       "8                      13.5              210.0  FEMALE   \n",
+       "11                     18.6              190.0  FEMALE   \n",
+       "13                     20.0              190.0    MALE   \n",
+       "15                     15.7              208.0    MALE   \n",
+       "16                     21.1              198.0    MALE   \n",
+       "23                     18.5              180.0  FEMALE   \n",
+       "34                     13.7              214.0  FEMALE   \n",
+       "36                     14.4              218.0  FEMALE   \n",
+       "42                     16.2              195.0  FEMALE   \n",
+       "48                     15.8              215.0    MALE   \n",
+       "61                     14.9              221.0    MALE   \n",
+       "64                     15.0              216.0  FEMALE   \n",
+       "65                     19.3              181.0  FEMALE   \n",
+       "68                     17.2              187.0  FEMALE   \n",
+       "70                     20.0              205.0    MALE   \n",
+       "72                     17.5              191.0    MALE   \n",
+       "74                     14.2              209.0  FEMALE   \n",
+       "77                     16.8              192.0  FEMALE   \n",
+       "81                     14.8              212.0  FEMALE   \n",
+       "91                     18.5              201.0    MALE   \n",
+       "96                     14.6              211.0  FEMALE   \n",
+       "105                    18.1              187.0  FEMALE   \n",
+       "111                    18.6              172.0  FEMALE   \n",
+       "\n",
+       "                                              species  \n",
+       "penguin_id                                             \n",
+       "1                 Adelie Penguin (Pygoscelis adeliae)  \n",
+       "4                 Adelie Penguin (Pygoscelis adeliae)  \n",
+       "8                   Gentoo penguin (Pygoscelis papua)  \n",
+       "11                Adelie Penguin (Pygoscelis adeliae)  \n",
+       "13                Adelie Penguin (Pygoscelis adeliae)  \n",
+       "15                  Gentoo penguin (Pygoscelis papua)  \n",
+       "16                Adelie Penguin (Pygoscelis adeliae)  \n",
+       "23                Adelie Penguin (Pygoscelis adeliae)  \n",
+       "34                  Gentoo penguin (Pygoscelis papua)  \n",
+       "36                  Gentoo penguin (Pygoscelis papua)  \n",
+       "42                Adelie Penguin (Pygoscelis adeliae)  \n",
+       "48                  Gentoo penguin (Pygoscelis papua)  \n",
+       "61                  Gentoo penguin (Pygoscelis papua)  \n",
+       "64                  Gentoo penguin (Pygoscelis papua)  \n",
+       "65                Adelie Penguin (Pygoscelis adeliae)  \n",
+       "68                Adelie Penguin (Pygoscelis adeliae)  \n",
+       "70          Chinstrap penguin (Pygoscelis antarctica)  \n",
+       "72          Chinstrap penguin (Pygoscelis antarctica)  \n",
+       "74                  Gentoo penguin (Pygoscelis papua)  \n",
+       "77                Adelie Penguin (Pygoscelis adeliae)  \n",
+       "81                  Gentoo penguin (Pygoscelis papua)  \n",
+       "91          Chinstrap penguin (Pygoscelis antarctica)  \n",
+       "96                  Gentoo penguin (Pygoscelis papua)  \n",
+       "105               Adelie Penguin (Pygoscelis adeliae)  \n",
+       "111               Adelie Penguin (Pygoscelis adeliae)  \n",
+       "\n",
+       "[67 rows x 7 columns]"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3034,60 +3670,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2d32081be31f44abb8de67e2209d76cd",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "HTML(value='Query job 2a043039-670f-4eb8-9cf0-765ee6ed7de6 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
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-       "version_minor": 0
-      },
-      "text/plain": [
-       "HTML(value='Query job 7a3da9b3-e6d5-453a-8178-9cb311e83113 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
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-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "HTML(value='Query job 5fcfd48b-c26f-487e-8387-c662b59ea424 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
-      ]
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-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "54d4f250e1014de181931e5ffe4f5525",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job c02fb597-8d5a-42ca-9185-03b59c5ef2f9 is DONE. 29.6 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:c02fb597-8d5a-42ca-9185-03b59c5ef2f9&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job bc8b2042-1e13-441c-9531-300ed5badb7a is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -3095,13 +3687,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "4588ae10de634460bf4026ddd9076351",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 7f1f565b-0f73-4a4e-b33f-8484fa260838 is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:7f1f565b-0f73-4a4e-b33f-8484fa260838&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 5e867182-dd7a-4aff-87a8-f7596e900fd5 is DONE. 0 Bytes processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -3109,13 +3699,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "8209cf8286a545ebb7b6ef9d002a43a1",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job d4b9d4a6-d75e-46e1-b092-ab58e8aef890 is DONE. 48 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:d4b9d4a6-d75e-46e1-b092-ab58e8aef890&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job d4cdb016-8f1e-4960-8ed7-4524ccc5a8a8 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -3153,12 +3741,12 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>229.48269</td>\n",
-       "      <td>82962.794947</td>\n",
-       "      <td>0.004248</td>\n",
-       "      <td>206.728384</td>\n",
-       "      <td>0.88633</td>\n",
-       "      <td>0.892953</td>\n",
+       "      <td>216.444357</td>\n",
+       "      <td>72639.698707</td>\n",
+       "      <td>0.00463</td>\n",
+       "      <td>170.588356</td>\n",
+       "      <td>0.896396</td>\n",
+       "      <td>0.900547</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -3167,15 +3755,15 @@
       ],
       "text/plain": [
        "   mean_absolute_error  mean_squared_error  mean_squared_log_error  \\\n",
-       "0            229.48269        82962.794947                0.004248   \n",
+       "0           216.444357        72639.698707                 0.00463   \n",
        "\n",
        "   median_absolute_error  r2_score  explained_variance  \n",
-       "0             206.728384   0.88633            0.892953  \n",
+       "0             170.588356  0.896396            0.900547  \n",
        "\n",
        "[1 rows x 6 columns]"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3195,18 +3783,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f32692d89f00406499f4ea5aa55268fb",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 73448ee8-698b-435f-b11e-6fe2de3bcd8d is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:73448ee8-698b-435f-b11e-6fe2de3bcd8d&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job e57383ef-f043-458b-96c6-893e7c5b0c00 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -3214,13 +3800,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "72e5f23a99de4a818c8493b8b4f3854d",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job e002f59d-a03c-4ec9-a85a-93adbfd7bd17 is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:e002f59d-a03c-4ec9-a85a-93adbfd7bd17&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 1a9db485-477b-43e2-94eb-dea7dc21d45d is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -3228,13 +3812,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9d5333a91b504dd9be51c997715530ab",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 4ab1febc-fb55-473a-b295-69e4329cc5f0 is DONE. 30.0 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:4ab1febc-fb55-473a-b295-69e4329cc5f0&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 4570a563-b8e0-4308-b8cb-c4731491d4f7 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -3243,10 +3825,10 @@
     {
      "data": {
       "text/plain": [
-       "0.8863300923278365"
+       "0.8963962044533755"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3254,7 +3836,7 @@
    "source": [
     "from bigframes.ml.metrics import r2_score\n",
     "\n",
-    "r2_score(y_test, predicted_y_test)"
+    "r2_score(y_test, predicted_y_test[\"predicted_body_mass_g\"])"
    ]
   },
   {
@@ -3274,57 +3856,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "fbc4a70f31d4465b974a7f7c9cc97731",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "HTML(value='Copy job c2413be4-6972-4e36-8234-5063628b6d71 is RUNNING. <a target=\"_blank\" href=\"https://console…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "Pipeline(steps=[('transform',\n",
-       "                 ColumnTransformer(transformers=[('ont_hot_encoder',\n",
-       "                                                  OneHotEncoder(max_categories=1000001,\n",
-       "                                                                min_frequency=0),\n",
-       "                                                  'island'),\n",
-       "                                                 ('standard_scaler',\n",
-       "                                                  StandardScaler(),\n",
-       "                                                  'culmen_length_mm'),\n",
-       "                                                 ('standard_scaler',\n",
-       "                                                  StandardScaler(),\n",
-       "                                                  'culmen_depth_mm'),\n",
-       "                                                 ('standard_scaler',\n",
-       "                                                  StandardScaler(),\n",
-       "                                                  'flipper_length_mm'),\n",
-       "                                                 ('ont_hot_encoder',\n",
-       "                                                  OneHotEncoder(max_categories=1000001,\n",
-       "                                                                min_frequency=0),\n",
-       "                                                  'sex'),\n",
-       "                                                 ('ont_hot_encoder',\n",
-       "                                                  OneHotEncoder(max_categories=1000001,\n",
-       "                                                                min_frequency=0),\n",
-       "                                                  'species')])),\n",
-       "                ('estimator',\n",
-       "                 LinearRegression(optimize_strategy='NORMAL_EQUATION'))])"
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# # Replace with a path where you have permission to save a model\n",
     "# model_name = \"bigframes-dev.bqml_tutorial.penguins_model\"\n",
@@ -3334,43 +3868,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 16,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Pipeline(steps=[('transform',\n",
-       "                 ColumnTransformer(transformers=[('ont_hot_encoder',\n",
-       "                                                  OneHotEncoder(max_categories=1000001,\n",
-       "                                                                min_frequency=0),\n",
-       "                                                  'island'),\n",
-       "                                                 ('standard_scaler',\n",
-       "                                                  StandardScaler(),\n",
-       "                                                  'culmen_length_mm'),\n",
-       "                                                 ('standard_scaler',\n",
-       "                                                  StandardScaler(),\n",
-       "                                                  'culmen_depth_mm'),\n",
-       "                                                 ('standard_scaler',\n",
-       "                                                  StandardScaler(),\n",
-       "                                                  'flipper_length_mm'),\n",
-       "                                                 ('ont_hot_encoder',\n",
-       "                                                  OneHotEncoder(max_categories=1000001,\n",
-       "                                                                min_frequency=0),\n",
-       "                                                  'sex'),\n",
-       "                                                 ('ont_hot_encoder',\n",
-       "                                                  OneHotEncoder(max_categories=1000001,\n",
-       "                                                                min_frequency=0),\n",
-       "                                                  'species')])),\n",
-       "                ('estimator',\n",
-       "                 LinearRegression(optimize_strategy='NORMAL_EQUATION'))])"
-      ]
-     },
-     "execution_count": 34,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# # WARNING - until b/281709360 is fixed & pipeline is updated, pipelines will load as models,\n",
     "# # and details of their transform steps will be lost (the loaded model will behave the same)\n",
@@ -3394,7 +3894,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.10.9"
   },
   "orig_nbformat": 4,
   "vscode": {
diff --git a/notebooks/regression/sklearn_linear_regression.ipynb b/notebooks/regression/sklearn_linear_regression.ipynb
index beb77ef092..ec14d15cdf 100644
--- a/notebooks/regression/sklearn_linear_regression.ipynb
+++ b/notebooks/regression/sklearn_linear_regression.ipynb
@@ -20,46 +20,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "62b29650872b4c438d0eefb825fcae32",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "HTML(value='Query job d47c23df-1830-4451-9016-7747c1420abd is RUNNING. <a target=\"_blank\" href=\"https://consol…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1ef2cf509710492eb37abd1f1feda149",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "HTML(value='Query job 7ada8963-c6e6-4d46-b42d-8a8cc6d6ead2 is DONE. 0 Bytes processed. <a target=\"_blank\" href…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2a2f06590494449982273038aa18699f",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job f201b84b-5506-4038-92e6-b4a82318df8f is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:f201b84b-5506-4038-92e6-b4a82318df8f&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 31a5b656-000e-4238-9fd9-c6e644ca298f is DONE. 31.7 kB processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -67,13 +37,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "0f25faa156584cc59dda9b0e60f72534",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 12e0f983-695e-4903-8ff1-2f353d7e8cba is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:12e0f983-695e-4903-8ff1-2f353d7e8cba&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job d8eed0ca-7ce9-4ed8-a592-e16af9f9db8d is DONE. 0 Bytes processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -113,250 +81,250 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>36.6</td>\n",
-       "      <td>18.4</td>\n",
-       "      <td>184.0</td>\n",
-       "      <td>3475.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>40.1</td>\n",
+       "      <td>18.9</td>\n",
+       "      <td>188.0</td>\n",
+       "      <td>4300.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>39.8</td>\n",
-       "      <td>19.1</td>\n",
-       "      <td>184.0</td>\n",
-       "      <td>4650.0</td>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>39.1</td>\n",
+       "      <td>18.7</td>\n",
+       "      <td>181.0</td>\n",
+       "      <td>3750.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>40.9</td>\n",
