diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 2a34c71412789..cc9a980a7c7d4 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -9478,7 +9478,7 @@ def _series_round(ser: Series, decimals: int):
         if len(new_cols) > 0:
             return self._constructor(
                 concat(new_cols, axis=1), index=self.index, columns=self.columns
-            )
+            ).__finalize__(self, method="round")
         else:
             return self
 
@@ -9866,7 +9866,8 @@ def count(
                 FutureWarning,
                 stacklevel=find_stack_level(),
             )
-            return self._count_level(level, axis=axis, numeric_only=numeric_only)
+            res = self._count_level(level, axis=axis, numeric_only=numeric_only)
+            return res.__finalize__(self, method="count")
 
         if numeric_only:
             frame = self._get_numeric_data()
@@ -9889,7 +9890,7 @@ def count(
                     counts, index=frame._get_agg_axis(axis)
                 )
 
-        return result.astype("int64")
+        return result.astype("int64").__finalize__(self, method="count")
 
     def _count_level(self, level: Level, axis: int = 0, numeric_only: bool = False):
         if numeric_only:
@@ -10519,13 +10520,14 @@ def quantile(
                     dtype = cdtype
 
             if is_list_like(q):
-                return self._constructor([], index=q, columns=cols, dtype=dtype)
+                res = self._constructor([], index=q, columns=cols, dtype=dtype)
+                return res.__finalize__(self, method="quantile")
             return self._constructor_sliced([], index=cols, name=q, dtype=dtype)
 
         res = data._mgr.quantile(qs=q, axis=1, interpolation=interpolation)
 
         result = self._constructor(res)
-        return result
+        return result.__finalize__(self, method="quantile")
 
     @doc(NDFrame.asfreq, **_shared_doc_kwargs)
     def asfreq(
@@ -10742,7 +10744,7 @@ def isin(self, values) -> DataFrame:
             from pandas.core.reshape.concat import concat
 
             values = collections.defaultdict(list, values)
-            return concat(
+            result = concat(
                 (
                     self.iloc[:, [i]].isin(values[col])
                     for i, col in enumerate(self.columns)
@@ -10752,11 +10754,11 @@ def isin(self, values) -> DataFrame:
         elif isinstance(values, Series):
             if not values.index.is_unique:
                 raise ValueError("cannot compute isin with a duplicate axis.")
-            return self.eq(values.reindex_like(self), axis="index")
+            result = self.eq(values.reindex_like(self), axis="index")
         elif isinstance(values, DataFrame):
             if not (values.columns.is_unique and values.index.is_unique):
                 raise ValueError("cannot compute isin with a duplicate axis.")
-            return self.eq(values.reindex_like(self))
+            result = self.eq(values.reindex_like(self))
         else:
             if not is_list_like(values):
                 raise TypeError(
@@ -10764,11 +10766,12 @@ def isin(self, values) -> DataFrame:
                     "to be passed to DataFrame.isin(), "
                     f"you passed a '{type(values).__name__}'"
                 )
-            return self._constructor(
+            result = self._constructor(
                 algorithms.isin(self.values.ravel(), values).reshape(self.shape),
                 self.index,
                 self.columns,
             )
+        return result.__finalize__(self, method="isin")
 
     # ----------------------------------------------------------------------
     # Add index and columns
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 4971c7f34cfdb..a497475ebd182 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -1646,7 +1646,7 @@ def __abs__(self: NDFrameT) -> NDFrameT:
 
     @final
     def __round__(self: NDFrameT, decimals: int = 0) -> NDFrameT:
-        return self.round(decimals)
+        return self.round(decimals).__finalize__(self, method="__round__")
 
     # -------------------------------------------------------------------------
     # Label or Level Combination Helpers
@@ -10383,7 +10383,7 @@ def pct_change(
             # We want to restore the original index
             rs = rs.loc[~rs.index.duplicated()]
             rs = rs.reindex_like(data)
-        return rs
+        return rs.__finalize__(self, method="pct_change")
 
     @final
     def _agg_by_level(
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 596953652d2ff..614f3525bb539 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -1799,7 +1799,8 @@ def to_frame(self, name: Hashable = lib.no_default) -> DataFrame:
             columns = Index([name])
 
         mgr = self._mgr.to_2d_mgr(columns)
-        return self._constructor_expanddim(mgr)
+        df = self._constructor_expanddim(mgr)
+        return df.__finalize__(self, method="to_frame")
 
     def _set_name(self, name, inplace=False) -> Series:
         """
diff --git a/pandas/tests/generic/test_duplicate_labels.py b/pandas/tests/generic/test_duplicate_labels.py
index 43cd3039870d0..189c5382ef114 100644
--- a/pandas/tests/generic/test_duplicate_labels.py
+++ b/pandas/tests/generic/test_duplicate_labels.py
@@ -63,10 +63,9 @@ def test_preserved_frame(self):
         assert df.loc[["a"]].flags.allows_duplicate_labels is False
         assert df.loc[:, ["A", "B"]].flags.allows_duplicate_labels is False
 
