BUG: Outer/right merge with EA dtypes cast to object (#43152)

Author: debnathshoham

doc/source/whatsnew/v1.3.3.rst

@@ -17,6 +17,7 @@ Fixed regressions
 - Fixed regression in :class:`DataFrame` constructor failing to broadcast for defined :class:`Index` and len one list of :class:`Timestamp` (:issue:`42810`)
 - Performance regression in :meth:`core.window.ewm.ExponentialMovingWindow.mean` (:issue:`42333`)
 - Fixed regression in :meth:`.GroupBy.agg` incorrectly raising in some cases (:issue:`42390`)
+- Fixed regression in :meth:`merge` where ``on`` columns with ``ExtensionDtype`` or ``bool`` data types were cast to ``object`` in ``right`` and ``outer`` merge (:issue:`40073`)
 - Fixed regression in :meth:`RangeIndex.where` and :meth:`RangeIndex.putmask` raising ``AssertionError`` when result did not represent a :class:`RangeIndex` (:issue:`43240`)
 - Fixed regression in :meth:`read_parquet` where the ``fastparquet`` engine would not work properly with fastparquet 0.7.0 (:issue:`43075`)
 

pandas/core/reshape/merge.py

@@ -70,6 +70,7 @@
     Categorical,
     Index,
     MultiIndex,
+    Series,
 )
 from pandas.core import groupby
 import pandas.core.algorithms as algos
@@ -81,10 +82,7 @@
 from pandas.core.sorting import is_int64_overflow_possible
 
 if TYPE_CHECKING:
-    from pandas import (
-        DataFrame,
-        Series,
-    )
+    from pandas import DataFrame
     from pandas.core.arrays import DatetimeArray
 
 
@@ -904,17 +902,22 @@ def _maybe_add_join_keys(
                 # error: Item "bool" of "Union[Any, bool]" has no attribute "all"
                 if mask_left.all():  # type: ignore[union-attr]
                     key_col = Index(rvals)
+                    result_dtype = rvals.dtype
                 # error: Item "bool" of "Union[Any, bool]" has no attribute "all"
                 elif (
                     right_indexer is not None
                     and mask_right.all()  # type: ignore[union-attr]
                 ):
                     key_col = Index(lvals)
+                    result_dtype = lvals.dtype
                 else:
                     key_col = Index(lvals).where(~mask_left, rvals)
+                    result_dtype = lvals.dtype
 
                 if result._is_label_reference(name):
-                    result[name] = key_col
+                    result[name] = Series(
+                        key_col, dtype=result_dtype, index=result.index
+                    )
                 elif result._is_level_reference(name):
                     if isinstance(result.index, MultiIndex):
                         key_col.name = name

pandas/tests/reshape/merge/test_merge.py

@@ -356,8 +356,8 @@ def test_merge_join_key_dtype_cast(self):
         df = merge(df1, df2, how="outer")
 
         # GH13169
-        # this really should be bool
-        assert df["key"].dtype == "object"
+        # GH#40073
+        assert df["key"].dtype == "bool"
 
         df1 = DataFrame({"val": [1]})
         df2 = DataFrame({"val": [2]})
@@ -368,10 +368,12 @@ def test_merge_join_key_dtype_cast(self):
 
     def test_handle_join_key_pass_array(self):
         left = DataFrame(
-            {"key": [1, 1, 2, 2, 3], "value": np.arange(5)}, columns=["value", "key"]
+            {"key": [1, 1, 2, 2, 3], "value": np.arange(5)},
+            columns=["value", "key"],
+            dtype="int64",
         )
-        right = DataFrame({"rvalue": np.arange(6)})
-        key = np.array([1, 1, 2, 3, 4, 5])
+        right = DataFrame({"rvalue": np.arange(6)}, dtype="int64")
+        key = np.array([1, 1, 2, 3, 4, 5], dtype="int64")
 
         merged = merge(left, right, left_on="key", right_on=key, how="outer")
         merged2 = merge(right, left, left_on=key, right_on="key", how="outer")
@@ -1644,6 +1646,57 @@ def test_merge_incompat_dtypes_error(self, df1_vals, df2_vals):
         with pytest.raises(ValueError, match=msg):
             merge(df2, df1, on=["A"])
 
+    @pytest.mark.parametrize(
+        "expected_data, how",
+        [
+            ([1, 2], "outer"),
+            ([], "inner"),
+            ([2], "right"),
+            ([1], "left"),
+        ],
+    )
+    def test_merge_EA_dtype(self, any_numeric_ea_dtype, how, expected_data):
+        # GH#40073
+        d1 = DataFrame([(1,)], columns=["id"], dtype=any_numeric_ea_dtype)
+        d2 = DataFrame([(2,)], columns=["id"], dtype=any_numeric_ea_dtype)
+        result = merge(d1, d2, how=how)
+        expected = DataFrame(expected_data, columns=["id"], dtype=any_numeric_ea_dtype)
+        tm.assert_frame_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "expected_data, how",
+        [
+            (["a", "b"], "outer"),
+            ([], "inner"),
+            (["b"], "right"),
+            (["a"], "left"),
+        ],
+    )
+    def test_merge_string_dtype(self, how, expected_data, any_string_dtype):
+        # GH#40073
+        d1 = DataFrame([("a",)], columns=["id"], dtype=any_string_dtype)
+        d2 = DataFrame([("b",)], columns=["id"], dtype=any_string_dtype)
+        result = merge(d1, d2, how=how)
+        expected = DataFrame(expected_data, columns=["id"], dtype=any_string_dtype)
+        tm.assert_frame_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "how, expected_data",
+        [
+            ("inner", [[True, 1, 4], [False, 5, 3]]),
+            ("outer", [[True, 1, 4], [False, 5, 3]]),
+            ("left", [[True, 1, 4], [False, 5, 3]]),
+            ("right", [[False, 5, 3], [True, 1, 4]]),
+        ],
+    )
+    def test_merge_bool_dtype(self, how, expected_data):
+        # GH#40073
+        df1 = DataFrame({"A": [True, False], "B": [1, 5]})
+        df2 = DataFrame({"A": [False, True], "C": [3, 4]})
+        result = merge(df1, df2, how=how)
+        expected = DataFrame(expected_data, columns=["A", "B", "C"])
+        tm.assert_frame_equal(result, expected)
+
 
 @pytest.fixture
 def left():