-       "      <td>18.9</td>\n",
-       "      <td>184.0</td>\n",
-       "      <td>3900.0</td>\n",
-       "      <td>MALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>47.4</td>\n",
+       "      <td>14.6</td>\n",
+       "      <td>212.0</td>\n",
+       "      <td>4725.0</td>\n",
+       "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>46.5</td>\n",
-       "      <td>17.9</td>\n",
-       "      <td>192.0</td>\n",
-       "      <td>3500.0</td>\n",
+       "      <td>42.5</td>\n",
+       "      <td>16.7</td>\n",
+       "      <td>187.0</td>\n",
+       "      <td>3350.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>37.3</td>\n",
-       "      <td>16.8</td>\n",
-       "      <td>192.0</td>\n",
-       "      <td>3000.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>43.2</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>197.0</td>\n",
+       "      <td>4775.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>43.2</td>\n",
-       "      <td>18.5</td>\n",
-       "      <td>192.0</td>\n",
-       "      <td>4100.0</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>46.7</td>\n",
+       "      <td>15.3</td>\n",
+       "      <td>219.0</td>\n",
+       "      <td>5200.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>46.9</td>\n",
-       "      <td>16.6</td>\n",
-       "      <td>192.0</td>\n",
-       "      <td>2700.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>41.3</td>\n",
+       "      <td>21.1</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>4400.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>50.5</td>\n",
-       "      <td>18.4</td>\n",
-       "      <td>200.0</td>\n",
-       "      <td>3400.0</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>45.2</td>\n",
+       "      <td>13.8</td>\n",
+       "      <td>215.0</td>\n",
+       "      <td>4750.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>49.5</td>\n",
-       "      <td>19.0</td>\n",
-       "      <td>200.0</td>\n",
-       "      <td>3800.0</td>\n",
-       "      <td>MALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>46.5</td>\n",
+       "      <td>13.5</td>\n",
+       "      <td>210.0</td>\n",
+       "      <td>4550.0</td>\n",
+       "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>40.2</td>\n",
-       "      <td>20.1</td>\n",
-       "      <td>200.0</td>\n",
-       "      <td>3975.0</td>\n",
-       "      <td>MALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>50.5</td>\n",
+       "      <td>15.2</td>\n",
+       "      <td>216.0</td>\n",
+       "      <td>5000.0</td>\n",
+       "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>40.8</td>\n",
-       "      <td>18.9</td>\n",
-       "      <td>208.0</td>\n",
-       "      <td>4300.0</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>48.2</td>\n",
+       "      <td>15.6</td>\n",
+       "      <td>221.0</td>\n",
+       "      <td>5100.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>39.0</td>\n",
-       "      <td>18.7</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3650.0</td>\n",
-       "      <td>MALE</td>\n",
+       "      <td>38.1</td>\n",
+       "      <td>18.6</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>3700.0</td>\n",
+       "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>37.0</td>\n",
-       "      <td>16.9</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3000.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>50.7</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>223.0</td>\n",
+       "      <td>5550.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>47.0</td>\n",
-       "      <td>17.3</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3700.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>37.8</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>4250.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>34.0</td>\n",
-       "      <td>17.1</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3400.0</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>17.9</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>3450.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>37.0</td>\n",
-       "      <td>16.5</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3400.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>48.7</td>\n",
+       "      <td>15.7</td>\n",
+       "      <td>208.0</td>\n",
+       "      <td>5350.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>45.7</td>\n",
-       "      <td>17.3</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3600.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>34.6</td>\n",
+       "      <td>21.1</td>\n",
+       "      <td>198.0</td>\n",
+       "      <td>4400.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>50.6</td>\n",
-       "      <td>19.4</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3800.0</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>46.8</td>\n",
+       "      <td>15.4</td>\n",
+       "      <td>215.0</td>\n",
+       "      <td>5150.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>39.7</td>\n",
-       "      <td>17.9</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>4250.0</td>\n",
+       "      <td>50.3</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>197.0</td>\n",
+       "      <td>3300.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>37.8</td>\n",
+       "      <td>37.2</td>\n",
        "      <td>18.1</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3750.0</td>\n",
+       "      <td>178.0</td>\n",
+       "      <td>3900.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>20</th>\n",
        "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>46.6</td>\n",
-       "      <td>17.8</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3800.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>18.8</td>\n",
+       "      <td>203.0</td>\n",
+       "      <td>4100.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>21</th>\n",
-       "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>51.3</td>\n",
-       "      <td>19.2</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3650.0</td>\n",
-       "      <td>MALE</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>40.5</td>\n",
+       "      <td>17.9</td>\n",
+       "      <td>187.0</td>\n",
+       "      <td>3200.0</td>\n",
+       "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22</th>\n",
-       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
-       "      <td>Dream</td>\n",
-       "      <td>40.2</td>\n",
-       "      <td>17.1</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3400.0</td>\n",
+       "      <td>Gentoo penguin (Pygoscelis papua)</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>45.5</td>\n",
+       "      <td>13.9</td>\n",
+       "      <td>210.0</td>\n",
+       "      <td>4200.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>23</th>\n",
        "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>36.8</td>\n",
+       "      <td>42.2</td>\n",
        "      <td>18.5</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3500.0</td>\n",
+       "      <td>180.0</td>\n",
+       "      <td>3550.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>24</th>\n",
        "      <td>Chinstrap penguin (Pygoscelis antarctica)</td>\n",
        "      <td>Dream</td>\n",
-       "      <td>49.6</td>\n",
-       "      <td>18.2</td>\n",
-       "      <td>193.0</td>\n",
+       "      <td>51.7</td>\n",
+       "      <td>20.3</td>\n",
+       "      <td>194.0</td>\n",
        "      <td>3775.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
@@ -366,65 +334,65 @@
        "</div>[344 rows x 7 columns in total]"
       ],
       "text/plain": [
-       "                                      species island  culmen_length_mm  \\\n",
-       "0         Adelie Penguin (Pygoscelis adeliae)  Dream              36.6   \n",
-       "1         Adelie Penguin (Pygoscelis adeliae)  Dream              39.8   \n",
-       "2         Adelie Penguin (Pygoscelis adeliae)  Dream              40.9   \n",
-       "3   Chinstrap penguin (Pygoscelis antarctica)  Dream              46.5   \n",
-       "4         Adelie Penguin (Pygoscelis adeliae)  Dream              37.3   \n",
-       "5         Adelie Penguin (Pygoscelis adeliae)  Dream              43.2   \n",
-       "6   Chinstrap penguin (Pygoscelis antarctica)  Dream              46.9   \n",
-       "7   Chinstrap penguin (Pygoscelis antarctica)  Dream              50.5   \n",
-       "8   Chinstrap penguin (Pygoscelis antarctica)  Dream              49.5   \n",
-       "9         Adelie Penguin (Pygoscelis adeliae)  Dream              40.2   \n",
-       "10        Adelie Penguin (Pygoscelis adeliae)  Dream              40.8   \n",
-       "11        Adelie Penguin (Pygoscelis adeliae)  Dream              39.0   \n",
-       "12        Adelie Penguin (Pygoscelis adeliae)  Dream              37.0   \n",
-       "13  Chinstrap penguin (Pygoscelis antarctica)  Dream              47.0   \n",
-       "14        Adelie Penguin (Pygoscelis adeliae)  Dream              34.0   \n",
-       "15        Adelie Penguin (Pygoscelis adeliae)  Dream              37.0   \n",
-       "16  Chinstrap penguin (Pygoscelis antarctica)  Dream              45.7   \n",
-       "17  Chinstrap penguin (Pygoscelis antarctica)  Dream              50.6   \n",
-       "18        Adelie Penguin (Pygoscelis adeliae)  Dream              39.7   \n",
-       "19        Adelie Penguin (Pygoscelis adeliae)  Dream              37.8   \n",
-       "20  Chinstrap penguin (Pygoscelis antarctica)  Dream              46.6   \n",
-       "21  Chinstrap penguin (Pygoscelis antarctica)  Dream              51.3   \n",
-       "22        Adelie Penguin (Pygoscelis adeliae)  Dream              40.2   \n",
-       "23        Adelie Penguin (Pygoscelis adeliae)  Dream              36.8   \n",
-       "24  Chinstrap penguin (Pygoscelis antarctica)  Dream              49.6   \n",
+       "                                      species     island  culmen_length_mm  \\\n",
+       "0         Adelie Penguin (Pygoscelis adeliae)     Biscoe              40.1   \n",
+       "1         Adelie Penguin (Pygoscelis adeliae)  Torgersen              39.1   \n",
+       "2           Gentoo penguin (Pygoscelis papua)     Biscoe              47.4   \n",
+       "3   Chinstrap penguin (Pygoscelis antarctica)      Dream              42.5   \n",
+       "4         Adelie Penguin (Pygoscelis adeliae)     Biscoe              43.2   \n",
+       "5           Gentoo penguin (Pygoscelis papua)     Biscoe              46.7   \n",
+       "6         Adelie Penguin (Pygoscelis adeliae)     Biscoe              41.3   \n",
+       "7           Gentoo penguin (Pygoscelis papua)     Biscoe              45.2   \n",
+       "8           Gentoo penguin (Pygoscelis papua)     Biscoe              46.5   \n",
+       "9           Gentoo penguin (Pygoscelis papua)     Biscoe              50.5   \n",
+       "10          Gentoo penguin (Pygoscelis papua)     Biscoe              48.2   \n",
+       "11        Adelie Penguin (Pygoscelis adeliae)      Dream              38.1   \n",
+       "12          Gentoo penguin (Pygoscelis papua)     Biscoe              50.7   \n",
+       "13        Adelie Penguin (Pygoscelis adeliae)     Biscoe              37.8   \n",
+       "14        Adelie Penguin (Pygoscelis adeliae)     Biscoe              35.0   \n",
+       "15          Gentoo penguin (Pygoscelis papua)     Biscoe              48.7   \n",
+       "16        Adelie Penguin (Pygoscelis adeliae)  Torgersen              34.6   \n",
+       "17          Gentoo penguin (Pygoscelis papua)     Biscoe              46.8   \n",
+       "18  Chinstrap penguin (Pygoscelis antarctica)      Dream              50.3   \n",
+       "19        Adelie Penguin (Pygoscelis adeliae)      Dream              37.2   \n",
+       "20  Chinstrap penguin (Pygoscelis antarctica)      Dream              51.0   \n",
+       "21        Adelie Penguin (Pygoscelis adeliae)     Biscoe              40.5   \n",
+       "22          Gentoo penguin (Pygoscelis papua)     Biscoe              45.5   \n",
+       "23        Adelie Penguin (Pygoscelis adeliae)      Dream              42.2   \n",
+       "24  Chinstrap penguin (Pygoscelis antarctica)      Dream              51.7   \n",
        "\n",
        "    culmen_depth_mm  flipper_length_mm  body_mass_g     sex  \n",
-       "0              18.4              184.0       3475.0  FEMALE  \n",
-       "1              19.1              184.0       4650.0    MALE  \n",
-       "2              18.9              184.0       3900.0    MALE  \n",
-       "3              17.9              192.0       3500.0  FEMALE  \n",
-       "4              16.8              192.0       3000.0  FEMALE  \n",
-       "5              18.5              192.0       4100.0    MALE  \n",
-       "6              16.6              192.0       2700.0  FEMALE  \n",
-       "7              18.4              200.0       3400.0  FEMALE  \n",
-       "8              19.0              200.0       3800.0    MALE  \n",
-       "9              20.1              200.0       3975.0    MALE  \n",
-       "10             18.9              208.0       4300.0    MALE  \n",
-       "11             18.7              185.0       3650.0    MALE  \n",
-       "12             16.9              185.0       3000.0  FEMALE  \n",
-       "13             17.3              185.0       3700.0  FEMALE  \n",
-       "14             17.1              185.0       3400.0  FEMALE  \n",
-       "15             16.5              185.0       3400.0  FEMALE  \n",
-       "16             17.3              193.0       3600.0  FEMALE  \n",
-       "17             19.4              193.0       3800.0    MALE  \n",
-       "18             17.9              193.0       4250.0    MALE  \n",
-       "19             18.1              193.0       3750.0    MALE  \n",
-       "20             17.8              193.0       3800.0  FEMALE  \n",
-       "21             19.2              193.0       3650.0    MALE  \n",
-       "22             17.1              193.0       3400.0  FEMALE  \n",
-       "23             18.5              193.0       3500.0  FEMALE  \n",
-       "24             18.2              193.0       3775.0    MALE  \n",
+       "0              18.9              188.0       4300.0    MALE  \n",
+       "1              18.7              181.0       3750.0    MALE  \n",
+       "2              14.6              212.0       4725.0  FEMALE  \n",
+       "3              16.7              187.0       3350.0  FEMALE  \n",
+       "4              19.0              197.0       4775.0    MALE  \n",
+       "5              15.3              219.0       5200.0    MALE  \n",
+       "6              21.1              195.0       4400.0    MALE  \n",
+       "7              13.8              215.0       4750.0  FEMALE  \n",
+       "8              13.5              210.0       4550.0  FEMALE  \n",
+       "9              15.2              216.0       5000.0  FEMALE  \n",
+       "10             15.6              221.0       5100.0    MALE  \n",
+       "11             18.6              190.0       3700.0  FEMALE  \n",
+       "12             15.0              223.0       5550.0    MALE  \n",
+       "13             20.0              190.0       4250.0    MALE  \n",
+       "14             17.9              190.0       3450.0  FEMALE  \n",
+       "15             15.7              208.0       5350.0    MALE  \n",
+       "16             21.1              198.0       4400.0    MALE  \n",
+       "17             15.4              215.0       5150.0    MALE  \n",
+       "18             20.0              197.0       3300.0    MALE  \n",
+       "19             18.1              178.0       3900.0    MALE  \n",
+       "20             18.8              203.0       4100.0    MALE  \n",
+       "21             17.9              187.0       3200.0  FEMALE  \n",
+       "22             13.9              210.0       4200.0  FEMALE  \n",
