code: def nansem(values, axis=None, skipna=True, ddof=1, mask=None):
      """
      Compute the standard error in the mean along given axis while ignoring NaNs
  
      Parameters
      ----------
      values : ndarray
      axis: int, optional
      skipna : bool, default True
      ddof : int, default 1
          Delta Degrees of Freedom. The divisor used in calculations is N - ddof,
          where N represents the number of elements.
      mask : ndarray[bool], optional
          nan-mask if known
  
      Returns
      -------
      result : float64
          Unless input is a float array, in which case use the same
          precision as the input array.
  
      Examples
      --------
      >>> import pandas.core.nanops as nanops
      >>> s = pd.Series([1, np.nan, 2, 3])
      >>> nanops.nansem(s)
       0.5773502691896258
      """
  
      # This checks if non-numeric-like data is passed with numeric_only=False
      # and raises a TypeError otherwise
      nanvar(values, axis, skipna, ddof=ddof, mask=mask)
  
      if mask is None:
          mask = isna(values)
      if not is_float_dtype(values.dtype):
          values = values.astype("f8")
      count, _ = _get_counts_nanvar(mask, axis, ddof, values.dtype)
      var = nanvar(values, axis, skipna, ddof=ddof)
  
      return np.sqrt(var) / np.sqrt(count)
  
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 18 for calling a global function with example usage: nansem(values, axis, skipna, ddof, mask) and returns: unknown