code: import numpy as np
  
  from pandas import Categorical, Series
  import pandas._testing as tm
  
  
  class TestUnique:
      def test_unique_data_ownership(self):
          # it works! GH#1807
          Series(Series(["a", "c", "b"]).unique()).sort_values()
  
      def test_unique(self):
          # GH#714 also, dtype=float
          ser = Series([1.2345] * 100)
          ser[::2] = np.nan
          result = ser.unique()
          assert len(result) == 2
  
          # explicit f4 dtype
          ser = Series([1.2345] * 100, dtype="f4")
          ser[::2] = np.nan
          result = ser.unique()
          assert len(result) == 2
  
      def test_unique_nan_object_dtype(self):
          # NAs in object arrays GH#714
          ser = Series(["foo"] * 100, dtype="O")
          ser[::2] = np.nan
          result = ser.unique()
          assert len(result) == 2
  
      def test_unique_none(self):
          # decision about None
          ser = Series([1, 2, 3, None, None, None], dtype=object)
          result = ser.unique()
          expected = np.array([1, 2, 3, None], dtype=object)
          tm.assert_numpy_array_equal(result, expected)
  
      def test_unique_categorical(self):
          # GH#18051
          cat = Categorical([])
          ser = Series(cat)
          result = ser.unique()
          tm.assert_categorical_equal(result, cat)
  
          cat = Categorical([np.nan])
          ser = Series(cat)
          result = ser.unique()
          tm.assert_categorical_equal(result, cat)
  