pandas.Series.unique — pandas 2.2.3 documentation (original) (raw)

Series.unique()[source]#

Return unique values of Series object.

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

Returns:

ndarray or ExtensionArray

The unique values returned as a NumPy array. See Notes.

See also

Series.drop_duplicates

Return Series with duplicate values removed.

unique

Top-level unique method for any 1-d array-like object.

Index.unique

Return Index with unique values from an Index object.

Notes

Returns the unique values as a NumPy array. In case of an extension-array backed Series, a newExtensionArray of that type with just the unique values is returned. This includes

• Categorical
• Period
• Datetime with Timezone
• Datetime without Timezone
• Timedelta
• Interval
• Sparse
• IntegerNA

See Examples section.

Examples

pd.Series([2, 1, 3, 3], name='A').unique() array([2, 1, 3])

pd.Series([pd.Timestamp('2016-01-01') for _ in range(3)]).unique() ['2016-01-01 00:00:00'] Length: 1, dtype: datetime64[ns]

pd.Series([pd.Timestamp('2016-01-01', tz='US/Eastern') ... for _ in range(3)]).unique() ['2016-01-01 00:00:00-05:00'] Length: 1, dtype: datetime64[ns, US/Eastern]

An Categorical will return categories in the order of appearance and with the same dtype.

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