BUG: Fix assert_frame_equal dtype handling when check_dtype=False (#61473)

Author: iabhi4

doc/source/whatsnew/v3.0.0.rst

@@ -857,6 +857,7 @@ Sparse
 ExtensionArray
 ^^^^^^^^^^^^^^
 - Bug in :class:`Categorical` when constructing with an :class:`Index` with :class:`ArrowDtype` (:issue:`60563`)
+- Bug in :func:`assert_frame_equal` with ``check_dtype=False`` that failed when comparing columns containing ``pd.NA`` with ``Int32`` and ``object`` dtypes. Now handles such comparisons by coercing to ``dtype="object"`` internally. (:issue:`61473`)
 - Bug in :meth:`.arrays.ArrowExtensionArray.__setitem__` which caused wrong behavior when using an integer array with repeated values as a key (:issue:`58530`)
 - Bug in :meth:`ArrowExtensionArray.factorize` where NA values were dropped when input was dictionary-encoded even when dropna was set to False(:issue:`60567`)
 - Bug in :meth:`api.types.is_datetime64_any_dtype` where a custom :class:`ExtensionDtype` would return ``False`` for array-likes (:issue:`57055`)

pandas/_testing/asserters.py

@@ -1014,6 +1014,7 @@ def assert_series_equal(
             pass
         else:
             assert_attr_equal("dtype", left, right, obj=f"Attributes of {obj}")
+
     if check_exact:
         left_values = left._values
         right_values = right._values
@@ -1030,11 +1031,18 @@ def assert_series_equal(
             )
         else:
             # convert both to NumPy if not, check_dtype would raise earlier
-            lv, rv = left_values, right_values
-            if isinstance(left_values, ExtensionArray):
-                lv = left_values.to_numpy()
-            if isinstance(right_values, ExtensionArray):
-                rv = right_values.to_numpy()
+            lv, rv = left._values, right._values
+            if not check_dtype and not (
+                isinstance(lv, ExtensionArray) and isinstance(rv, ExtensionArray)
+            ):
+                lv = left.to_numpy(dtype="object")
+                rv = right.to_numpy(dtype="object")
+            else:
+                if isinstance(lv, ExtensionArray):
+                    lv = rv.to_numpy()
+                if isinstance(rv, ExtensionArray):
+                    rv = rv.to_numpy()
+
             assert_numpy_array_equal(
                 lv,
                 rv,
@@ -1105,9 +1113,16 @@ def assert_series_equal(
             obj=str(obj),
         )
     else:
+        lv, rv = left._values, right._values
+        if not check_dtype and not (
+            isinstance(left._values, ExtensionArray)
+            and isinstance(right._values, ExtensionArray)
+        ):
+            lv = left.to_numpy(dtype="object")
+            rv = right.to_numpy(dtype="object")
         _testing.assert_almost_equal(
-            left._values,
-            right._values,
+            lv,
+            rv,
             rtol=rtol,
             atol=atol,
             check_dtype=bool(check_dtype),

pandas/tests/util/test_assert_frame_equal.py

@@ -395,3 +395,11 @@ def test_assert_frame_equal_set_mismatch():
     msg = r'DataFrame.iloc\[:, 0\] \(column name="set_column"\) values are different'
     with pytest.raises(AssertionError, match=msg):
         tm.assert_frame_equal(df1, df2)
+
+
+def test_assert_frame_equal_with_pdNA_and_check_dtype_false():
+    # GH#61473
+    df1 = DataFrame({"x": pd.Series([pd.NA], dtype="Int32")})
+    df2 = DataFrame({"x": pd.Series([pd.NA], dtype="object")})
+
+    tm.assert_frame_equal(df1, df2, check_dtype=False)