Pandas: Series - unique() function

Unique values of Series object in Pandas

The unique() function is used to get unique values of Series object.

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

Syntax:

Series.unique(self)

Returns: ndarray or ExtensionArray
The unique values returned as a NumPy array. See Notes.

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

• Categorical
• Period
• Datetime with Timezone
• Interval
• Sparse
• IntegerNA

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
pd.Series([2, 4, 3, 3], name='P').unique()

Output:

array([2, 4, 3], dtype=int64)

Python-Pandas Code:

import numpy as np
import pandas as pd
pd.Series([2, 4, 3, 3], name='P').unique()
pd.Series([pd.Timestamp('2019-01-01') for _ in range(3)]).unique()

Output:

array(['2019-01-01T00:00:00.000000000'], dtype='datetime64[ns]')

Python-Pandas Code:

import numpy as np
import pandas as pd
pd.Series([2, 4, 3, 3], name='P').unique()
pd.Series([pd.Timestamp('2019-01-01', tz='US/Eastern')
           for _ in range(3)]).unique()

Output:

['2019-01-01 00:00:00-05:00']
Length: 1, dtype: datetime64[ns, US/Eastern]

Example - An unordered Categorical will return categories in the order of appearance:

Python-Pandas Code:

import numpy as np
import pandas as pd
pd.Series(pd.Categorical(list('qppqr'))).unique()

Output:

[q, p, r]
Categories (3, object): [q, p, r]

Example - An ordered Categorical preserves the category ordering:

Python-Pandas Code:

import numpy as np
import pandas as pd
pd.Series(pd.Categorical(list('qppqr'), categories=list('pqr'),
                         ordered=True)).unique()

Output:

[q, p, r]
Categories (3, object): [p < q < r]

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