BUG: DataFrame.update doesn't preserve dtypes

pandas/core/frame.py

@@ -81,6 +81,7 @@
     construct_1d_arraylike_from_scalar,
     construct_2d_arraylike_from_scalar,
     find_common_type,
+    find_result_type,
     infer_dtype_from_scalar,
     invalidate_string_dtypes,
     maybe_box_native,
@@ -100,6 +101,7 @@
     is_integer_dtype,
     is_iterator,
     is_list_like,
+    is_object_dtype,
     is_scalar,
     is_sequence,
     needs_i8_conversion,
@@ -8881,7 +8883,22 @@ def update(
             if mask.all():
                 continue
 
-            self.loc[:, col] = expressions.where(mask, this, that)
+            col_dtype = self[col].dtype
+            update_result = expressions.where(mask, this, that)
+            # Preserve dtype if udpate_result is all compatible with dtype
+            # This only happens for `bool` and `datetime64`
+            if col_dtype.kind in "bM" and is_object_dtype(update_result.dtype):
+                try:
+                    if all(
+                        col_dtype == find_result_type(col_dtype, x)
+                        for x in update_result
+                    ):
+                        update_result = update_result.astype(col_dtype)
+                except TypeError:
+                    # Do nothing if we cannot interpret `col_dtype` as a data type
+                    # e.g. `datetime64[ns, UTC]`
+                    pass
+            self.loc[:, col] = update_result
 
     # ----------------------------------------------------------------------
     # Data reshaping

pandas/tests/frame/methods/test_update.py

@@ -3,6 +3,8 @@
 
 import pandas.util._test_decorators as td
 
+from pandas.core.dtypes.common import pandas_dtype
+
 import pandas as pd
 from pandas import (
     DataFrame,
@@ -177,3 +179,47 @@ def test_update_dt_column_with_NaT_create_column(self):
             {"A": [1.0, 3.0], "B": [pd.NaT, pd.to_datetime("2016-01-01")]}
         )
         tm.assert_frame_equal(df, expected)
+
+    @pytest.mark.parametrize(
+        "value ,dtype",
+        [
+            (True, pandas_dtype("bool")),
+            (1, pandas_dtype("int64")),
+            (np.uint64(2), pandas_dtype("uint64")),
+            (3.0, pandas_dtype("float")),
+            (4.0 + 1j, pandas_dtype("complex")),
+            ("a", pandas_dtype("string")),
+            (pd.to_timedelta("1 ms"), pandas_dtype("timedelta64[ns]")),
+            (np.datetime64("2000-01-01T00:00:00"), pandas_dtype("datetime64[ns]")),
+            (pd.Timestamp("2000-01-01T00:00:00Z"), pandas_dtype("datetime64[ns, UTC]")),
+        ],
+    )
+    def test_update_preserve_dtype(self, value, dtype):
+        # GH#55509
+        df1 = (
+            DataFrame(
+                {
+                    "idx": [1, 2],
+                    "val": [value] * 2,
+                }
+            )
+            .set_index("idx")
+            .astype(dtype)
+        )
+        df2 = (
+            DataFrame(
+                {
+                    "idx": [1],
+                    "val": [value],
+                }
+            )
+            .set_index("idx")
+            .astype(dtype)
+        )
+
+        assert df1.dtypes["val"] == dtype
+        assert df2.dtypes["val"] == dtype
+
+        df1.update(df2)
+
+        assert df1.dtypes["val"] == dtype