+       "23             18.5              180.0       3550.0  FEMALE  \n",
+       "24             20.3              194.0       3775.0    MALE  \n",
        "...\n",
        "\n",
        "[344 rows x 7 columns]"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -450,32 +418,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a9ad907fa6e64a61a9dce420bc7d2beb",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "HTML(value='Query job 3537a10a-641a-4d40-ae47-449c641b1bc5 is DONE. 28.9 kB processed. <a target=\"_blank\" href…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "94360b343eed419c884383a39e0d563d",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 81305962-a96a-4c86-949c-471b2ae7c86d is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:81305962-a96a-4c86-949c-471b2ae7c86d&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 34101409-7c65-4045-ad52-c6ba24dc9cbb is DONE. 31.7 kB processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -483,13 +435,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "514e68d5b0b4452a9ccdff947848541a",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 2af0b0d6-c11b-499e-8d25-a2c628b2853b is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:2af0b0d6-c11b-499e-8d25-a2c628b2853b&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 74190ac2-21a2-47b0-bc21-ef5373565f17 is DONE. 0 Bytes processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -527,294 +477,294 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>36.6</td>\n",
-       "      <td>18.4</td>\n",
-       "      <td>184.0</td>\n",
-       "      <td>3475.0</td>\n",
-       "      <td>FEMALE</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>39.8</td>\n",
-       "      <td>19.1</td>\n",
-       "      <td>184.0</td>\n",
-       "      <td>4650.0</td>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>40.1</td>\n",
+       "      <td>18.9</td>\n",
+       "      <td>188.0</td>\n",
+       "      <td>4300.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>40.9</td>\n",
-       "      <td>18.9</td>\n",
-       "      <td>184.0</td>\n",
-       "      <td>3900.0</td>\n",
+       "      <th>1</th>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>39.1</td>\n",
+       "      <td>18.7</td>\n",
+       "      <td>181.0</td>\n",
+       "      <td>3750.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>37.3</td>\n",
-       "      <td>16.8</td>\n",
-       "      <td>192.0</td>\n",
-       "      <td>3000.0</td>\n",
-       "      <td>FEMALE</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>Dream</td>\n",
+       "      <td>Biscoe</td>\n",
        "      <td>43.2</td>\n",
-       "      <td>18.5</td>\n",
-       "      <td>192.0</td>\n",
-       "      <td>4100.0</td>\n",
-       "      <td>MALE</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>40.2</td>\n",
-       "      <td>20.1</td>\n",
-       "      <td>200.0</td>\n",
-       "      <td>3975.0</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>197.0</td>\n",
+       "      <td>4775.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>10</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>40.8</td>\n",
-       "      <td>18.9</td>\n",
-       "      <td>208.0</td>\n",
-       "      <td>4300.0</td>\n",
+       "      <th>6</th>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>41.3</td>\n",
+       "      <td>21.1</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>4400.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
        "      <td>Dream</td>\n",
-       "      <td>39.0</td>\n",
-       "      <td>18.7</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3650.0</td>\n",
-       "      <td>MALE</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>37.0</td>\n",
-       "      <td>16.9</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3000.0</td>\n",
+       "      <td>38.1</td>\n",
+       "      <td>18.6</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>3700.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>34.0</td>\n",
-       "      <td>17.1</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3400.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <th>13</th>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>37.8</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>4250.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>37.0</td>\n",
-       "      <td>16.5</td>\n",
-       "      <td>185.0</td>\n",
-       "      <td>3400.0</td>\n",
+       "      <th>14</th>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>17.9</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>3450.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>18</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>39.7</td>\n",
-       "      <td>17.9</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>4250.0</td>\n",
+       "      <th>16</th>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>34.6</td>\n",
+       "      <td>21.1</td>\n",
+       "      <td>198.0</td>\n",
+       "      <td>4400.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19</th>\n",
        "      <td>Dream</td>\n",
-       "      <td>37.8</td>\n",
+       "      <td>37.2</td>\n",
        "      <td>18.1</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3750.0</td>\n",
+       "      <td>178.0</td>\n",
+       "      <td>3900.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>22</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>40.2</td>\n",
-       "      <td>17.1</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3400.0</td>\n",
+       "      <th>21</th>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>40.5</td>\n",
+       "      <td>17.9</td>\n",
+       "      <td>187.0</td>\n",
+       "      <td>3200.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>23</th>\n",
        "      <td>Dream</td>\n",
-       "      <td>36.8</td>\n",
+       "      <td>42.2</td>\n",
        "      <td>18.5</td>\n",
-       "      <td>193.0</td>\n",
-       "      <td>3500.0</td>\n",
+       "      <td>180.0</td>\n",
+       "      <td>3550.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>26</th>\n",
+       "      <th>30</th>\n",
        "      <td>Dream</td>\n",
-       "      <td>41.5</td>\n",
-       "      <td>18.5</td>\n",
-       "      <td>201.0</td>\n",
-       "      <td>4000.0</td>\n",
+       "      <td>39.2</td>\n",
+       "      <td>21.1</td>\n",
+       "      <td>196.0</td>\n",
+       "      <td>4150.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>31</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>33.1</td>\n",
-       "      <td>16.1</td>\n",
-       "      <td>178.0</td>\n",
-       "      <td>2900.0</td>\n",
-       "      <td>FEMALE</td>\n",
+       "      <th>32</th>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>42.9</td>\n",
+       "      <td>17.6</td>\n",
+       "      <td>196.0</td>\n",
+       "      <td>4700.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>32</th>\n",
+       "      <th>38</th>\n",
        "      <td>Dream</td>\n",
-       "      <td>37.2</td>\n",
-       "      <td>18.1</td>\n",
-       "      <td>178.0</td>\n",
+       "      <td>41.1</td>\n",
+       "      <td>17.5</td>\n",
+       "      <td>190.0</td>\n",
        "      <td>3900.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>33</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>39.5</td>\n",
-       "      <td>16.7</td>\n",
-       "      <td>178.0</td>\n",
-       "      <td>3250.0</td>\n",
+       "      <th>40</th>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>38.6</td>\n",
+       "      <td>21.2</td>\n",
+       "      <td>191.0</td>\n",
+       "      <td>3800.0</td>\n",
+       "      <td>MALE</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>35.5</td>\n",
+       "      <td>16.2</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>3350.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>35</th>\n",
+       "      <th>44</th>\n",
        "      <td>Dream</td>\n",
-       "      <td>36.0</td>\n",
-       "      <td>18.5</td>\n",
+       "      <td>39.2</td>\n",
+       "      <td>18.6</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>4250.0</td>\n",
+       "      <td>MALE</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>35.2</td>\n",
+       "      <td>15.9</td>\n",
        "      <td>186.0</td>\n",
-       "      <td>3100.0</td>\n",
+       "      <td>3050.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>36</th>\n",
+       "      <th>46</th>\n",
        "      <td>Dream</td>\n",
+       "      <td>43.2</td>\n",
+       "      <td>18.5</td>\n",
+       "      <td>192.0</td>\n",
+       "      <td>4100.0</td>\n",
+       "      <td>MALE</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>Biscoe</td>\n",
        "      <td>39.6</td>\n",
-       "      <td>18.1</td>\n",
+       "      <td>17.7</td>\n",
        "      <td>186.0</td>\n",
-       "      <td>4450.0</td>\n",
-       "      <td>MALE</td>\n",
+       "      <td>3500.0</td>\n",
+       "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>38</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>41.3</td>\n",
+       "      <th>53</th>\n",
+       "      <td>Biscoe</td>\n",
+       "      <td>45.6</td>\n",
        "      <td>20.3</td>\n",
-       "      <td>194.0</td>\n",
-       "      <td>3550.0</td>\n",
+       "      <td>191.0</td>\n",
+       "      <td>4600.0</td>\n",
        "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>41</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>35.7</td>\n",
-       "      <td>18.0</td>\n",
-       "      <td>202.0</td>\n",
-       "      <td>3550.0</td>\n",
+       "      <th>58</th>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>40.9</td>\n",
+       "      <td>16.8</td>\n",
+       "      <td>191.0</td>\n",
+       "      <td>3700.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>51</th>\n",
-       "      <td>Dream</td>\n",
-       "      <td>38.1</td>\n",
-       "      <td>17.6</td>\n",
-       "      <td>187.0</td>\n",
-       "      <td>3425.0</td>\n",
+       "      <th>60</th>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>40.3</td>\n",
+       "      <td>18.0</td>\n",
+       "      <td>195.0</td>\n",
+       "      <td>3250.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>53</th>\n",
+       "      <th>62</th>\n",
        "      <td>Dream</td>\n",
        "      <td>36.0</td>\n",
-       "      <td>17.1</td>\n",
-       "      <td>187.0</td>\n",
-       "      <td>3700.0</td>\n",
+       "      <td>18.5</td>\n",
+       "      <td>186.0</td>\n",
+       "      <td>3100.0</td>\n",
        "      <td>FEMALE</td>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>63</th>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>39.3</td>\n",
+       "      <td>20.6</td>\n",
+       "      <td>190.0</td>\n",
+       "      <td>3650.0</td>\n",
+       "      <td>MALE</td>\n",
+       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>25 rows × 6 columns</p>\n",
        "</div>[146 rows x 6 columns in total]"
       ],
       "text/plain": [
-       "   island  culmen_length_mm  culmen_depth_mm  flipper_length_mm  body_mass_g  \\\n",
-       "0   Dream              36.6             18.4              184.0       3475.0   \n",
-       "1   Dream              39.8             19.1              184.0       4650.0   \n",
-       "2   Dream              40.9             18.9              184.0       3900.0   \n",
-       "4   Dream              37.3             16.8              192.0       3000.0   \n",
-       "5   Dream              43.2             18.5              192.0       4100.0   \n",
-       "9   Dream              40.2             20.1              200.0       3975.0   \n",
-       "10  Dream              40.8             18.9              208.0       4300.0   \n",
-       "11  Dream              39.0             18.7              185.0       3650.0   \n",
-       "12  Dream              37.0             16.9              185.0       3000.0   \n",
-       "14  Dream              34.0             17.1              185.0       3400.0   \n",
-       "15  Dream              37.0             16.5              185.0       3400.0   \n",
-       "18  Dream              39.7             17.9              193.0       4250.0   \n",
-       "19  Dream              37.8             18.1              193.0       3750.0   \n",
-       "22  Dream              40.2             17.1              193.0       3400.0   \n",
-       "23  Dream              36.8             18.5              193.0       3500.0   \n",
-       "26  Dream              41.5             18.5              201.0       4000.0   \n",
-       "31  Dream              33.1             16.1              178.0       2900.0   \n",
-       "32  Dream              37.2             18.1              178.0       3900.0   \n",
-       "33  Dream              39.5             16.7              178.0       3250.0   \n",
-       "35  Dream              36.0             18.5              186.0       3100.0   \n",
-       "36  Dream              39.6             18.1              186.0       4450.0   \n",
-       "38  Dream              41.3             20.3              194.0       3550.0   \n",
-       "41  Dream              35.7             18.0              202.0       3550.0   \n",
-       "51  Dream              38.1             17.6              187.0       3425.0   \n",
-       "53  Dream              36.0             17.1              187.0       3700.0   \n",
+       "       island  culmen_length_mm  culmen_depth_mm  flipper_length_mm  \\\n",
+       "0      Biscoe              40.1             18.9              188.0   \n",
+       "1   Torgersen              39.1             18.7              181.0   \n",
+       "4      Biscoe              43.2             19.0              197.0   \n",
+       "6      Biscoe              41.3             21.1              195.0   \n",
+       "11      Dream              38.1             18.6              190.0   \n",
+       "13     Biscoe              37.8             20.0              190.0   \n",
+       "14     Biscoe              35.0             17.9              190.0   \n",
+       "16  Torgersen              34.6             21.1              198.0   \n",
+       "19      Dream              37.2             18.1              178.0   \n",
+       "21     Biscoe              40.5             17.9              187.0   \n",
+       "23      Dream              42.2             18.5              180.0   \n",
+       "30      Dream              39.2             21.1              196.0   \n",
+       "32  Torgersen              42.9             17.6              196.0   \n",
+       "38      Dream              41.1             17.5              190.0   \n",
+       "40  Torgersen              38.6             21.2              191.0   \n",
+       "42     Biscoe              35.5             16.2              195.0   \n",
+       "44      Dream              39.2             18.6              190.0   \n",
+       "45  Torgersen              35.2             15.9              186.0   \n",
+       "46      Dream              43.2             18.5              192.0   \n",
+       "49     Biscoe              39.6             17.7              186.0   \n",
+       "53     Biscoe              45.6             20.3              191.0   \n",
+       "58  Torgersen              40.9             16.8              191.0   \n",
+       "60  Torgersen              40.3             18.0              195.0   \n",
+       "62      Dream              36.0             18.5              186.0   \n",
+       "63  Torgersen              39.3             20.6              190.0   \n",
        "\n",
-       "       sex  \n",
-       "0   FEMALE  \n",
-       "1     MALE  \n",
-       "2     MALE  \n",
-       "4   FEMALE  \n",
-       "5     MALE  \n",
-       "9     MALE  \n",
-       "10    MALE  \n",
-       "11    MALE  \n",
-       "12  FEMALE  \n",
-       "14  FEMALE  \n",
-       "15  FEMALE  \n",
-       "18    MALE  \n",
-       "19    MALE  \n",
