Backport PR pandas-dev#54755 on branch 2.1.x (BUG: merge raising for …

…ea int and numpy float) (pandas-dev#54779)

BUG: merge raising for ea int and numpy float (pandas-dev#54755)

* BUG: merge raising for ea int and numpy float

* Fix up mypy and add check

(cherry picked from commit 9939c32)

doc/source/whatsnew/v2.1.0.rst

@@ -816,6 +816,7 @@ Reshaping
 - Bug in :func:`merge_asof` raising ``KeyError`` for extension dtypes (:issue:`52904`)
 - Bug in :func:`merge_asof` raising ``ValueError`` for data backed by read-only ndarrays (:issue:`53513`)
 - Bug in :func:`merge_asof` with ``left_index=True`` or ``right_index=True`` with mismatched index dtypes giving incorrect results in some cases instead of raising ``MergeError`` (:issue:`53870`)
+- Bug in :func:`merge` when merging on integer ``ExtensionDtype`` and float NumPy dtype raising ``TypeError`` (:issue:`46178`)
 - Bug in :meth:`DataFrame.agg` and :meth:`Series.agg` on non-unique columns would return incorrect type when dist-like argument passed in (:issue:`51099`)
 - Bug in :meth:`DataFrame.combine_first` ignoring other's columns if ``other`` is empty (:issue:`53792`)
 - Bug in :meth:`DataFrame.idxmin` and :meth:`DataFrame.idxmax`, where the axis dtype would be lost for empty frames (:issue:`53265`)

pandas/core/reshape/merge.py

@@ -53,6 +53,7 @@
     ensure_object,
     is_bool,
     is_bool_dtype,
+    is_extension_array_dtype,
     is_float_dtype,
     is_integer,
     is_integer_dtype,
@@ -1385,6 +1386,21 @@ def _maybe_coerce_merge_keys(self) -> None:
                 if lk.dtype.kind == rk.dtype.kind:
                     continue
 
+                if is_extension_array_dtype(lk.dtype) and not is_extension_array_dtype(
+                    rk.dtype
+                ):
+                    ct = find_common_type([lk.dtype, rk.dtype])
+                    if is_extension_array_dtype(ct):
+                        rk = ct.construct_array_type()._from_sequence(rk)  # type: ignore[union-attr]  # noqa: E501
+                    else:
+                        rk = rk.astype(ct)  # type: ignore[arg-type]
+                elif is_extension_array_dtype(rk.dtype):
+                    ct = find_common_type([lk.dtype, rk.dtype])
+                    if is_extension_array_dtype(ct):
+                        lk = ct.construct_array_type()._from_sequence(lk)  # type: ignore[union-attr]  # noqa: E501
+                    else:
+                        lk = lk.astype(ct)  # type: ignore[arg-type]
+
                 # check whether ints and floats
                 if is_integer_dtype(rk.dtype) and is_float_dtype(lk.dtype):
                     # GH 47391 numpy > 1.24 will raise a RuntimeError for nan -> int

pandas/tests/reshape/merge/test_merge.py

@@ -2847,3 +2847,26 @@ def test_merge_multiindex_single_level():
 
     result = df.merge(df2, left_on=["col"], right_index=True, how="left")
     tm.assert_frame_equal(result, expected)
+
+
+def test_merge_ea_int_and_float_numpy():
+    # GH#46178
+    df1 = DataFrame([1.0, np.nan], dtype=pd.Int64Dtype())
+    df2 = DataFrame([1.5])
+    expected = DataFrame(columns=[0], dtype="Int64")
+
+    with tm.assert_produces_warning(UserWarning, match="You are merging"):
+        result = df1.merge(df2)
+    tm.assert_frame_equal(result, expected)
+
+    with tm.assert_produces_warning(UserWarning, match="You are merging"):
+        result = df2.merge(df1)
+    tm.assert_frame_equal(result, expected.astype("float64"))
+
+    df2 = DataFrame([1.0])
+    expected = DataFrame([1], columns=[0], dtype="Int64")
+    result = df1.merge(df2)
+    tm.assert_frame_equal(result, expected)
+
+    result = df2.merge(df1)
+    tm.assert_frame_equal(result, expected.astype("float64"))