Respect groupby.nunique(dropna=False)

python/cudf/cudf/_lib/aggregation.pyx

@@ -78,8 +78,11 @@ class Aggregation:
         )
 
     @classmethod
-    def nunique(cls):
-        return cls(pylibcudf.aggregation.nunique(pylibcudf.types.NullPolicy.EXCLUDE))
+    def nunique(cls, dropna=True):
+        return cls(pylibcudf.aggregation.nunique(
+            pylibcudf.types.NullPolicy.EXCLUDE
+            if dropna else pylibcudf.types.NullPolicy.INCLUDE
+        ))
 
     @classmethod
     def nth(cls, size):

python/cudf/cudf/core/groupby/groupby.py

@@ -2232,6 +2232,22 @@ def func(x):
 
         return self.agg(func)
 
+    @_performance_tracking
+    def nunique(self, dropna: bool = True):
+        """
+        Return number of unique elements in the group.
+
+        Parameters
+        ----------
+        dropna : bool, default True
+            Don't include NaN in the counts.
+        """
+
+        def func(x):
+            return getattr(x, "nunique")(dropna=dropna)
+
+        return self.agg(func)
+
     @_performance_tracking
     def std(
         self,

python/cudf/cudf/tests/test_groupby.py

@@ -1940,6 +1940,23 @@ def test_groupby_nunique(agg, by):
     assert_groupby_results_equal(expect, got, check_dtype=False)
 
 
+@pytest.mark.parametrize("dropna", [True, False])
+def test_nunique_dropna(dropna):
+    gdf = cudf.DataFrame(
+        {
+            "a": [1, 1, 2],
+            "b": [4, None, 5],
+            "c": [None, None, 7],
+            "d": [1, 1, 3],
+        }
+    )
+    pdf = gdf.to_pandas()
+
+    result = gdf.groupby("a")["b"].nunique(dropna=dropna)
+    expected = pdf.groupby("a")["b"].nunique(dropna=dropna)
+    assert_groupby_results_equal(result, expected, check_dtype=False)
+
+
 @pytest.mark.parametrize(
     "n",
     [0, 1, 2, 10],