code: def to_arrow(self):
      data_buf_32 = np.array(self.base_data.memoryview()).view("int32")
      data_buf_128 = np.empty(len(data_buf_32) * 4, dtype="int32")
  
      # use striding to set the first 32 bits of each 128-bit chunk:
      data_buf_128[::4] = data_buf_32
      # use striding again to set the remaining bits of each 128-bit chunk:
      # 0 for non-negative values, -1 for negative values:
      data_buf_128[1::4] = np.piecewise(
          data_buf_32, [data_buf_32 < 0], [-1, 0]
      )
      data_buf_128[2::4] = np.piecewise(
          data_buf_32, [data_buf_32 < 0], [-1, 0]
      )
      data_buf_128[3::4] = np.piecewise(
          data_buf_32, [data_buf_32 < 0], [-1, 0]
      )
      data_buf = pa.py_buffer(data_buf_128)
      mask_buf = (
          self.base_mask
          if self.base_mask is None
          else pa.py_buffer(self.base_mask.memoryview())
      )
      return pa.Array.from_buffers(
          type=self.dtype.to_arrow(),
          offset=self._offset,
          length=self.size,
          buffers=[mask_buf, data_buf],
      )
  
imports: from __future__ import annotations
  import warnings
  from decimal import Decimal
  from typing import Any, Optional, Sequence, Union, cast
  import cupy
  import numpy
  import pyarrow
  from typing_extensions import Self
  import cudf
  from cudf import _lib
  from cudf._lib.strings.convert.convert_fixed_point import from_decimal
  from cudf._typing import ColumnBinaryOperand, Dtype
  from cudf.api.types import is_integer_dtype, is_scalar
  from cudf.core.buffer import as_buffer
  from cudf.core.column import ColumnBase
  from cudf.core.dtypes import Decimal32Dtype, Decimal64Dtype, Decimal128Dtype, DecimalDtype
  from cudf.core.mixins import BinaryOperand
  from cudf.utils.utils import pa_mask_buffer_to_mask
  from .numerical_base import NumericalBaseColumn
label_desc: Use image node_id 2 for calling the Decimal32Column obj's underlying member method code with example usage: obj.to_arrow() and returns: pa