code: def nanall(values, axis=None, skipna=True, mask=None):
      """
      Check if all elements along an axis evaluate to True.
  
      Parameters
      ----------
      values : ndarray
      axis: int, optional
      skipna : bool, default True
      mask : ndarray[bool], optional
          nan-mask if known
  
      Returns
      -------
      result : bool
  
      Examples
      --------
      >>> import pandas.core.nanops as nanops
      >>> s = pd.Series([1, 2, np.nan])
      >>> nanops.nanall(s)
      True
  
      >>> import pandas.core.nanops as nanops
      >>> s = pd.Series([1, 0])
      >>> nanops.nanall(s)
      False
      """
      values, mask, dtype, _, _ = _get_values(
          values, skipna, True, copy=skipna, mask=mask
      )
      return values.all(axis)
  
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 11 for calling a global function with example usage: nanall(values, axis, skipna, mask) and returns: values