BUG: convert_dtypes ingoring convert keywords for pyarrow backend

doc/source/whatsnew/v2.0.1.rst

@@ -38,6 +38,7 @@ Bug fixes
 - Bug in :func:`to_datetime` and :func:`to_timedelta` when trying to convert numeric data with a :class:`ArrowDtype` (:issue:`52425`)
 - Bug in :func:`to_numeric` with ``errors='coerce'`` and ``dtype_backend='pyarrow'`` with :class:`ArrowDtype` data (:issue:`52588`)
 - Bug in :meth:`ArrowDtype.__from_arrow__` not respecting if dtype is explicitly given (:issue:`52533`)
+- Bug in :meth:`DataFrame.convert_dtypes` ignores ``convert_foo`` keywords when ``dtype_backeend="pyarrow"`` (:issue:`52872`)
 - Bug in :meth:`DataFrame.max` and related casting different :class:`Timestamp` resolutions always to nanoseconds (:issue:`52524`)
 - Bug in :meth:`Series.describe` not returning :class:`ArrowDtype` with ``pyarrow.float64`` type with numeric data (:issue:`52427`)
 - Bug in :meth:`Series.dt.tz_localize` incorrectly localizing timestamps with :class:`ArrowDtype` (:issue:`52677`)

pandas/core/dtypes/cast.py

@@ -1106,20 +1106,30 @@ def convert_dtypes(
         from pandas.core.arrays.arrow.dtype import ArrowDtype
         from pandas.core.arrays.string_ import StringDtype
 
-        if isinstance(inferred_dtype, PandasExtensionDtype):
-            base_dtype = inferred_dtype.base
-        elif isinstance(inferred_dtype, (BaseMaskedDtype, ArrowDtype)):
-            base_dtype = inferred_dtype.numpy_dtype
-        elif isinstance(inferred_dtype, StringDtype):
-            base_dtype = np.dtype(str)
-        else:
-            # error: Incompatible types in assignment (expression has type
-            # "Union[str, Any, dtype[Any], ExtensionDtype]",
-            # variable has type "Union[dtype[Any], ExtensionDtype, None]")
-            base_dtype = inferred_dtype  # type: ignore[assignment]
-        pa_type = to_pyarrow_type(base_dtype)
-        if pa_type is not None:
-            inferred_dtype = ArrowDtype(pa_type)
+        if (
+            (convert_integer and inferred_dtype.kind in "iu")
+            or (convert_floating and inferred_dtype.kind in "fc")
+            or (convert_boolean and inferred_dtype.kind == "b")
+            or (convert_string and is_string_dtype(inferred_dtype))
+            or (
+                inferred_dtype.kind not in "iufcb"
+                and not is_string_dtype(inferred_dtype)
+            )
+        ):
+            if isinstance(inferred_dtype, PandasExtensionDtype):
+                base_dtype = inferred_dtype.base
+            elif isinstance(inferred_dtype, (BaseMaskedDtype, ArrowDtype)):
+                base_dtype = inferred_dtype.numpy_dtype
+            elif isinstance(inferred_dtype, StringDtype):
+                base_dtype = np.dtype(str)
+            else:
+                # error: Incompatible types in assignment (expression has type
+                # "Union[str, Any, dtype[Any], ExtensionDtype]",
+                # variable has type "Union[dtype[Any], ExtensionDtype, None]")
+                base_dtype = inferred_dtype  # type: ignore[assignment]
+            pa_type = to_pyarrow_type(base_dtype)
+            if pa_type is not None:
+                inferred_dtype = ArrowDtype(pa_type)
 
     # 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

@@ -134,3 +134,17 @@ 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):
+        # GH#52872
+        pytest.importorskip("pyarrow")
+        df = pd.DataFrame({"a": [1, 2], "b": 1.5, "c": True, "d": "x"})
+        expected = df.copy()
+        result = df.convert_dtypes(
+            convert_floating=False,
+            convert_integer=False,
+            convert_boolean=False,
+            convert_string=False,
+            dtype_backend="pyarrow",
+        )
+        tm.assert_frame_equal(result, expected)