code: def nansum(values, axis=None, skipna=True, min_count=0, mask=None):
      
      values, mask, dtype, dtype_max, _ = _get_values(values,
                                                      skipna, 0, mask=mask)
      dtype_sum = dtype_max
      if is_float_dtype(dtype):
          dtype_sum = dtype
      elif is_timedelta64_dtype(dtype):
          dtype_sum = np.float64
      the_sum = values.sum(axis, dtype=dtype_sum)
      the_sum = _maybe_null_out(the_sum, axis, mask, min_count=min_count)
  
      return _wrap_results(the_sum, dtype)
docs: Sum the elements along an axis ignoring NaNs
  
      Parameters
      ----------
      values : ndarray[dtype]
      axis: int, optional
      skipna : bool, default True
      min_count: int, default 0
      mask : ndarray[bool], optional
          nan-mask if known
  
      Returns
      -------
      result : dtype
  
      Examples
      --------
      >>> import pandas.core.nanops as nanops
      >>> s = pd.Series([1, 2, np.nan])
      >>> nanops.nansum(s)
      3.0