pandas.Series.values#
- property Series.values[source]#
Return Series as ndarray or ndarray-like depending on the dtype.
Warning
We recommend using
Series.array
orSeries.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]')