-       "22  FEMALE  \n",
-       "23  FEMALE  \n",
-       "26    MALE  \n",
-       "31  FEMALE  \n",
-       "32    MALE  \n",
-       "33  FEMALE  \n",
-       "35  FEMALE  \n",
-       "36    MALE  \n",
-       "38    MALE  \n",
-       "41  FEMALE  \n",
-       "51  FEMALE  \n",
-       "53  FEMALE  \n",
+       "    body_mass_g     sex  \n",
+       "0        4300.0    MALE  \n",
+       "1        3750.0    MALE  \n",
+       "4        4775.0    MALE  \n",
+       "6        4400.0    MALE  \n",
+       "11       3700.0  FEMALE  \n",
+       "13       4250.0    MALE  \n",
+       "14       3450.0  FEMALE  \n",
+       "16       4400.0    MALE  \n",
+       "19       3900.0    MALE  \n",
+       "21       3200.0  FEMALE  \n",
+       "23       3550.0  FEMALE  \n",
+       "30       4150.0    MALE  \n",
+       "32       4700.0    MALE  \n",
+       "38       3900.0    MALE  \n",
+       "40       3800.0    MALE  \n",
+       "42       3350.0  FEMALE  \n",
+       "44       4250.0    MALE  \n",
+       "45       3050.0  FEMALE  \n",
+       "46       4100.0    MALE  \n",
+       "49       3500.0  FEMALE  \n",
+       "53       4600.0    MALE  \n",
+       "58       3700.0  FEMALE  \n",
+       "60       3250.0  FEMALE  \n",
+       "62       3100.0  FEMALE  \n",
+       "63       3650.0    MALE  \n",
        "...\n",
        "\n",
        "[146 rows x 6 columns]"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -843,18 +793,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "81f9aa34c7234bd88b6b7a4bc77d4b4e",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 0808457b-a0df-4a37-b7a5-8885f4a4588c is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:0808457b-a0df-4a37-b7a5-8885f4a4588c&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 288f0daa-a51e-45b4-86bf-d054467c4a99 is DONE. 28.9 kB processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -881,7 +829,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -897,7 +845,7 @@
        "                ('linreg', LinearRegression(fit_intercept=False))])"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -936,9 +884,63 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "Query job e9bfa6a5-a53f-4d8b-ae8c-cc8cd55d0947 is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:e9bfa6a5-a53f-4d8b-ae8c-cc8cd55d0947&page=queryresults\">Open Job</a>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Query job d8d553cf-3d36-49aa-b18b-9a05576a1fb0 is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:d8d553cf-3d36-49aa-b18b-9a05576a1fb0&page=queryresults\">Open Job</a>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Query job 75ef0083-9a4f-4ffb-a6c6-d82974a1659f is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:75ef0083-9a4f-4ffb-a6c6-d82974a1659f&page=queryresults\">Open Job</a>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Pipeline(steps=[('preproc',\n",
+       "                 ColumnTransformer(transformers=[('onehot', OneHotEncoder(),\n",
+       "                                                  ['island', 'species', 'sex']),\n",
+       "                                                 ('scaler', StandardScaler(),\n",
+       "                                                  ['culmen_depth_mm',\n",
+       "                                                   'culmen_length_mm',\n",
+       "                                                   'flipper_length_mm'])])),\n",
+       "                ('linreg', LinearRegression(fit_intercept=False))])"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "pipeline.fit(X_train, y_train)"
    ]
@@ -953,18 +955,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "fcf406d36c0d4915b318cd30c0f3df25",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 55c5a9ce-8159-4a1a-99a4-af3a906640ba is DONE. 29.3 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:55c5a9ce-8159-4a1a-99a4-af3a906640ba&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 81196f97-304b-4d77-bb0f-8fc8adb8fe75 is RUNNING. <a target=\"_blank\" href=\"https://consol…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -972,13 +972,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "41399a6b1d4f45328bacc6c868cefdf6",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 3e41c470-de70-4f13-89d9-c5564d0b2836 is DONE. 232 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:3e41c470-de70-4f13-89d9-c5564d0b2836&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job b417f27a-387d-4eb2-8d6d-287327ef0471 is DONE. 232 Bytes processed. <a target=\"_blank\" hr…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -986,13 +984,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e3c17676eab448c0942c0c32689ba4b5",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job ed2f9042-a737-4d13-bd21-8c3d29cd61a2 is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:ed2f9042-a737-4d13-bd21-8c3d29cd61a2&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job b7f89a61-d76a-47be-8b83-917d69f255a2 is DONE. 31.7 kB processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1000,13 +996,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "6c903861564b412aad9d9decad26560c",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 815d16b5-0a5d-42be-a766-1cff5b8f22f2 is DONE. 28.9 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:815d16b5-0a5d-42be-a766-1cff5b8f22f2&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 9619c393-90b3-4fea-a197-d09389e9486c is DONE. 31.7 kB processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1014,13 +1008,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2c2534cd90e64c81be45753b81b1be46",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 37a38dc6-5073-4544-a1e3-da145a843922 is DONE. 29.4 kB processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:37a38dc6-5073-4544-a1e3-da145a843922&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job e5854451-ffb4-4a28-a25f-3bdd68e9edae is DONE. 32.2 kB processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1029,10 +1021,10 @@
     {
      "data": {
       "text/plain": [
-       "0.6757452736197735"
+       "0.2655729213572775"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1040,9 +1032,9 @@
    "source": [
     "from bigframes.ml.metrics import r2_score\n",
     "\n",
-    "pred_y = pipeline.predict(X_test)\n",
+    "y_pred = pipeline.predict(X_test)[\"predicted_body_mass_g\"]\n",
     "\n",
-    "r2_score(y_test, pred_y)"
+    "r2_score(y_test, y_pred)"
    ]
   },
   {
@@ -1055,18 +1047,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9295d6a3ff834f7a91a43d3f4ef4a61c",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Load job 7b46750c-70b4-468d-87ba-9f84f579f2a6 is DONE. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:7b46750c-70b4-468d-87ba-9f84f579f2a6&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Load job d4c2f933-3514-4901-bcd7-888ee66eba82 is RUNNING. <a target=\"_blank\" href=\"https://console…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1097,32 +1087,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b7eb82b3b5fc4a8e97468070a3e76300",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "HTML(value='Query job e4ffd919-6f69-4382-a7e5-db37c7c1fefa is RUNNING. <a target=\"_blank\" href=\"https://consol…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f14acf6da0cf4752a0d9c6086abc783f",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job d10dd37d-5e8e-4e15-9c83-a7e9a4c592a8 is DONE. 593 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:d10dd37d-5e8e-4e15-9c83-a7e9a4c592a8&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 6b3e3285-79e9-4137-bf3b-7b7185ef76a5 is DONE. 24 Bytes processed. <a target=\"_blank\" hre…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1130,13 +1104,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "edc7bc6434bd4be4926626a235aab65a",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 207cb787-cf8a-43ea-8e73-644d3f58b11a is DONE. 24 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:207cb787-cf8a-43ea-8e73-644d3f58b11a&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 173c4194-e194-43d2-8359-7bec83d3c861 is DONE. 0 Bytes processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1144,13 +1116,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "55a8cbd9b1ab47eeab6e1c305847630f",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job c5dc5075-cac0-4947-9e9f-06aa9cc5bd2a is DONE. 0 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:c5dc5075-cac0-4947-9e9f-06aa9cc5bd2a&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 53ba2332-590c-488d-9505-23aebaaad9cb is DONE. 48 Bytes processed. <a target=\"_blank\" hre…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1158,13 +1128,11 @@
     },
     {
      "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "463a5b072148474db629b9346fa3a6d1",
-       "version_major": 2,
-       "version_minor": 0
-      },
+      "text/html": [
+       "Query job 2ca4a569-7186-48ed-b3e4-004dca704798 is DONE. 282 Bytes processed. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:2ca4a569-7186-48ed-b3e4-004dca704798&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "HTML(value='Query job 66e4a8e0-4cae-4e9d-86e0-17dc24f6cfbb is DONE. 0 Bytes processed. <a target=\"_blank\" href…"
+       "<IPython.core.display.HTML object>"
       ]
      },
      "metadata": {},
@@ -1192,41 +1160,83 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>predicted_body_mass_g</th>\n",
+       "      <th>species</th>\n",
+       "      <th>island</th>\n",
+       "      <th>culmen_length_mm</th>\n",
+       "      <th>culmen_depth_mm</th>\n",
+       "      <th>flipper_length_mm</th>\n",
+       "      <th>sex</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>tag_number</th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1633</th>\n",
-       "      <td>3965.994361</td>\n",
+       "      <td>4017.203152</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>39.5</td>\n",
+       "      <td>18.8</td>\n",
+       "      <td>196.0</td>\n",
+       "      <td>MALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1672</th>\n",
-       "      <td>3246.312058</td>\n",
+       "      <td>3127.601519</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Torgersen</td>\n",
+       "      <td>38.5</td>\n",
+       "      <td>17.2</td>\n",
+       "      <td>181.0</td>\n",
+       "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1690</th>\n",
-       "      <td>3456.404062</td>\n",
+       "      <td>3386.101231</td>\n",
+       "      <td>Adelie Penguin (Pygoscelis adeliae)</td>\n",
+       "      <td>Dream</td>\n",
+       "      <td>37.9</td>\n",
+       "      <td>18.1</td>\n",
+       "      <td>188.0</td>\n",
+       "      <td>FEMALE</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>3 rows × 1 columns</p>\n",
-       "</div>[3 rows x 1 columns in total]"
+       "<p>3 rows × 7 columns</p>\n",
+       "</div>[3 rows x 7 columns in total]"
       ],
       "text/plain": [
-       "            predicted_body_mass_g\n",
-       "tag_number                       \n",
-       "1633                  3965.994361\n",
-       "1672                  3246.312058\n",
-       "1690                  3456.404062\n",
+       "            predicted_body_mass_g                              species  \\\n",
+       "tag_number                                                               \n",
+       "1633                  4017.203152  Adelie Penguin (Pygoscelis adeliae)   \n",
+       "1672                  3127.601519  Adelie Penguin (Pygoscelis adeliae)   \n",
+       "1690                  3386.101231  Adelie Penguin (Pygoscelis adeliae)   \n",
+       "\n",
+       "               island  culmen_length_mm  culmen_depth_mm  flipper_length_mm  \\\n",
+       "tag_number                                                                    \n",
+       "1633        Torgersen              39.5             18.8              196.0   \n",
+       "1672        Torgersen              38.5             17.2              181.0   \n",
+       "1690            Dream              37.9             18.1              188.0   \n",
        "\n",
-       "[3 rows x 1 columns]"
+       "               sex  \n",
+       "tag_number          \n",
+       "1633          MALE  \n",
+       "1672        FEMALE  \n",
+       "1690        FEMALE  \n",
+       "\n",
+       "[3 rows x 7 columns]"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1240,28 +1250,53 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 4. Save in BigQuery"
+    "## 6. Save in BigQuery"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "text/html": [
+       "Copy job d1def4a4-1da1-43a9-8ae5-4459444d993d is DONE. <a target=\"_blank\" href=\"https://console.cloud.google.com/bigquery?project=bigframes-dev&j=bq:US:d1def4a4-1da1-43a9-8ae5-4459444d993d&page=queryresults\">Open Job</a>"
+      ],
       "text/plain": [
-       "Pipeline(steps=[('preproc',\n",
-       "                 ColumnTransformer(transformers=[('onehot', OneHotEncoder(),\n",
-       "                                                  ['island', 'species', 'sex']),\n",
-       "                                                 ('scaler', StandardScaler(),\n",
-       "                                                  ['culmen_depth_mm',\n",
-       "                                                   'culmen_length_mm',\n",
-       "                                                   'flipper_length_mm'])])),\n",
-       "                ('linreg', LinearRegression(fit_intercept=False))])"
+       "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 20,
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Pipeline(steps=[('transform',\n",
+       "                 ColumnTransformer(transformers=[('ont_hot_encoder',\n",
+       "                                                  OneHotEncoder(max_categories=1000001,\n",
+       "                                                                min_frequency=0),\n",
+       "                                                  'island'),\n",
+       "                                                 ('standard_scaler',\n",
+       "                                                  StandardScaler(),\n",
+       "                                                  'culmen_length_mm'),\n",
+       "                                                 ('standard_scaler',\n",
+       "                                                  StandardScaler(),\n",
+       "                                                  'culmen_depth_mm'),\n",
+       "                                                 ('standard_scaler',\n",
+       "                                                  StandardScaler(),\n",
+       "                                                  'flipper_length_mm'),\n",
+       "                                                 ('ont_hot_encoder',\n",
+       "                                                  OneHotEncoder(max_categories=1000001,\n",
+       "                                                                min_frequency=0),\n",
+       "                                                  'sex')])),\n",
+       "                ('estimator',\n",
+       "                 LinearRegression(fit_intercept=False,\n",
+       "                                  optimize_strategy='NORMAL_EQUATION'))])"
+      ]
+     },
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1269,6 +1304,13 @@
    "source": [
     "pipeline.to_gbq(\"bigframes-dev.bigframes_demo_us.penguin_model\", replace=True)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -1287,7 +1329,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.10.9"
   },
   "orig_nbformat": 4,
   "vscode": {
diff --git a/tests/system/large/ml/test_cluster.py b/tests/system/large/ml/test_cluster.py
index f01116665f..9244c4b9f1 100644
--- a/tests/system/large/ml/test_cluster.py
+++ b/tests/system/large/ml/test_cluster.py
@@ -98,7 +98,9 @@ def test_cluster_configure_fit_score_predict(
         score_result, score_expected, check_exact=False, rtol=0.1
     )
 