-    @not_implemented
     def test_to_frame(self):
-        s = pd.Series(dtype=float).set_flags(allows_duplicate_labels=False)
-        assert s.to_frame().flags.allows_duplicate_labels is False
+        ser = pd.Series(dtype=float).set_flags(allows_duplicate_labels=False)
+        assert ser.to_frame().flags.allows_duplicate_labels is False
 
     @pytest.mark.parametrize("func", ["add", "sub"])
     @pytest.mark.parametrize(
diff --git a/pandas/tests/generic/test_finalize.py b/pandas/tests/generic/test_finalize.py
index 403e5c6c7daf7..cf92cd55a720e 100644
--- a/pandas/tests/generic/test_finalize.py
+++ b/pandas/tests/generic/test_finalize.py
@@ -38,14 +38,9 @@
     (pd.Series, ([0],), operator.methodcaller("take", [])),
     (pd.Series, ([0],), operator.methodcaller("__getitem__", [True])),
     (pd.Series, ([0],), operator.methodcaller("repeat", 2)),
-    pytest.param(
-        (pd.Series, ([0],), operator.methodcaller("reset_index")),
-        marks=pytest.mark.xfail,
-    ),
+    (pd.Series, ([0],), operator.methodcaller("reset_index")),
     (pd.Series, ([0],), operator.methodcaller("reset_index", drop=True)),
-    pytest.param(
-        (pd.Series, ([0],), operator.methodcaller("to_frame")), marks=pytest.mark.xfail
-    ),
+    (pd.Series, ([0],), operator.methodcaller("to_frame")),
     (pd.Series, ([0, 0],), operator.methodcaller("drop_duplicates")),
     (pd.Series, ([0, 0],), operator.methodcaller("duplicated")),
     (pd.Series, ([0, 0],), operator.methodcaller("round")),
@@ -205,7 +200,6 @@
     ),
     pytest.param(
         (pd.DataFrame, frame_data, operator.methodcaller("round", 2)),
-        marks=not_implemented_mark,
     ),
     pytest.param(
         (pd.DataFrame, frame_data, operator.methodcaller("corr")),
@@ -228,12 +222,10 @@
     ),
     pytest.param(
         (pd.DataFrame, frame_data, operator.methodcaller("count")),
-        marks=not_implemented_mark,
     ),
     pytest.param(
         (pd.DataFrame, frame_mi_data, operator.methodcaller("count", level="A")),
         marks=[
-            not_implemented_mark,
             pytest.mark.filterwarnings("ignore:Using the level keyword:FutureWarning"),
         ],
     ),
@@ -261,7 +253,6 @@
     ),
     pytest.param(
         (pd.DataFrame, frame_data, operator.methodcaller("quantile", q=[0.25, 0.75])),
-        marks=not_implemented_mark,
     ),
     pytest.param(
         (pd.DataFrame, frame_data, operator.methodcaller("quantile")),
@@ -279,11 +270,9 @@
     ),
     pytest.param(
         (pd.DataFrame, frame_mi_data, operator.methodcaller("isin", [1])),
-        marks=not_implemented_mark,
     ),
     pytest.param(
         (pd.DataFrame, frame_mi_data, operator.methodcaller("isin", pd.Series([1]))),
-        marks=not_implemented_mark,
     ),
     pytest.param(
         (
@@ -291,7 +280,6 @@
             frame_mi_data,
             operator.methodcaller("isin", pd.DataFrame({"A": [1]})),
         ),
-        marks=not_implemented_mark,
     ),
     (pd.DataFrame, frame_data, operator.methodcaller("swapaxes", 0, 1)),
     (pd.DataFrame, frame_mi_data, operator.methodcaller("droplevel", "A")),
@@ -300,10 +288,7 @@
         (pd.DataFrame, frame_data, operator.methodcaller("squeeze")),
         marks=not_implemented_mark,
     ),
-    pytest.param(
-        (pd.Series, ([1, 2],), operator.methodcaller("squeeze"))
-        # marks=not_implemented_mark,
-    ),
+    (pd.Series, ([1, 2],), operator.methodcaller("squeeze")),
     (pd.Series, ([1, 2],), operator.methodcaller("rename_axis", index="a")),
     (pd.DataFrame, frame_data, operator.methodcaller("rename_axis", columns="a")),
     # Unary ops
@@ -315,7 +300,7 @@
     (pd.Series, [1], operator.inv),
     (pd.DataFrame, frame_data, abs),
     (pd.Series, [1], abs),
-    pytest.param((pd.DataFrame, frame_data, round), marks=not_implemented_mark),
+    pytest.param((pd.DataFrame, frame_data, round)),
     (pd.Series, [1], round),
     (pd.DataFrame, frame_data, operator.methodcaller("take", [0, 0])),
     (pd.DataFrame, frame_mi_data, operator.methodcaller("xs", "a")),
@@ -461,10 +446,7 @@
         marks=not_implemented_mark,
     ),
     (pd.Series, ([1, 2],), operator.methodcaller("pct_change")),
-    pytest.param(
-        (pd.DataFrame, frame_data, operator.methodcaller("pct_change")),
-        marks=not_implemented_mark,
-    ),
+    (pd.DataFrame, frame_data, operator.methodcaller("pct_change")),
     (pd.Series, ([1],), operator.methodcaller("transform", lambda x: x - x.min())),
     pytest.param(
         (