pandas.Series.values#

propertySeries.values[source] #

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年01月01日T05:00:00.000000000',
 '2013年01月02日T05:00:00.000000000',
 '2013年01月03日T05:00:00.000000000'], dtype='datetime64[ns]')