unique(self) -> 'ArrayLike'
Uniques are returned in order of appearance. Hash table-based unique, therefore does NOT sort.
Returns the unique values as a NumPy array. In case of an extension-array backed Series, a new ~api.extensions.ExtensionArray
of that type with just the unique values is returned. This includes
Categorical
Period
Datetime with Timezone
Interval
Sparse
IntegerNA
See Examples section.
The unique values returned as a NumPy array. See Notes.
Return unique values of Series object.
Index.unique
Return Index with unique values from an Index object.
unique
Top-level unique method for any 1-d array-like object.
>>> pd.Series([2, 1, 3, 3], name='A').unique() array([2, 1, 3])This example is valid syntax, but we were not able to check execution
>>> pd.Series([pd.Timestamp('2016-01-01') for _ in range(3)]).unique() array(['2016-01-01T00:00:00.000000000'], dtype='datetime64[ns]')This example is valid syntax, but we were not able to check execution
>>> pd.Series([pd.Timestamp('2016-01-01', tz='US/Eastern')
... for _ in range(3)]).unique() <DatetimeArray> ['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.
This example is valid syntax, but we were not able to check execution>>> pd.Series(pd.Categorical(list('baabc'))).unique() ['b', 'a', 'c'] Categories (3, object): ['a', 'b', 'c']This example is valid syntax, but we were not able to check execution
>>> pd.Series(pd.Categorical(list('baabc'), categories=list('abc'),See :
... ordered=True)).unique() ['b', 'a', 'c'] Categories (3, object): ['a' < 'b' < 'c']
The following pages refer to to this document either explicitly or contain code examples using this.
pandas.core.indexes.base.Index.unique
pandas.core.algorithms.unique
pandas.core.series.Series.unique
pandas.core.indexes.multi.MultiIndex.unique
pandas.core.arrays.categorical.Categorical.unique
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