code: def test_overflow_mean_partitioned_group_by_5194(
      dtype: pl.PolarsDataType,
  ) -> None:
      df = pl.DataFrame(
          [
              pl.Series("data", [10_00_00_00] * 100_000, dtype=dtype),
              pl.Series("group", [1, 2] * 50_000, dtype=dtype),
          ]
      )
      result = (
          df.group_by("group")
          .agg(pl.col("data").mean())
          .sort(by="group")
      )
      expected = {"group": [1, 2], "data": [10000000.0, 10000000.0]}
      assert result.to_dict(as_series=False) == expected
  
imports: from __future__ import annotations
  from collections import OrderedDict
  from datetime import datetime, timedelta
  from typing import Any
  import pytest
  import polars
  from polars.testing import assert_frame_equal, assert_series_equal
label_desc: Use image node_id 24 for calling a global function with example usage: test_overflow_mean_partitioned_group_by_5194(dtype) without return types