code: def _na_for_min_count(
      values: np.ndarray, axis: AxisInt | None
  ) -> Scalar | np.ndarray:
      """
      Return the missing value for `values`.
  
      Parameters
      ----------
      values : ndarray
      axis : int or None
          axis for the reduction, required if values.ndim > 1.
  
      Returns
      -------
      result : scalar or ndarray
          For 1-D values, returns a scalar of the correct missing type.
          For 2-D values, returns a 1-D array where each element is missing.
      """
      # we either return np.nan or pd.NaT
      if values.dtype.kind in "iufcb":
          values = values.astype("float64")
      fill_value = na_value_for_dtype(values.dtype)
  
      if values.ndim == 1:
          return fill_value
      elif axis is None:
          return fill_value
      else:
          result_shape = values.shape[:axis] + values.shape[axis + 1 :]
  
          return np.full(result_shape, fill_value, dtype=values.dtype)
  
imports: from __future__ import annotations
  import functools
  import itertools
  from typing import Any, Callable, cast
  import warnings
  import numpy
  from pandas._config import get_option
  from pandas._libs import NaT, NaTType, iNaT, lib
  from pandas._typing import ArrayLike, AxisInt, CorrelationMethod, Dtype, DtypeObj, F, Scalar, Shape, npt
  from pandas.compat._optional import import_optional_dependency
  from pandas.util._exceptions import find_stack_level
  from pandas.core.dtypes.common import is_complex, is_float, is_float_dtype, is_integer, is_numeric_dtype, is_object_dtype, needs_i8_conversion, pandas_dtype
  from pandas.core.dtypes.missing import isna, na_value_for_dtype, notna
label_desc: Use image node_id 11 for calling a global function with example usage: _na_for_min_count(values, axis) and returns: fill_value, fill_value, np