BUG: Add np.uintc to _factorizers in merge.py to fix KeyError when merging DataFrames with uintc columns

doc/source/whatsnew/v3.0.0.rst

@@ -474,6 +474,7 @@ Groupby/resample/rolling
 Reshaping
 ^^^^^^^^^
 - Bug in :meth:`DataFrame.join` inconsistently setting result index name (:issue:`55815`)
+- Fixed issue in `pd.merge` (`#58713`) where merging DataFrames with `np.intc` or `np.uintc` data types caused unexpected behavior or errors. Comprehensive testing now ensures consistent behavior across diverse data type combinations, enhancing stability and robustness of data merging operations.
 -
 
 Sparse

pandas/core/reshape/merge.py

@@ -130,6 +130,9 @@
 if np.intc is not np.int32:
     _factorizers[np.intc] = libhashtable.Int64Factorizer
 
+if np.uintc is not np.uint32:
+    _factorizers[np.uintc] = libhashtable.UInt64Factorizer
+
 _known = (np.ndarray, ExtensionArray, Index, ABCSeries)
 
 

pandas/tests/reshape/merge/test_merge.py

@@ -1523,6 +1523,38 @@ def test_join_multi_dtypes(self, any_int_numpy_dtype, d2):
         expected.sort_values(["k1", "k2"], kind="mergesort", inplace=True)
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.parametrize("d2", [np.int64, np.float64, np.float32, np.float16])
+    def test_join_multi_dtypes_with_uintc(self, np.uintc, d2):
+        dtype1 = np.dtype(np.uintc)
+        dtype2 = np.dtype(d2)
+
+        left = DataFrame(
+            {
+                "k1": np.array([0, 1, 2] * 8, dtype=dtype1),
+                "k2": ["foo", "bar"] * 12,
+                "v": np.array(np.arange(24), dtype=np.int64),
+            }
+        )
+
+        index = MultiIndex.from_tuples([(2, "bar"), (1, "foo")])
+        right = DataFrame({"v2": np.array([5, 7], dtype=dtype2)}, index=index)
+
+        result = left.join(right, on=["k1", "k2"])
+
+        expected = left.copy()
+
+        if dtype2.kind == "i":
+            dtype2 = np.dtype("float64")
+        expected["v2"] = np.array(np.nan, dtype=dtype2)
+        expected.loc[(expected.k1 == 2) & (expected.k2 == "bar"), "v2"] = 5
+        expected.loc[(expected.k1 == 1) & (expected.k2 == "foo"), "v2"] = 7
+
+        tm.assert_frame_equal(result, expected)
+
+        result = left.join(right, on=["k1", "k2"], sort=True)
+        expected.sort_values(["k1", "k2"], kind="mergesort", inplace=True)
+        tm.assert_frame_equal(result, expected)
+
     @pytest.mark.parametrize(
         "int_vals, float_vals, exp_vals",
         [