Backport PR #53651 on branch 2.0.x (BUG: convert_dtype(dtype_backend=nullable_numpy) with ArrowDtype) (#53749)

* Backport PR #53651: BUG: convert_dtype(dtype_backend=nullable_numpy) with ArrowDtype

* Move import

---------

Co-authored-by: Matthew Roeschke <[email protected]>

Author: meeseeksmachine

doc/source/whatsnew/v2.0.3.rst

@@ -21,6 +21,7 @@ Fixed regressions
 
 Bug fixes
 ~~~~~~~~~
+- Bug in :func:`DataFrame.convert_dtype` and :func:`Series.convert_dtype` when trying to convert :class:`ArrowDtype` with ``dtype_backend="nullable_numpy"`` (:issue:`53648`)
 - Bug in :func:`RangeIndex.union` when using ``sort=True`` with another :class:`RangeIndex` (:issue:`53490`)
 - Bug in :func:`Series.reindex` when expanding a non-nanosecond datetime or timedelta :class:`Series` would not fill with ``NaT`` correctly (:issue:`53497`)
 - Bug in :func:`read_csv` when defining ``dtype`` with ``bool[pyarrow]`` for the ``"c"`` and ``"python"`` engines (:issue:`53390`)

pandas/core/dtypes/cast.py

@@ -96,6 +96,8 @@
     notna,
 )
 
+from pandas.io._util import _arrow_dtype_mapping
+
 if TYPE_CHECKING:
     from pandas import Index
     from pandas.core.arrays import (
@@ -1046,6 +1048,8 @@ def convert_dtypes(
     """
     inferred_dtype: str | DtypeObj
 
+    from pandas.core.arrays.arrow.dtype import ArrowDtype
+
     if (
         convert_string or convert_integer or convert_boolean or convert_floating
     ) and isinstance(input_array, np.ndarray):
@@ -1128,7 +1132,6 @@ def convert_dtypes(
 
     if dtype_backend == "pyarrow":
         from pandas.core.arrays.arrow.array import to_pyarrow_type
-        from pandas.core.arrays.arrow.dtype import ArrowDtype
         from pandas.core.arrays.string_ import StringDtype
 
         assert not isinstance(inferred_dtype, str)
@@ -1156,6 +1159,9 @@ def convert_dtypes(
             pa_type = to_pyarrow_type(base_dtype)
             if pa_type is not None:
                 inferred_dtype = ArrowDtype(pa_type)
+    elif dtype_backend == "numpy_nullable" and isinstance(inferred_dtype, ArrowDtype):
+        # GH 53648
+        inferred_dtype = _arrow_dtype_mapping()[inferred_dtype.pyarrow_dtype]
 
     # error: Incompatible return value type (got "Union[str, Union[dtype[Any],
     # ExtensionDtype]]", expected "Union[dtype[Any], ExtensionDtype]")

pandas/tests/frame/methods/test_convert_dtypes.py

@@ -146,7 +146,7 @@ def test_pyarrow_engine_lines_false(self):
         with pytest.raises(ValueError, match=msg):
             df.convert_dtypes(dtype_backend="numpy")
 
-    def test_pyarrow_backend_no_convesion(self):
+    def test_pyarrow_backend_no_conversion(self):
         # GH#52872
         pytest.importorskip("pyarrow")
         df = pd.DataFrame({"a": [1, 2], "b": 1.5, "c": True, "d": "x"})
@@ -159,3 +159,11 @@ def test_pyarrow_backend_no_convesion(self):
             dtype_backend="pyarrow",
         )
         tm.assert_frame_equal(result, expected)
+
+    def test_convert_dtypes_pyarrow_to_np_nullable(self):
+        # GH 53648
+        pytest.importorskip("pyarrow")
+        ser = pd.DataFrame(range(2), dtype="int32[pyarrow]")
+        result = ser.convert_dtypes(dtype_backend="numpy_nullable")
+        expected = pd.DataFrame(range(2), dtype="Int32")
+        tm.assert_frame_equal(result, expected)

pandas/tests/series/methods/test_convert_dtypes.py

@@ -240,3 +240,11 @@ def test_convert_dtype_object_with_na_float(self, infer_objects, dtype):
         result = ser.convert_dtypes(infer_objects=infer_objects)
         expected = pd.Series([1.5, pd.NA], dtype=dtype)
         tm.assert_series_equal(result, expected)
+
+    def test_convert_dtypes_pyarrow_to_np_nullable(self):
+        # GH 53648
+        pytest.importorskip("pyarrow")
+        ser = pd.Series(range(2), dtype="int32[pyarrow]")
+        result = ser.convert_dtypes(dtype_backend="numpy_nullable")
+        expected = pd.Series(range(2), dtype="Int32")
+        tm.assert_series_equal(result, expected)