code: def _test_dataframe(size=10000, seed=0):
      import pandas as pd
  
      np.random.seed(seed)
      df = pd.DataFrame(
          {
              "uint8": _random_integers(size, np.uint8),
              "uint16": _random_integers(size, np.uint16),
              "uint32": _random_integers(size, np.uint32),
              "uint64": _random_integers(size, np.uint64),
              "int8": _random_integers(size, np.int8),
              "int16": _random_integers(size, np.int16),
              "int32": _random_integers(size, np.int32),
              "int64": _random_integers(size, np.int64),
              "float32": np.random.randn(size).astype(np.float32),
              "float64": np.arange(size, dtype=np.float64),
              "bool": np.random.randn(size) > 0,
              "strings": [util.rands(10) for i in range(size)],
              "all_none": [None] * size,
              "all_none_category": [None] * size,
          }
      )
  
      # TODO(PARQUET-1015)
      # df['all_none_category'] = df['all_none_category'].astype('category')
      return df
  
file_path: arrow/python/pyarrow/tests/parquet/common.py
imports: import io
  import numpy
  import pyarrow
  from pyarrow.tests import util
label_desc: Use image node_id 8 for calling a global function with example usage: _test_dataframe(size, seed) and returns: df