(self, axis=0, inplace=False)
Intel Scalable Dataframe Compiler User Guide
    ********************************************

    Pandas API: pandas.Series.dropna

    Limitations
    -----------
    - Parameters ``inplace`` and ``axis`` are currently unsupported by Intel Scalable Dataframe Compiler.

    Examples
    --------
    .. literalinclude:: ../../../examples/series/series_dropna.py
       :language: python
       :lines: 34-
       :caption: Return a new Series with missing values removed.
       :name: ex_series_dropna

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

    .. seealso::

        :ref:`Series.isna <pandas.Series.isna>`
            Indicate missing values.

        :ref:`Series.notna <pandas.Series.notna>`
            Indicate existing (non-missing) values.

        :ref:`Series.fillna <pandas.Series.fillna>`
            Replace missing values.

        :ref:`DataFrame.dropna <pandas.DataFrame.dropna>`
            Drop rows or columns which contain NA values.

        `pandas.Index.dropna
        <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Index.dropna.html#pandas.Index.dropna>`_
            Return Index without NA/NaN values

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

    .. only:: developer
       Tests: python -m sdc.runtests -k sdc.tests.test_series.TestSeries.test_series_dropna*
Intel Scalable Dataframe Compiler User Guide
    ********************************************
Intel Scalable Dataframe Compiler User Guide ********************************************
def hpat_pandas_series_dropna(self, axis=0, inplace=False):
    """
    Intel Scalable Dataframe Compiler User Guide
    ********************************************

    Pandas API: pandas.Series.dropna

    Limitations
    -----------
    - Parameters ``inplace`` and ``axis`` are currently unsupported by Intel Scalable Dataframe Compiler.

    Examples
    --------
    .. literalinclude:: ../../../examples/series/series_dropna.py
       :language: python
       :lines: 34-
       :caption: Return a new Series with missing values removed.
       :name: ex_series_dropna

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

    .. seealso::

        :ref:`Series.isna <pandas.Series.isna>`
            Indicate missing values.

        :ref:`Series.notna <pandas.Series.notna>`
            Indicate existing (non-missing) values.

        :ref:`Series.fillna <pandas.Series.fillna>`
            Replace missing values.

        :ref:`DataFrame.dropna <pandas.DataFrame.dropna>`
            Drop rows or columns which contain NA values.

        `pandas.Index.dropna
        <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Index.dropna.html#pandas.Index.dropna>`_
            Return Index without NA/NaN values

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

    .. only:: developer
       Tests: python -m sdc.runtests -k sdc.tests.test_series.TestSeries.test_series_dropna*
    """

    _func_name = 'Method dropna().'

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

    if not (isinstance(axis, (types.Integer, types.StringLiteral, types.UnicodeType, types.Omitted)) or axis == 0):
        ty_checker.raise_exc(axis, 'int or str', 'axis')

    if not (inplace is False or isinstance(inplace, types.Omitted)):
        ty_checker.raise_exc(inplace, 'bool', 'inplace')

    # if both data and index are numeric (i.e. types.Array) dispatch to numpy_like.dropna impl
    if (isinstance(self.dtype, types.Number) and isinstance(self.index.dtype, types.Number)):
        def hpat_pandas_series_dropna_impl(self, axis=0, inplace=False):
            return numpy_like.dropna(self._data, self._index, self._name)

        return hpat_pandas_series_dropna_impl

    else:
        def hpat_pandas_series_dropna_str_impl(self, axis=0, inplace=False):
            # TO-DO: verify these operations are fused
            na_data_arr = sdc.hiframes.api.get_nan_mask(self._data)
            data = self._data[~na_data_arr]
            index = self._index[~na_data_arr]
            return pandas.Series(data, index, self._name)

        return hpat_pandas_series_dropna_str_impl
def hpat_pandas_series_dropna ( self , axis = 0 , inplace = False ) : _func_name = 'Method dropna().' ty_checker = TypeChecker ( _func_name ) ty_checker . check ( self , SeriesType ) if not ( isinstance ( axis , ( types . Integer , types . StringLiteral , types . UnicodeType , types . Omitted ) ) or axis == 0 ) : ty_checker . raise_exc ( axis , 'int or str' , 'axis' ) if not ( inplace is False or isinstance ( inplace , types . Omitted ) ) : ty_checker . raise_exc ( inplace , 'bool' , 'inplace' ) # if both data and index are numeric (i.e. types.Array) dispatch to numpy_like.dropna impl if ( isinstance ( self . dtype , types . Number ) and isinstance ( self . index . dtype , types . Number ) ) : def hpat_pandas_series_dropna_impl ( self , axis = 0 , inplace = False ) : return numpy_like . dropna ( self . _data , self . _index , self . _name ) return hpat_pandas_series_dropna_impl else : def hpat_pandas_series_dropna_str_impl ( self , axis = 0 , inplace = False ) : # TO-DO: verify these operations are fused na_data_arr = sdc . hiframes . api . get_nan_mask ( self . _data ) data = self . _data [ ~ na_data_arr ] index = self . _index [ ~ na_data_arr ] return pandas . Series ( data , index , self . _name ) return hpat_pandas_series_dropna_str_impl