BUG: DataFrame.update bool dtype being converted to object #55509

doc/source/whatsnew/v2.1.2.rst

@@ -43,6 +43,7 @@ Bug fixes
 - Fixed bug in :meth:`DataFrame.__setitem__` not inferring string dtype for zero-dimensional array with ``infer_string=True`` (:issue:`55366`)
 - Fixed bug in :meth:`DataFrame.idxmin` and :meth:`DataFrame.idxmax` raising for arrow dtypes (:issue:`55368`)
 - Fixed bug in :meth:`DataFrame.interpolate` raising incorrect error message (:issue:`55347`)
+- Fixed bug in :meth:`DataFrame.update` bool dtype being converted to object (:issue:`55509`)
 - Fixed bug in :meth:`Index.insert` raising when inserting ``None`` into :class:`Index` with ``dtype="string[pyarrow_numpy]"`` (:issue:`55365`)
 - Fixed bug in :meth:`Series.all`  and :meth:`Series.any` not treating missing values correctly for ``dtype="string[pyarrow_numpy]"`` (:issue:`55367`)
 - Fixed bug in :meth:`Series.floordiv` for :class:`ArrowDtype` (:issue:`55561`)

pandas/core/frame.py

@@ -8,6 +8,7 @@
 alignment and a host of useful data manipulation methods having to do with the
 labeling information
 """
+
 from __future__ import annotations
 
 import collections
@@ -8764,11 +8765,30 @@ def update(
         if not isinstance(other, DataFrame):
             other = DataFrame(other)
 
-        other = other.reindex(self.index)
+        indexes_intersection = other.index.intersection(
+            self.index
+        )  # order is important
+        if not len(indexes_intersection):
+            raise ValueError(
+                "Can't update dataframe when other has no index in common with "
+                "this dataframe."
+            )
+
+        if other.index.is_unique:
+            indexes_this = indexes_intersection
+            if self.index.is_unique:
+                indexes_that = indexes_intersection
+            else:
+                full_indexes_this = self.index.take(
+                    self.index.get_indexer_for(indexes_intersection)
+                )
+                indexes_that = indexes_intersection.reindex(full_indexes_this)[0]
+        else:
+            raise ValueError("Update not allowed with duplicate indexes on other.")
 
         for col in self.columns.intersection(other.columns):
-            this = self[col]._values
-            that = other[col]._values
+            this = self.loc[indexes_this, col]._values
+            that = other.loc[indexes_that, col]._values
 
             if filter_func is not None:
                 mask = ~filter_func(this) | isna(that)
@@ -8788,7 +8808,7 @@ def update(
             if mask.all():
                 continue
 
-            self.loc[:, col] = self[col].where(mask, that)
+            self.loc[indexes_this, col] = self.loc[indexes_this, col].where(mask, that)
 
     # ----------------------------------------------------------------------
     # Data reshaping
@@ -10218,9 +10238,11 @@ def _append(
 
             index = Index(
                 [other.name],
-                name=self.index.names
-                if isinstance(self.index, MultiIndex)
-                else self.index.name,
+                name=(
+                    self.index.names
+                    if isinstance(self.index, MultiIndex)
+                    else self.index.name
+                ),
             )
             row_df = other.to_frame().T
             # infer_objects is needed for

pandas/tests/frame/methods/test_update.py

@@ -184,3 +184,47 @@ 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_df, value_other, dtype",
+        [
+            (True, False, bool),
+            (1, 2, int),
+            (np.uint64(1), np.uint(2), np.dtype("uint64")),
+            (1.0, 2.0, float),
+            (1.0 + 1j, 2.0 + 2j, complex),
+            ("a", "b", pd.StringDtype()),
+            (
+                pd.to_timedelta("1 ms"),
+                pd.to_timedelta("2 ms"),
+                np.dtype("timedelta64[ns]"),
+            ),
+            (
+                np.datetime64("2000-01-01T00:00:00"),
+                np.datetime64("2000-01-02T00:00:00"),
+                np.dtype("datetime64[ns]"),
+            ),
+        ],
+    )
+    def test_update_preserve_dtype(self, value_df, value_other, dtype):
+        # GH#55509
+        df = DataFrame({"a": [value_df] * 2}, index=[1, 2])
+        other = DataFrame({"a": [value_other]}, index=[1])
+        expected = DataFrame({"a": [value_other, value_df]}, index=[1, 2])
+        df.update(other)
+        tm.assert_frame_equal(df, expected)
+
+    def test_update_raises_on_duplicate_argument_index(self):
+        # GH#55509
+        df = DataFrame({"a": [1, 1]}, index=[1, 2])
+        other = DataFrame({"a": [2, 3]}, index=[1, 1])
+        with pytest.raises(ValueError, match="duplicate index"):
+            df.update(other)
+
+    def test_update_on_duplicate_frame_unique_argument_index(self):
+        # GH#55509
+        df = DataFrame({"a": [1, 1, 1]}, index=[1, 1, 2])
+        other = DataFrame({"a": [2, 3]}, index=[1, 2])
+        expected = DataFrame({"a": [2, 2, 3]}, index=[1, 1, 2])
+        df.update(other)
+        tm.assert_frame_equal(df, expected)