-    result = model.predict(new_penguins).to_pandas()
+    predictions = model.predict(new_penguins).to_pandas()
+    assert predictions.shape == (4, 9)
+    result = predictions[["CENTROID_ID"]]
     expected = pd.DataFrame(
         {"CENTROID_ID": [2, 3, 1, 2]},
         dtype="Int64",
diff --git a/tests/system/large/ml/test_ensemble.py b/tests/system/large/ml/test_ensemble.py
index a8613dfeb9..b98d7a757c 100644
--- a/tests/system/large/ml/test_ensemble.py
+++ b/tests/system/large/ml/test_ensemble.py
@@ -179,7 +179,7 @@ def test_xgbclassifier_default_params(penguins_df_default_index, dataset_id):
     )
 
 
-@pytest.mark.flaky(retries=2, delay=120)
+# @pytest.mark.flaky(retries=2, delay=120)
 def test_xgbclassifier_dart_booster_multiple_params(
     penguins_df_default_index, dataset_id
 ):
diff --git a/tests/system/large/ml/test_pipeline.py b/tests/system/large/ml/test_pipeline.py
index 3e56954058..2929baf3f7 100644
--- a/tests/system/large/ml/test_pipeline.py
+++ b/tests/system/large/ml/test_pipeline.py
@@ -545,7 +545,9 @@ def test_pipeline_standard_scaler_kmeans_fit_score_predict(
         score_result, score_expected, check_exact=False, rtol=0.1
     )
 
