Address review comments

Author: snitish

doc/source/whatsnew/v3.0.0.rst

@@ -55,8 +55,8 @@ Other enhancements
 - :meth:`Series.plot` now correctly handle the ``ylabel`` parameter for pie charts, allowing for explicit control over the y-axis label (:issue:`58239`)
 - :meth:`DataFrame.plot.scatter` argument ``c`` now accepts a column of strings, where rows with the same string are colored identically (:issue:`16827` and :issue:`16485`)
 - :func:`read_parquet` accepts ``to_pandas_kwargs`` which are forwarded to :meth:`pyarrow.Table.to_pandas` which enables passing additional keywords to customize the conversion to pandas, such as ``maps_as_pydicts`` to read the Parquet map data type as python dictionaries (:issue:`56842`)
+- :meth:`.DataFrameGroupBy.transform`, :meth:`.SeriesGroupBy.transform`, :meth:`.DataFrameGroupBy.agg`, :meth:`.SeriesGroupBy.agg`, :meth:`.SeriesGroupBy.apply`, :meth:`.DataFrameGroupBy.apply` now support ``kurt`` (:issue:`40139`)
 - :meth:`DataFrameGroupBy.transform`, :meth:`SeriesGroupBy.transform`, :meth:`DataFrameGroupBy.agg`, :meth:`SeriesGroupBy.agg`, :meth:`RollingGroupby.apply`, :meth:`ExpandingGroupby.apply`, :meth:`Rolling.apply`, :meth:`Expanding.apply`, :meth:`DataFrame.apply` with ``engine="numba"`` now supports positional arguments passed as kwargs (:issue:`58995`)
-- :meth:`DataFrameGroupBy.transform`, :meth:`SeriesGroupBy.transform`, :meth:`DataFrameGroupBy.agg`, :meth:`SeriesGroupBy.agg`, :meth:`SeriesGroupBy.apply`, :meth:`DataFrame.apply` now support ``kurt`` (:issue:`40139`)
 - :meth:`Rolling.agg`, :meth:`Expanding.agg` and :meth:`ExponentialMovingWindow.agg` now accept :class:`NamedAgg` aggregations through ``**kwargs`` (:issue:`28333`)
 - :meth:`Series.map` can now accept kwargs to pass on to func (:issue:`59814`)
 - :meth:`pandas.concat` will raise a ``ValueError`` when ``ignore_index=True`` and ``keys`` is not ``None`` (:issue:`59274`)

pandas/tests/groupby/methods/test_kurt.py

@@ -1,4 +1,5 @@
 import numpy as np
+import pytest
 
 import pandas.util._test_decorators as td
 
@@ -30,23 +31,27 @@ def test_groupby_kurt_equivalence():
     tm.assert_frame_equal(result, expected)
 
 
-@td.skip_if_no("pyarrow")
-def test_groupby_kurt_arrow_float64():
+@pytest.mark.parametrize(
+    "dtype",
+    [
+        pytest.param("float64[pyarrow]", marks=td.skip_if_no("pyarrow")),
+        "Float64",
+    ],
+)
+def test_groupby_kurt_arrow_float64(dtype):
     # GH#40139
-    # Test groupby.kurt() with float64[pyarrow] dtype
+    # Test groupby.kurt() with float64[pyarrow] and Float64 dtypes
     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]",
+        dtype=dtype,
     )
     gb = df.groupby(by=lambda x: 0)
 
     result = gb.kurt()
-    expected = pd.DataFrame(
-        {"x": [2.1644713], "y": [0.1513969]}, dtype="float64[pyarrow]"
-    )
+    expected = pd.DataFrame({"x": [2.1644713], "y": [0.1513969]}, dtype=dtype)
     tm.assert_almost_equal(result, expected)