Merge branch 'main' into issue_61917

Author: khemkaran10

pandas/_libs/internals.pyx

@@ -1006,8 +1006,12 @@ cdef class BlockValuesRefs:
 
 cdef extern from "Python.h":
     """
+    // python version < 3.14
     #if PY_VERSION_HEX < 0x030E0000
-    int __Pyx_PyUnstable_Object_IsUniqueReferencedTemporary(PyObject *ref);
+    // This function is unused and is declared to avoid a build warning
+    int __Pyx_PyUnstable_Object_IsUniqueReferencedTemporary(PyObject *ref) {
+        return Py_REFCNT(ref) == 1;
+    }
     #else
     #define __Pyx_PyUnstable_Object_IsUniqueReferencedTemporary \
         PyUnstable_Object_IsUniqueReferencedTemporary

pandas/core/arrays/datetimelike.py

@@ -2342,6 +2342,9 @@ def _with_freq(self, freq) -> Self:
 
     def _values_for_json(self) -> np.ndarray:
         # Small performance bump vs the base class which calls np.asarray(self)
+        if self.unit != "ns":
+            # GH#55827
+            return self.as_unit("ns")._values_for_json()
         if isinstance(self.dtype, np.dtype):
             return self._ndarray
         return super()._values_for_json()

pandas/tests/frame/methods/test_update.py

@@ -197,6 +197,7 @@ def test_update_dt_column_with_NaT_create_column(self):
                 np.datetime64("2000-01-02T00:00:00"),
                 np.dtype("datetime64[ns]"),
             ),
+            (1, 2, pd.Int64Dtype()),
         ],
     )
     def test_update_preserve_dtype(self, value_df, value_other, dtype):
@@ -228,3 +229,19 @@ def test_update_on_duplicate_frame_unique_argument_index(self):
         expected = DataFrame({"a": [2, 2, 3]}, index=[1, 1, 2], dtype=np.dtype("intc"))
         df.update(other)
         tm.assert_frame_equal(df, expected)
+
+    def test_update_preserve_mixed_dtypes(self):
+        # GH#44104
+        dtype1 = pd.Int64Dtype()
+        dtype2 = pd.StringDtype()
+        df = DataFrame({"a": [1, 2, 3], "b": ["x", "y", "z"]})
+        df = df.astype({"a": dtype1, "b": dtype2})
+
+        other = DataFrame({"a": [4, 5], "b": ["a", "b"]})
+        other = other.astype({"a": dtype1, "b": dtype2})
+
+        expected = DataFrame({"a": [4, 5, 3], "b": ["a", "b", "z"]})
+        expected = expected.astype({"a": dtype1, "b": dtype2})
+
+        df.update(other)
+        tm.assert_frame_equal(df, expected)

pandas/tests/io/json/test_pandas.py

@@ -135,12 +135,6 @@ def test_frame_non_unique_index_raises(self, orient):
         ],
     )
     def test_frame_non_unique_columns(self, orient, data, request):
-        if isinstance(data[0][0], Timestamp) and orient == "split":
-            mark = pytest.mark.xfail(
-                reason="GH#55827 non-nanosecond dt64 fails to round-trip"
-            )
-            request.applymarker(mark)
-
         df = DataFrame(data, index=[1, 2], columns=["x", "x"])
 
         expected_warning = None
@@ -162,10 +156,14 @@ def test_frame_non_unique_columns(self, orient, data, request):
                 # in milliseconds; these are internally stored in nanosecond,
                 # so divide to get where we need
                 # TODO: a to_epoch method would also solve; see GH 14772
-                expected.isetitem(0, expected.iloc[:, 0].astype(np.int64) // 1000000)
+                dta = expected.iloc[:, 0]._values
+                dta = dta.as_unit("ns")  # GH#55827
+                expected.isetitem(0, dta.astype(np.int64) // 1_000_000)
         elif orient == "split":
             expected = df
             expected.columns = ["x", "x.1"]
+            if expected["x"].dtype.kind == "M":
+                expected["x"] = expected["x"].astype("M8[ns]")  # GH#55827
 
         tm.assert_frame_equal(result, expected)