-    result = pl.predict(new_penguins).to_pandas().sort_index()
+    predictions = pl.predict(new_penguins).to_pandas().sort_index()
+    assert predictions.shape == (6, 9)
+    result = predictions[["CENTROID_ID"]]
     expected = pd.DataFrame(
         {"CENTROID_ID": [1, 2, 1, 2, 1, 2]},
         dtype="Int64",
diff --git a/tests/system/small/ml/test_cluster.py b/tests/system/small/ml/test_cluster.py
index 266a38e3ee..a9fec0bbce 100644
--- a/tests/system/small/ml/test_cluster.py
+++ b/tests/system/small/ml/test_cluster.py
@@ -62,7 +62,9 @@
 
 def test_kmeans_predict(session, penguins_kmeans_model: cluster.KMeans):
     new_penguins = session.read_pandas(_PD_NEW_PENGUINS)
-    result = penguins_kmeans_model.predict(new_penguins).to_pandas()
+    predictions = penguins_kmeans_model.predict(new_penguins).to_pandas()
+    assert predictions.shape == (4, 9)
+    result = predictions[["CENTROID_ID"]]
     expected = pd.DataFrame(
         {"CENTROID_ID": [2, 3, 1, 2]},
         dtype="Int64",
diff --git a/tests/system/small/ml/test_ensemble.py b/tests/system/small/ml/test_ensemble.py
index bba083d98d..55d9fef661 100644
--- a/tests/system/small/ml/test_ensemble.py
+++ b/tests/system/small/ml/test_ensemble.py
@@ -98,7 +98,9 @@ def test_xgbregressor_model_score_series(
 def test_xgbregressor_model_predict(
     penguins_xgbregressor_model: bigframes.ml.ensemble.XGBRegressor, new_penguins_df
 ):
-    result = penguins_xgbregressor_model.predict(new_penguins_df).to_pandas()
+    predictions = penguins_xgbregressor_model.predict(new_penguins_df).to_pandas()
+    assert predictions.shape == (3, 8)
+    result = predictions[["predicted_body_mass_g"]]
     expected = pandas.DataFrame(
         {"predicted_body_mass_g": ["4293.1538089", "3410.0271", "3357.944"]},
         dtype="Float64",
@@ -220,7 +222,9 @@ def test_xgbclassifier_model_score_series(
 def test_xgbclassifier_model_predict(
     penguins_xgbclassifier_model: bigframes.ml.ensemble.XGBClassifier, new_penguins_df
 ):
-    result = penguins_xgbclassifier_model.predict(new_penguins_df).to_pandas()
+    predictions = penguins_xgbclassifier_model.predict(new_penguins_df).to_pandas()
+    assert predictions.shape == (3, 9)
+    result = predictions[["predicted_sex"]]
     expected = pandas.DataFrame(
         {"predicted_sex": ["MALE", "MALE", "FEMALE"]},
         dtype="string[pyarrow]",
@@ -363,7 +367,11 @@ def test_randomforestregressor_model_predict(
     penguins_randomforest_regressor_model: bigframes.ml.ensemble.RandomForestRegressor,
     new_penguins_df,
 ):
-    result = penguins_randomforest_regressor_model.predict(new_penguins_df).to_pandas()
+    predictions = penguins_randomforest_regressor_model.predict(
+        new_penguins_df
+    ).to_pandas()
+    assert predictions.shape == (3, 8)
+    result = predictions[["predicted_body_mass_g"]]
     expected = pandas.DataFrame(
         {"predicted_body_mass_g": ["3897.341797", "3458.385742", "3458.385742"]},
         dtype="Float64",
@@ -490,7 +498,11 @@ def test_randomforestclassifier_model_predict(
     penguins_randomforest_classifier_model: bigframes.ml.ensemble.RandomForestClassifier,
     new_penguins_df,
 ):
-    result = penguins_randomforest_classifier_model.predict(new_penguins_df).to_pandas()
+    predictions = penguins_randomforest_classifier_model.predict(
+        new_penguins_df
+    ).to_pandas()
+    assert predictions.shape == (3, 9)
+    result = predictions[["predicted_sex"]]
     expected = pandas.DataFrame(
         {"predicted_sex": ["MALE", "MALE", "FEMALE"]},
         dtype="string[pyarrow]",
diff --git a/tests/system/small/ml/test_forecasting.py b/tests/system/small/ml/test_forecasting.py
index 55079c94cf..948db59650 100644
--- a/tests/system/small/ml/test_forecasting.py
+++ b/tests/system/small/ml/test_forecasting.py
@@ -22,6 +22,8 @@
 def test_model_predict(time_series_arima_plus_model):
     utc = pytz.utc
     predictions = time_series_arima_plus_model.predict().to_pandas()
+    assert predictions.shape == (3, 8)
+    result = predictions[["forecast_timestamp", "forecast_value"]]
     expected = pd.DataFrame(
         {
             "forecast_timestamp": [
@@ -38,7 +40,7 @@ def test_model_predict(time_series_arima_plus_model):
     )
 
