pandas.unique — pandas 1.0.1 documentation (original) (raw)

pandas. unique(values)[source]¶

Hash table-based unique. Uniques are returned in order of appearance. This does NOT sort.

Significantly faster than numpy.unique. Includes NA values.

Parameters

values1d array-like

Returns

numpy.ndarray or ExtensionArray

The return can be:

• Index : when the input is an Index
• Categorical : when the input is a Categorical dtype
• ndarray : when the input is a Series/ndarray

Return numpy.ndarray or ExtensionArray.

Examples

pd.unique(pd.Series([2, 1, 3, 3])) array([2, 1, 3])

pd.unique(pd.Series([2] + [1] * 5)) array([2, 1])

pd.unique(pd.Series([pd.Timestamp('20160101'), ... pd.Timestamp('20160101')])) array(['2016-01-01T00:00:00.000000000'], dtype='datetime64[ns]')

pd.unique(pd.Series([pd.Timestamp('20160101', tz='US/Eastern'), ... pd.Timestamp('20160101', tz='US/Eastern')])) array([Timestamp('2016-01-01 00:00:00-0500', tz='US/Eastern')], dtype=object)

pd.unique(pd.Index([pd.Timestamp('20160101', tz='US/Eastern'), ... pd.Timestamp('20160101', tz='US/Eastern')])) DatetimeIndex(['2016-01-01 00:00:00-05:00'], ... dtype='datetime64[ns, US/Eastern]', freq=None)

pd.unique(list('baabc')) array(['b', 'a', 'c'], dtype=object)

An unordered Categorical will return categories in the order of appearance.

pd.unique(pd.Series(pd.Categorical(list('baabc')))) [b, a, c] Categories (3, object): [b, a, c]

pd.unique(pd.Series(pd.Categorical(list('baabc'), ... categories=list('abc')))) [b, a, c] Categories (3, object): [b, a, c]

An ordered Categorical preserves the category ordering.

pd.unique(pd.Series(pd.Categorical(list('baabc'), ... categories=list('abc'), ... ordered=True))) [b, a, c] Categories (3, object): [a < b < c]

An array of tuples

pd.unique([('a', 'b'), ('b', 'a'), ('a', 'c'), ('b', 'a')]) array([('a', 'b'), ('b', 'a'), ('a', 'c')], dtype=object)