fix sample

Author: tswast

samples/snippets/st_regionstats_test.py

@@ -0,0 +1,67 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+def test_st_regionstats():
+    project_id = "bigframes-dev"
+
+    # [START bigquery_dataframes_st_regionstats]
+    from typing import cast
+
+    import bigframes.bigquery as bq
+    import bigframes.pandas as bpd
+
+    # TODO: Set the project_id to your Google Cloud project ID.
+    # project_id = "your-project-id"
+    #
+    # TODO: Set the dataset_id to the ID of the dataset that contains the
+    # `climate` table. This is likely a linked dataset to Earth Engine.
+    # See: https://cloud.google.com/bigquery/docs/link-earth-engine
+    linked_dataset = "era5_land_daily_aggregated"
+
+    # Load the table of country boundaries.
+    bpd.options.bigquery.project = project_id
+    countries = bpd.read_gbq("bigquery-public-data.overture_maps.division_area")
+
+    # Filter to just the countries.
+    countries = countries[countries["subtype"] == "country"].copy()
+    countries["name"] = countries["names"].struct.field("primary")
+
+    # TODO: Add st_simplify when it is available in BigFrames.
+    # https://github.com/googleapis/python-bigquery-dataframes/issues/1497
+    # countries["simplified_geometry"] = bq.st_simplify(countries["geometry"], 10000)
+    countries["simplified_geometry"] = countries["geometry"]
+
+    # Get the reference to the temperature data from a linked dataset.
+    # Note: This sample assumes you have a linked dataset to Earth Engine.
+    # See: https://cloud.google.com/bigquery/docs/link-earth-engine
+    image_href = bpd.read_gbq(f"{project_id}.{linked_dataset}.climate").where(
+        lambda df: df["start_datetime"] == "2025-01-01 00:00:00"
+    )
+    raster_id = image_href["assets"].struct.field("image").struct.field("href").item
+    stats = bq.st_regionstats(
+        countries["simplified_geometry"],
+        raster_id=cast(str, raster_id),
+        band="temperature_2m",
+    )
+
+    # Extract the mean and convert from Kelvin to Celsius.
+    countries["mean_temperature"] = stats.struct.field("mean") - 273.15
+
+    # Sort by the mean temperature to find the warmest countries.
+    result = countries[["name", "mean_temperature"]].sort_values(
+        "mean_temperature", ascending=False
+    )
+    print(result.head())
+    # [END bigquery_dataframes_st_regionstats]