     pd.testing.assert_frame_equal(
-        predictions,
+        result,
         expected,
         rtol=0.1,
         check_index_type=False,
diff --git a/tests/system/small/ml/test_imported.py b/tests/system/small/ml/test_imported.py
index d305567066..9008e85a0b 100644
--- a/tests/system/small/ml/test_imported.py
+++ b/tests/system/small/ml/test_imported.py
@@ -32,7 +32,9 @@ def test_tensorflow_create_model_default_session(imported_tensorflow_model_path)
 
 def test_tensorflow_model_predict(imported_tensorflow_model, llm_text_df):
     df = llm_text_df.rename(columns={"prompt": "input"})
-    result = imported_tensorflow_model.predict(df).to_pandas()
+    predictions = imported_tensorflow_model.predict(df).to_pandas()
+    assert predictions.shape == (3, 2)
+    result = predictions[["dense_1"]]
     # The values are non-human-readable. As they are a dense layer of Neural Network.
     # And since it is pretrained and imported, the model is a opaque-box.
     # We may want to switch to better test model and cases.
@@ -72,7 +74,9 @@ def test_onnx_create_model_default_session(imported_onnx_model_path):
 
 
 def test_onnx_model_predict(imported_onnx_model, onnx_iris_df):
-    result = imported_onnx_model.predict(onnx_iris_df).to_pandas()
+    predictions = imported_onnx_model.predict(onnx_iris_df).to_pandas()
+    assert predictions.shape == (3, 7)
+    result = predictions[["label", "probabilities"]]
     value1 = np.array([0.9999993443489075, 0.0, 0.0])
     value2 = np.array([0.0, 0.0, 0.9999993443489075])
     expected = pd.DataFrame(
diff --git a/tests/system/small/ml/test_linear_model.py b/tests/system/small/ml/test_linear_model.py
index 3a8232ed9e..218c1074ab 100644
--- a/tests/system/small/ml/test_linear_model.py
+++ b/tests/system/small/ml/test_linear_model.py
@@ -91,13 +91,15 @@ def test_linear_reg_model_score_series(
 
 def test_linear_reg_model_predict(penguins_linear_model, new_penguins_df):
     predictions = penguins_linear_model.predict(new_penguins_df).to_pandas()
+    assert predictions.shape == (3, 8)
+    result = predictions[["predicted_body_mass_g"]]
     expected = pandas.DataFrame(
         {"predicted_body_mass_g": [4030.1, 3280.8, 3177.9]},
         dtype="Float64",
         index=pandas.Index([1633, 1672, 1690], name="tag_number", dtype="Int64"),
     )
     pandas.testing.assert_frame_equal(
-        predictions.sort_index(),
+        result.sort_index(),
         expected,
         check_exact=False,
         rtol=0.1,
@@ -224,13 +226,15 @@ def test_logistic_model_score_series(
 
 def test_logsitic_model_predict(penguins_logistic_model, new_penguins_df):
     predictions = penguins_logistic_model.predict(new_penguins_df).to_pandas()
+    assert predictions.shape == (3, 9)
+    result = predictions[["predicted_sex"]]
     expected = pandas.DataFrame(
         {"predicted_sex": ["MALE", "MALE", "FEMALE"]},
         dtype="string[pyarrow]",
         index=pandas.Index([1633, 1672, 1690], name="tag_number", dtype="Int64"),
     )
     pandas.testing.assert_frame_equal(
-        predictions.sort_index(),
+        result.sort_index(),
         expected,
         check_exact=False,
         rtol=0.1,
diff --git a/tests/system/small/ml/test_llm.py b/tests/system/small/ml/test_llm.py
index 79d3c40317..306098548e 100644
--- a/tests/system/small/ml/test_llm.py
+++ b/tests/system/small/ml/test_llm.py
@@ -12,8 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from unittest import TestCase
-
 import numpy as np
 import pytest
 
