code: def _get_counts(mask, axis, dtype=float):
      dtype = _get_dtype(dtype)
      if axis is None:
          return dtype.type(mask.size - mask.sum())
  
      count = mask.shape[axis] - mask.sum(axis)
      if is_scalar(count):
          return dtype.type(count)
      try:
          return count.astype(dtype)
      except AttributeError:
          return np.array(count, dtype=dtype)
  
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 26 for calling a global function with example usage: _get_counts(mask, axis, dtype) and returns: dtype, dtype, count, np