chore: import upstream snapshot with attribution

docs/snippets/all/concepts/query-and-transform/dataframe_query_example.py

@@ -0,0 +1,51 @@
+"""Query and display the first 10 rows of a recording."""
+
+import atexit
+import math
+import os
+import tempfile
+
+from datafusion import col
+
+import rerun as rr
+
+# should be a cross-platform way to generate a rrd path.
+RRD_PATH = tempfile.mktemp(suffix=".rrd")
+atexit.register(
+    lambda: os.unlink(RRD_PATH) if os.path.exists(RRD_PATH) else None
+)
+
+# region: setup
+# create some data
+times = list(range(64))
+scalars = [math.sin(t / 10.0) for t in times]
+
+# log the data to a temporary recording
+with rr.RecordingStream("rerun_example_dataframe_query") as rec:
+    rec.save(RRD_PATH)
+    rec.send_columns(
+        "/data",
+        indexes=[rr.TimeColumn("step", sequence=times)],
+        columns=rr.Scalars.columns(scalars=scalars),
+    )
+# endregion: setup
+
+
+# region: query
+# load the demo recording in a temporary catalog
+with rr.server.Server(datasets={"dataset": [RRD_PATH]}) as server:
+    # obtain a dataset from the catalog
+    dataset = server.client().get_dataset("dataset")
+
+    # (optional) filter interesting data
+    dataset_view = dataset.filter_contents("/data")
+
+    # obtain a DataFusion dataframe
+    df = dataset_view.reader(index="step")
+
+    # (optional) filter rows using DataFusion expressions
+    df = df.filter(col("/data:Scalars:scalars")[0] > 0.95)
+
+    # execute the query
+    print(df)  # or convert to Pandas, Polars, PyArrow, etc.
+# endregion: query