@@ -48,7 +46,7 @@ def test_create_text_generator_model_default_session(bq_connection, llm_text_pan
     llm_text_df = bpd.read_pandas(llm_text_pandas_df)
 
     df = model.predict(llm_text_df).to_pandas()
-    TestCase().assertSequenceEqual(df.shape, (3, 1))
+    assert df.shape == (3, 4)
     assert "ml_generate_text_llm_result" in df.columns
     series = df["ml_generate_text_llm_result"]
     assert all(series.str.len() > 20)
@@ -72,7 +70,7 @@ def test_create_text_generator_32k_model_default_session(
     llm_text_df = bpd.read_pandas(llm_text_pandas_df)
 
     df = model.predict(llm_text_df).to_pandas()
-    TestCase().assertSequenceEqual(df.shape, (3, 1))
+    assert df.shape == (3, 4)
     assert "ml_generate_text_llm_result" in df.columns
     series = df["ml_generate_text_llm_result"]
     assert all(series.str.len() > 20)
@@ -97,7 +95,7 @@ def test_create_text_generator_model_default_connection(llm_text_pandas_df):
     )
 
     df = model.predict(llm_text_df).to_pandas()
-    TestCase().assertSequenceEqual(df.shape, (3, 1))
+    assert df.shape == (3, 4)
     assert "ml_generate_text_llm_result" in df.columns
     series = df["ml_generate_text_llm_result"]
     assert all(series.str.len() > 20)
@@ -109,7 +107,7 @@ def test_text_generator_predict_default_params_success(
     palm2_text_generator_model, llm_text_df
 ):
     df = palm2_text_generator_model.predict(llm_text_df).to_pandas()
-    TestCase().assertSequenceEqual(df.shape, (3, 1))
+    assert df.shape == (3, 4)
     assert "ml_generate_text_llm_result" in df.columns
     series = df["ml_generate_text_llm_result"]
     assert all(series.str.len() > 20)
@@ -120,7 +118,7 @@ def test_text_generator_predict_series_default_params_success(
     palm2_text_generator_model, llm_text_df
 ):
     df = palm2_text_generator_model.predict(llm_text_df["prompt"]).to_pandas()
-    TestCase().assertSequenceEqual(df.shape, (3, 1))
+    assert df.shape == (3, 4)
     assert "ml_generate_text_llm_result" in df.columns
     series = df["ml_generate_text_llm_result"]
     assert all(series.str.len() > 20)
@@ -132,7 +130,7 @@ def test_text_generator_predict_arbitrary_col_label_success(
 ):
     llm_text_df = llm_text_df.rename(columns={"prompt": "arbitrary"})
     df = palm2_text_generator_model.predict(llm_text_df).to_pandas()
-    TestCase().assertSequenceEqual(df.shape, (3, 1))
+    assert df.shape == (3, 4)
     assert "ml_generate_text_llm_result" in df.columns
     series = df["ml_generate_text_llm_result"]
     assert all(series.str.len() > 20)
@@ -145,7 +143,7 @@ def test_text_generator_predict_with_params_success(
     df = palm2_text_generator_model.predict(
         llm_text_df, temperature=0.5, max_output_tokens=100, top_k=20, top_p=0.5
     ).to_pandas()
-    TestCase().assertSequenceEqual(df.shape, (3, 1))
+    assert df.shape == (3, 4)
     assert "ml_generate_text_llm_result" in df.columns
     series = df["ml_generate_text_llm_result"]
     assert all(series.str.len() > 20)
@@ -196,7 +194,7 @@ def test_embedding_generator_predict_success(
     palm2_embedding_generator_model, llm_text_df
 ):
     df = palm2_embedding_generator_model.predict(llm_text_df).to_pandas()
-    TestCase().assertSequenceEqual(df.shape, (3, 1))
+    assert df.shape == (3, 4)
     assert "text_embedding" in df.columns
     series = df["text_embedding"]
     value = series[0]
@@ -209,7 +207,7 @@ def test_embedding_generator_multilingual_predict_success(
     palm2_embedding_generator_multilingual_model, llm_text_df
 ):
     df = palm2_embedding_generator_multilingual_model.predict(llm_text_df).to_pandas()
-    TestCase().assertSequenceEqual(df.shape, (3, 1))
+    assert df.shape == (3, 4)
     assert "text_embedding" in df.columns
     series = df["text_embedding"]
     value = series[0]
@@ -222,7 +220,7 @@ def test_embedding_generator_predict_series_success(
     palm2_embedding_generator_model, llm_text_df
 ):
     df = palm2_embedding_generator_model.predict(llm_text_df["prompt"]).to_pandas()
-    TestCase().assertSequenceEqual(df.shape, (3, 1))
+    assert df.shape == (3, 4)
     assert "text_embedding" in df.columns
     series = df["text_embedding"]
     value = series[0]
diff --git a/third_party/bigframes_vendored/sklearn/cluster/_kmeans.py b/third_party/bigframes_vendored/sklearn/cluster/_kmeans.py
index 5369d3662d..be6c5e7c52 100644
--- a/third_party/bigframes_vendored/sklearn/cluster/_kmeans.py
+++ b/third_party/bigframes_vendored/sklearn/cluster/_kmeans.py
@@ -20,19 +20,7 @@
 class _BaseKMeans(BaseEstimator, ABC):
     """Base class for KMeans and MiniBatchKMeans"""
 
-    def predict(self, X):
-        """Predict the closest cluster each sample in X belongs to.
-
-        Args:
-            X (bigframes.dataframe.DataFrame or bigframes.series.Series):
-                Series or DataFrame of shape (n_samples, n_features). The data matrix for
-                which we want to get the predictions.
-
-        Returns:
-            bigframes.dataframe.DataFrame: DataFrame of shape (n_samples,), containing the
-                class labels for each sample.
-        """
-        raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
+    pass
 
 
 class KMeans(_BaseKMeans):
@@ -73,7 +61,7 @@ def predict(
                 DataFrame of shape (n_samples, n_features). New data to predict.
 
         Returns:
-            bigframes.dataframe.DataFrame: DataFrame of the cluster each sample belongs to.
+            bigframes.dataframe.DataFrame: DataFrame of shape (n_samples, n_input_columns + n_prediction_columns). Returns predicted labels.
         """
         raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
diff --git a/third_party/bigframes_vendored/sklearn/linear_model/_base.py b/third_party/bigframes_vendored/sklearn/linear_model/_base.py
index 8dc3b6280a..ab946e5861 100644
--- a/third_party/bigframes_vendored/sklearn/linear_model/_base.py
+++ b/third_party/bigframes_vendored/sklearn/linear_model/_base.py
@@ -16,7 +16,6 @@
 # Original location: https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/linear_model/_base.py
 
 from abc import ABCMeta
-from typing import List, Optional
 
 from bigframes import constants
 from third_party.bigframes_vendored.sklearn.base import (
@@ -35,7 +34,7 @@ def predict(self, X):
                 Series or DataFrame of shape (n_samples, n_features). Samples.
 
         Returns:
-            bigframes.dataframe.DataFrame: DataFrame of shape (n_samples,). Returns predicted values.
+            bigframes.dataframe.DataFrame: DataFrame of shape (n_samples, n_input_columns + n_prediction_columns). Returns predicted values.
         """
         raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
@@ -50,8 +49,7 @@ def predict(self, X):
                 which we want to get the predictions.
 
         Returns:
-            bigframes.dataframe.DataFrame:  DataFrame of shape (n_samples,), containing
-                the class labels for each sample.
+            bigframes.dataframe.DataFrame: DataFrame of shape (n_samples, n_input_columns + n_prediction_columns). Returns predicted values.
         """
         raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)
 
diff --git a/third_party/bigframes_vendored/xgboost/sklearn.py b/third_party/bigframes_vendored/xgboost/sklearn.py
index b7b43b85a3..dfd0ba7356 100644
--- a/third_party/bigframes_vendored/xgboost/sklearn.py
+++ b/third_party/bigframes_vendored/xgboost/sklearn.py
@@ -18,7 +18,7 @@ def predict(self, X):
                 Series or DataFrame of shape (n_samples, n_features). Samples.
 
         Returns:
-            DataFrame of shape (n_samples,): Returns predicted values.
+            bigframes.dataframe.DataFrame: DataFrame of shape (n_samples, n_input_columns + n_prediction_columns). Returns predicted values.
         """
         raise NotImplementedError(constants.ABSTRACT_METHOD_ERROR_MESSAGE)