(self)
Intel Scalable Dataframe Compiler User Guide
    ********************************************

    Pandas API: pandas.Series.isnull

    Examples
    --------
    .. literalinclude:: ../../../examples/series/series_isnull.py
       :language: python
       :lines: 27-
       :caption: Detect missing values.
       :name: ex_series_isnull

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

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

    .. only:: developer
        Test: python -m sdc.runtests -k sdc.tests.test_series.TestSeries.test_series_isnull*
Intel Scalable Dataframe Compiler User Guide
    ********************************************
Intel Scalable Dataframe Compiler User Guide ********************************************
def hpat_pandas_series_isnull(self):
    """
    Intel Scalable Dataframe Compiler User Guide
    ********************************************

    Pandas API: pandas.Series.isnull

    Examples
    --------
    .. literalinclude:: ../../../examples/series/series_isnull.py
       :language: python
       :lines: 27-
       :caption: Detect missing values.
       :name: ex_series_isnull

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

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

    .. only:: developer
        Test: python -m sdc.runtests -k sdc.tests.test_series.TestSeries.test_series_isnull*
    """

    _func_name = 'Method isnull().'

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

    if isinstance(self.data.dtype, (types.Number, types.Boolean, bool)):
        def hpat_pandas_series_isnull_impl(self):
            return pandas.Series(data=numpy_like.isnan(self._data), index=self._index, name=self._name)

        return hpat_pandas_series_isnull_impl

    if isinstance(self.data.dtype, types.UnicodeType):
        def hpat_pandas_series_isnull_impl(self):
            result = numpy.empty(len(self._data), numpy.bool_)
            byte_size = 8
            # iterate over bits in StringArrayType null_bitmap and fill array indicating if array's element are NaN
            for i in range(len(self._data)):
                bmap_idx = i // byte_size
                bit_idx = i % byte_size
                bmap = self._data.null_bitmap[bmap_idx]
                bit_value = (bmap >> bit_idx) & 1
                result[i] = bit_value == 0
            return pandas.Series(result, index=self._index, name=self._name)

        return hpat_pandas_series_isnull_impl
def hpat_pandas_series_isnull ( self ) : _func_name = 'Method isnull().' ty_checker = TypeChecker ( _func_name ) ty_checker . check ( self , SeriesType ) if isinstance ( self . data . dtype , ( types . Number , types . Boolean , bool ) ) : def hpat_pandas_series_isnull_impl ( self ) : return pandas . Series ( data = numpy_like . isnan ( self . _data ) , index = self . _index , name = self . _name ) return hpat_pandas_series_isnull_impl if isinstance ( self . data . dtype , types . UnicodeType ) : def hpat_pandas_series_isnull_impl ( self ) : result = numpy . empty ( len ( self . _data ) , numpy . bool_ ) byte_size = 8 # iterate over bits in StringArrayType null_bitmap and fill array indicating if array's element are NaN for i in range ( len ( self . _data ) ) : bmap_idx = i // byte_size bit_idx = i % byte_size bmap = self . _data . null_bitmap [ bmap_idx ] bit_value = ( bmap >> bit_idx ) & 1 result [ i ] = bit_value == 0 return pandas . Series ( result , index = self . _index , name = self . _name ) return hpat_pandas_series_isnull_impl