pandas.unique#

pandas.unique(values)[source]#

Return unique values based on a hash table.

Uniques are returned in order of appearance. This does NOT sort.

Significantly faster than numpy.unique for long enough sequences.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.

See also

Index.unique

Return unique values from an Index.

Series.unique

Return unique values of Series object.

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"),...]...)...)<DatetimeArray>['2016-01-01 00:00:00-05:00']Length: 1, dtype: datetime64[ns, US/Eastern]

>>>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(np.array(list("baabc"),dtype="O"))array(['b', 'a', 'c'], dtype=object)

An unordered Categorical will return categories in theorder of appearance.

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

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