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# pandas.Series.values

property Series.values

  Return Series as ndarray or ndarray-like depending on the dtype.

  Warning

  We recommend using `Series.array` or `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]')