code: def test_parquet_is_in_statistics(
      monkeypatch: Any, capfd: Any, tmp_path: Path
  ) -> None:
      tmp_path.mkdir(exist_ok=True)
  
      monkeypatch.setenv("POLARS_VERBOSE", "1")
  
      df = pl.DataFrame(
          {"idx": pl.arange(0, 100, eager=True)}
      ).with_columns((pl.col("idx") // 25).alias("part"))
      df = pl.concat(
          df.partition_by("part", as_dict=False), rechunk=False
      )
      assert df.n_chunks("all") == [4, 4]
  
      file_path = tmp_path / "stats.parquet"
      df.write_parquet(file_path, statistics=True, use_pyarrow=False)
  
      file_path = tmp_path / "stats.parquet"
      df.write_parquet(file_path, statistics=True, use_pyarrow=False)
  
      for pred in [
          pl.col("idx").is_in([150, 200, 300]),
          pl.col("idx").is_in([5, 250, 350]),
      ]:
          result = pl.scan_parquet(file_path).filter(pred).collect()
          assert_frame_equal(result, df.filter(pred))
  
      captured = capfd.readouterr().err
      assert (
          "parquet file must be read, statistics not sufficient for predicate."
          in captured
      )
      assert (
          "parquet file can be skipped, the statistics were sufficient"
          " to apply the predicate." in captured
      )
  
imports: from __future__ import annotations
  from collections import OrderedDict
  from pathlib import Path
  from typing import TYPE_CHECKING, Any
  import pandas
  import pytest
  import polars
  from polars.testing import assert_frame_equal
label_desc: Use image node_id 12 for calling a global function with example usage: test_parquet_is_in_statistics(monkeypatch, capfd, tmp_path) without return types