pandas.Series.values

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
array(['a', 'a', 'b', 'c'], dtype=object)
>>> pd.Series(list('aabc')).astype('category').values
[a, a, b, c]
Categories (3, object): [a, b, c]

Timezone aware datetime data is converted to UTC:

>>> pd.Series(pd.date_range('20130101', periods=3,
...                         tz='US/Eastern')).values
array(['2013-01-01T05:00:00.000000000',
       '2013-01-02T05:00:00.000000000',
       '2013-01-03T05:00:00.000000000'], dtype='datetime64[ns]')
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