(data=None, index=None, dtype=None, name=None, copy=False, fastpath=False)
return hpat_pandas_series_ctor_impl
Intel Scalable Dataframe Compiler User Guide
    ********************************************
    Pandas API: pandas.Series

    Limitations
    -----------
    - Parameters ``dtype`` and ``copy`` are currently unsupported.
    - Types iterable and dict as ``data`` parameter are currently unsupported.
    - Categorical types (i.e. 'category' and ``CategoricalDtype``) are supported in ``dtype``
    only if they are provided as constants in jitted code.

    Examples
    --------
    Create Series with data [1, 2, 3] and index ['A', 'B', 'C'].

    >>> pd.Series([1, 2, 3], ['A', 'B', 'C'])

    Create Series with categorical data:

    >>> pd.Series([1, 2, 3], dtype='category')
    >>> pd.Series([1, 2, 3], dtype=CategoricalDtype([1, 2, 3]))

    .. seealso::

        :ref:`DataFrame <pandas.DataFrame>`
            DataFrame constructor.
Intel Scalable Dataframe Compiler User Guide
    ********************************************
    Pandas API: pandas.Series
Intel Scalable Dataframe Compiler User Guide ******************************************** Pandas API : pandas . Series
def pd_series_overload(data=None, index=None, dtype=None, name=None, copy=False, fastpath=False):
    """
    Intel Scalable Dataframe Compiler User Guide
    ********************************************
    Pandas API: pandas.Series

    Limitations
    -----------
    - Parameters ``dtype`` and ``copy`` are currently unsupported.
    - Types iterable and dict as ``data`` parameter are currently unsupported.
    - Categorical types (i.e. 'category' and ``CategoricalDtype``) are supported in ``dtype``
    only if they are provided as constants in jitted code.

    Examples
    --------
    Create Series with data [1, 2, 3] and index ['A', 'B', 'C'].

    >>> pd.Series([1, 2, 3], ['A', 'B', 'C'])

    Create Series with categorical data:

    >>> pd.Series([1, 2, 3], dtype='category')
    >>> pd.Series([1, 2, 3], dtype=CategoricalDtype([1, 2, 3]))

    .. seealso::

        :ref:`DataFrame <pandas.DataFrame>`
            DataFrame constructor.
    """

    if is_categoricaldtype(dtype):
        return _Series_category(data, index, dtype, name, copy, fastpath)

    def hpat_pandas_series_ctor_impl(data=None, index=None, dtype=None, name=None, copy=False, fastpath=False):

        fix_data = sdc.hiframes.api.fix_df_array(data)
        fix_index = sdc.hiframes.api.fix_df_index(index, fix_data)
        return sdc.hiframes.api.init_series(fix_data, fix_index, name)

    return hpat_pandas_series_ctor_impl
def pd_series_overload ( data = None , index = None , dtype = None , name = None , copy = False , fastpath = False ) : if is_categoricaldtype ( dtype ) : return _Series_category ( data , index , dtype , name , copy , fastpath ) def hpat_pandas_series_ctor_impl ( data = None , index = None , dtype = None , name = None , copy = False , fastpath = False ) : fix_data = sdc . hiframes . api . fix_df_array ( data ) fix_index = sdc . hiframes . api . fix_df_index ( index , fix_data ) return sdc . hiframes . api . init_series ( fix_data , fix_index , name ) return hpat_pandas_series_ctor_impl