way to try with no key

blogs/pandas-pvtkey/nokey_query.py

@@ -0,0 +1,24 @@
+#!/usr/bin/env python
+
+def query_to_dataframe(query):
+  import pandas as pd
+  return pd.read_gbq(query,
+                     project_id='cloud-training-demos',
+                     dialect='standard',
+                     verbose=False)
+
+query = """
+SELECT
+  year,
+  COUNT(1) as num_babies
+FROM
+  publicdata.samples.natality
+WHERE
+  year > 2000
+GROUP BY
+  year
+"""
+
+df = query_to_dataframe(query)
+print(df.head())
+

blogs/sklearn/babyweight_skl.ipynb

@@ -1031,7 +1031,30 @@
     "deletable": true,
     "editable": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "jobId: babyweight_skl_20180526_184047\n",
+      "state: QUEUED\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Job [babyweight_skl_20180526_184047] submitted successfully.\n",
+      "Your job is still active. You may view the status of your job with the command\n",
+      "\n",
+      "  $ gcloud ml-engine jobs describe babyweight_skl_20180526_184047\n",
+      "\n",
+      "or continue streaming the logs with the command\n",
+      "\n",
+      "  $ gcloud ml-engine jobs stream-logs babyweight_skl_20180526_184047\n"
+     ]
+    }
+   ],
    "source": [
     "%bash\n",
     "\n",
@@ -1048,7 +1071,7 @@
     "  --runtime-version=$RUNTIME_VERSION \\\n",
     "  --python-version=$PYTHON_VERSION \\\n",
     "  -- \\\n",
-    "  --bucket=${BUCKET} --frac=1.0 --projectId $PROJECT"
+    "  --bucket=${BUCKET} --frac=0.1 --projectId $PROJECT"
    ]
   },
   {