(
    self,
    axis=None,
    skipna=None,
    level=None,
    numeric_only=None,
    min_count=0,
)
return hpat_pandas_series_sum_impl
Intel Scalable Dataframe Compiler User Guide
    ********************************************

    Pandas API: pandas.Series.sum

    Limitations
    -----------
    - Parameters ``axis``, ``level``, ``numeric_only`` and ``min_count`` \
        are currently unsupported by Intel Scalable Dataframe Compiler

    Examples
    --------
    .. literalinclude:: ../../../examples/series/series_sum.py
       :language: python
       :lines: 27-
       :caption: Return the sum of the values for the requested axis.
       :name: ex_series_sum

    .. command-output:: python ./series/series_sum.py
       :cwd: ../../../examples

    .. seealso::

        :ref:`Series.sum <pandas.Series.sum>`
            Return the sum.

        :ref:`Series.min <pandas.Series.min>`
            Return the minimum.

        :ref:`Series.max <pandas.Series.max>`
            Return the maximum.

        :ref:`Series.idxmin <pandas.Series.idxmin>`
            Return the index of the minimum.

        :ref:`Series.idxmax <pandas.Series.idxmax>`
            Return the index of the maximum.

        :ref:`DataFrame.sum <pandas.DataFrame.sum>`
            Return the sum over the requested axis.

        :ref:`DataFrame.min <pandas.DataFrame.min>`
            Return the minimum over the requested axis.

        :ref:`DataFrame.max <pandas.DataFrame.max>`
            Return the maximum over the requested axis.

        :ref:`DataFrame.idxmin <pandas.DataFrame.idxmin>`
            Return the index of the minimum over the requested axis.

        :ref:`DataFrame.idxmax <pandas.DataFrame.idxmax>`
            Return index of first occurrence of maximum over requested axis.

    Intel Scalable Dataframe Compiler Developer Guide
    *************************************************
    Pandas Series method :meth:`pandas.Series.sum` implementation.

    .. only:: developer
        Test: python -m sdc.runtests sdc.tests.test_series -k series_sum
Intel Scalable Dataframe Compiler User Guide
    ********************************************
Intel Scalable Dataframe Compiler User Guide ********************************************
def hpat_pandas_series_sum(
    self,
    axis=None,
    skipna=None,
    level=None,
    numeric_only=None,
    min_count=0,
):
    """
    Intel Scalable Dataframe Compiler User Guide
    ********************************************

    Pandas API: pandas.Series.sum

    Limitations
    -----------
    - Parameters ``axis``, ``level``, ``numeric_only`` and ``min_count`` \
        are currently unsupported by Intel Scalable Dataframe Compiler

    Examples
    --------
    .. literalinclude:: ../../../examples/series/series_sum.py
       :language: python
       :lines: 27-
       :caption: Return the sum of the values for the requested axis.
       :name: ex_series_sum

    .. command-output:: python ./series/series_sum.py
       :cwd: ../../../examples

    .. seealso::

        :ref:`Series.sum <pandas.Series.sum>`
            Return the sum.

        :ref:`Series.min <pandas.Series.min>`
            Return the minimum.

        :ref:`Series.max <pandas.Series.max>`
            Return the maximum.

        :ref:`Series.idxmin <pandas.Series.idxmin>`
            Return the index of the minimum.

        :ref:`Series.idxmax <pandas.Series.idxmax>`
            Return the index of the maximum.

        :ref:`DataFrame.sum <pandas.DataFrame.sum>`
            Return the sum over the requested axis.

        :ref:`DataFrame.min <pandas.DataFrame.min>`
            Return the minimum over the requested axis.

        :ref:`DataFrame.max <pandas.DataFrame.max>`
            Return the maximum over the requested axis.

        :ref:`DataFrame.idxmin <pandas.DataFrame.idxmin>`
            Return the index of the minimum over the requested axis.

        :ref:`DataFrame.idxmax <pandas.DataFrame.idxmax>`
            Return index of first occurrence of maximum over requested axis.

    Intel Scalable Dataframe Compiler Developer Guide
    *************************************************
    Pandas Series method :meth:`pandas.Series.sum` implementation.

    .. only:: developer
        Test: python -m sdc.runtests sdc.tests.test_series -k series_sum
    """

    _func_name = 'Method sum().'

    ty_checker = TypeChecker(_func_name)
    ty_checker.check(self, SeriesType)

    if not (isinstance(axis, (types.Integer, types.Omitted)) or axis is None):
        ty_checker.raise_exc(axis, 'int', 'axis')

    if not (isinstance(skipna, (types.Boolean, types.Omitted, types.NoneType)) or skipna is None):
        ty_checker.raise_exc(skipna, 'bool', 'skipna')

    if not (isinstance(level, (types.Integer, types.StringLiteral, types.Omitted, types.NoneType)) or level is None):
        ty_checker.raise_exc(level, 'int or str', 'level')

    if not (isinstance(numeric_only, (types.Boolean, types.Omitted)) or numeric_only is None):
        ty_checker.raise_exc(numeric_only, 'bool', 'numeric_only')

    if not (isinstance(min_count, (types.Integer, types.Omitted)) or min_count == 0):
        ty_checker.raise_exc(min_count, 'int', 'min_count')

    def hpat_pandas_series_sum_impl(
        self,
        axis=None,
        skipna=None,
        level=None,
        numeric_only=None,
        min_count=0,
    ):

        if skipna is None:
            _skipna = True
        else:
            _skipna = skipna

        if _skipna:
            return numpy_like.nansum(self._data)
        return numpy_like.sum(self._data)

    return hpat_pandas_series_sum_impl
def hpat_pandas_series_sum ( self , axis = None , skipna = None , level = None , numeric_only = None , min_count = 0 , ) : _func_name = 'Method sum().' ty_checker = TypeChecker ( _func_name ) ty_checker . check ( self , SeriesType ) if not ( isinstance ( axis , ( types . Integer , types . Omitted ) ) or axis is None ) : ty_checker . raise_exc ( axis , 'int' , 'axis' ) if not ( isinstance ( skipna , ( types . Boolean , types . Omitted , types . NoneType ) ) or skipna is None ) : ty_checker . raise_exc ( skipna , 'bool' , 'skipna' ) if not ( isinstance ( level , ( types . Integer , types . StringLiteral , types . Omitted , types . NoneType ) ) or level is None ) : ty_checker . raise_exc ( level , 'int or str' , 'level' ) if not ( isinstance ( numeric_only , ( types . Boolean , types . Omitted ) ) or numeric_only is None ) : ty_checker . raise_exc ( numeric_only , 'bool' , 'numeric_only' ) if not ( isinstance ( min_count , ( types . Integer , types . Omitted ) ) or min_count == 0 ) : ty_checker . raise_exc ( min_count , 'int' , 'min_count' ) def hpat_pandas_series_sum_impl ( self , axis = None , skipna = None , level = None , numeric_only = None , min_count = 0 , ) : if skipna is None : _skipna = True else : _skipna = skipna if _skipna : return numpy_like . nansum ( self . _data ) return numpy_like . sum ( self . _data ) return hpat_pandas_series_sum_impl