ENH: Address review comments

Author: snitish

pandas/_libs/groupby.pyx

@@ -910,7 +910,7 @@ def group_var(
 @cython.wraparound(False)
 @cython.boundscheck(False)
 @cython.cdivision(True)
-@cython.cpow
+@cython.cpow(True)
 def group_skew(
     float64_t[:, ::1] out,
     int64_t[::1] counts,
@@ -961,7 +961,7 @@ def group_skew(
                     isna_entry = _treat_as_na(val, False)
 
                 if not isna_entry:
-                    # Based on RunningStats::Push from
+                    # Running stats update based on RunningStats::Push from
                     #  https://www.johndcook.com/blog/skewness_kurtosis/
                     n1 = nobs[lab, j]
                     n = n1 + 1
@@ -998,7 +998,7 @@ def group_skew(
 @cython.wraparound(False)
 @cython.boundscheck(False)
 @cython.cdivision(True)
-@cython.cpow
+@cython.cpow(True)
 def group_kurt(
     float64_t[:, ::1] out,
     int64_t[::1] counts,
@@ -1050,7 +1050,7 @@ def group_kurt(
                     isna_entry = _treat_as_na(val, False)
 
                 if not isna_entry:
-                    # Based on RunningStats::Push from
+                    # Running stats update based on RunningStats::Push from
                     #  https://www.johndcook.com/blog/skewness_kurtosis/
                     n1 = nobs[lab, j]
                     n = n1 + 1

pandas/core/groupby/generic.py

@@ -1270,13 +1270,8 @@ def skew(
         Name: Max Speed, dtype: float64
         """
 
-        def alt(obj):
-            # This should not be reached since the cython path should raise
-            #  TypeError and not NotImplementedError.
-            raise TypeError(f"'skew' is not supported for dtype={obj.dtype}")
-
         return self._cython_agg_general(
-            "skew", alt=alt, skipna=skipna, numeric_only=numeric_only, **kwargs
+            "skew", alt=None, skipna=skipna, numeric_only=numeric_only, **kwargs
         )
 
     def kurt(
@@ -3084,13 +3079,8 @@ def kurt(
         mammal   0.204125
         """
 
-        def alt(obj):
-            # This should not be reached since the cython path should raise
-            #  TypeError and not NotImplementedError.
-            raise TypeError(f"'kurt' is not supported for dtype={obj.dtype}")
-
         return self._cython_agg_general(
-            "kurt", alt=alt, skipna=skipna, numeric_only=numeric_only, **kwargs
+            "kurt", alt=None, skipna=skipna, numeric_only=numeric_only, **kwargs
         )
 
     @property

pandas/tests/groupby/methods/test_kurt.py

@@ -5,6 +5,7 @@
 
 
 def test_groupby_kurt_equivalence():
+    # GH#40139
     # Test that that groupby kurt method (which uses libgroupby.group_kurt)
     #  matches the results of operating group-by-group (which uses nanops.nankurt)
     nrows = 1000
@@ -23,5 +24,59 @@ def test_groupby_kurt_equivalence():
 
     grpwise = [grp.kurt().to_frame(i).T for i, grp in gb]
     expected = pd.concat(grpwise, axis=0)
-    expected.index = expected.index.astype(result.index.dtype)  # 32bit builds
+    expected.index = expected.index.astype(np.intp)  # 32bit builds
     tm.assert_frame_equal(result, expected)
+
+
+def test_groupby_kurt_arrow_float64():
+    # GH#40139
+    # Test groupby.kurt() with skipna = False
+    df = pd.DataFrame(
+        {
+            "x": [1.0, np.nan, 3.2, 4.8, 2.3, 1.9, 8.9],
+            "y": [1.6, 3.3, 3.2, 6.8, 1.3, 2.9, 9.0],
+        },
+        dtype="float64[pyarrow]",
+    )
+    gb = df.groupby(by=lambda x: 0)
+
+    result = gb.kurt()
+    expected = pd.DataFrame(
+        {"x": [2.1644713], "y": [0.1513969]}, dtype="float64[pyarrow]"
+    )
+    tm.assert_almost_equal(result, expected)
+
+
+def test_groupby_kurt_noskipna():
+    # GH#40139
+    # Test groupby.kurt() with skipna = False
+    df = pd.DataFrame(
+        {
+            "x": [1.0, np.nan, 3.2, 4.8, 2.3, 1.9, 8.9],
+            "y": [1.6, 3.3, 3.2, 6.8, 1.3, 2.9, 9.0],
+        }
+    )
+    gb = df.groupby(by=lambda x: 0)
+
+    result = gb.kurt(skipna=False)
+    expected = pd.DataFrame({"x": [np.nan], "y": [0.1513969]})
+    tm.assert_almost_equal(result, expected)
+
+
+def test_groupby_kurt_all_ones():
+    # GH#40139
+    # Test groupby.kurt() with skipna = False
+    df = pd.DataFrame(
+        {
+            "x": [1.0] * 10,
+        }
+    )
+    gb = df.groupby(by=lambda x: 0)
+
+    result = gb.kurt(skipna=False)
+    expected = pd.DataFrame(
+        {
+            "x": [0.0],  # Same behavior as pd.DataFrame.kurt()
+        }
+    )
+    tm.assert_almost_equal(result, expected)