code: def _get_counts_nanvar(mask, axis, ddof, dtype=float):
      dtype = _get_dtype(dtype)
      count = _get_counts(mask, axis, dtype=dtype)
      d = count - dtype.type(ddof)
  
      # always return NaN, never inf
      if is_scalar(count):
          if count <= ddof:
              count = np.nan
              d = np.nan
      else:
          mask2 = count <= ddof
          if mask2.any():
              np.putmask(d, mask2, np.nan)
              np.putmask(count, mask2, np.nan)
      return count, d
  
imports: from distutils.version import LooseVersion
  import functools
  import itertools
  import operator
  import warnings
  import numpy
  from pandas._libs import iNaT, lib, tslibs
  import pandas.compat
  from pandas.core.dtypes.cast import _int64_max, maybe_upcast_putmask
  from pandas.core.dtypes.common import _get_dtype, is_any_int_dtype, is_bool_dtype, is_complex, is_complex_dtype, is_datetime64_dtype, is_datetime64tz_dtype, is_datetime_or_timedelta_dtype, is_float, is_float_dtype, is_integer, is_integer_dtype, is_numeric_dtype, is_object_dtype, is_scalar, is_timedelta64_dtype, pandas_dtype
  from pandas.core.dtypes.dtypes import DatetimeTZDtype
  from pandas.core.dtypes.missing import isna, na_value_for_dtype, notna
  import pandas.core.common
  from pandas.core.config import get_option
label_desc: Use image node_id 15 for calling a global function with example usage: _get_counts_nanvar(mask, axis, ddof, dtype) and returns: count,  d