Method values

pandas/core/series.py:747–787

Return Series as ndarray or ndarray-like depending on the dtype. .. warning:: We recommend using :attr:`Series.array` or :meth:`Series.to_numpy`, depending on whether you need a reference to the underlying data or a NumPy array. Returns

(self)

    @property
    def values(self):
        """
        Return Series as ndarray or ndarray-like depending on the dtype.

        .. warning::

           We recommend using :attr:`Series.array` or
           :meth:`Series.to_numpy`, depending on whether you need
           a reference to the underlying data or a NumPy array.

        Returns
        -------
        numpy.ndarray or ndarray-like

        See Also
        --------
        Series.array : Reference to the underlying data.
        Series.to_numpy : A NumPy array representing the underlying data.

        Examples
        --------
        >>> pd.Series([1, 2, 3]).values
        array([1, 2, 3])

        >>> pd.Series(list("aabc")).values
        <ArrowStringArray>
        ['a', 'a', 'b', 'c']
        Length: 4, dtype: str

        >>> pd.Series(list("aabc")).astype("category").values
        ['a', 'a', 'b', 'c']
        Categories (3, str): ['a', 'b', 'c']

        Timezone aware datetime data is converted to UTC:

        >>> pd.Series(pd.date_range("20130101", periods=3, tz="US/Eastern")).values
        array(['2013-01-01T05:00:00.000000',
               '2013-01-02T05:00:00.000000',
               '2013-01-03T05:00:00.000000'], dtype='datetime64[us]')
        """
        return self._mgr.external_values()

    @property
    def _values(self):