diff --git a/tests/unique_test.py b/tests/unique_test.py
index <HASH>..<HASH> 100644
--- a/tests/unique_test.py
+++ b/tests/unique_test.py
@@ -37,3 +37,10 @@ def test_unique_nan():
         mask = np.isnan(values)
         assert values[~mask].tolist() == df.x.values[~mask].tolist()
         # assert indices.tolist() == [0, 1, 2, 0, 3, 0]
+
+def test_unique_missing():
+    # Create test databn
+    x = np.array([None, 'A', 'B', -1, 0, 2, '', '', None, None, None, np.nan, np.nan, np.nan, np.nan,])
+    df = vaex.from_arrays(x=x)
+    uniques = df.x.unique(dropnan=True).tolist()
+    assert set(uniques) == set(['', 'A', 'B', -1, 0, 2, None])
Unit-test for unique in case of dtype object and n/a values (#<I>)

* Unit-test for unique in case of object type and missing values (np.nan, None)



* make first element None so it is dtype=object



* fix: include None, skip nan, since comparison of nan is always false