Backport PR pandas-dev#36444: BUG: inconsistent replace

Author: QuentinN42

doc/source/whatsnew/v1.1.3.rst

@@ -34,6 +34,7 @@ Fixed regressions
 - Fixed regression in :meth:`Series.__getitem__` incorrectly raising when the input was a tuple (:issue:`35534`)
 - Fixed regression in :meth:`Series.__getitem__` incorrectly raising when the input was a frozenset (:issue:`35747`)
 - Fixed regression in :meth:`read_excel` with ``engine="odf"`` caused ``UnboundLocalError`` in some cases where cells had nested child nodes (:issue:`36122`, :issue:`35802`)
+- Fixed regression in :meth:`DataFrame.replace` inconsistent replace when using a float in the replace method (:issue:`35376`)
 - Fixed regression in :class:`DataFrame` and :class:`Series` comparisons between numeric arrays and strings (:issue:`35700`, :issue:`36377`)
 - Fixed regression in :meth:`DataFrame.apply` with ``raw=True`` and user-function returning string (:issue:`35940`)
 - Fixed regression when setting empty :class:`DataFrame` column to a :class:`Series` in preserving name of index in frame (:issue:`36527`)

pandas/core/internals/blocks.py

@@ -36,6 +36,7 @@
     is_datetime64tz_dtype,
     is_dtype_equal,
     is_extension_array_dtype,
+    is_float,
     is_float_dtype,
     is_integer,
     is_integer_dtype,
@@ -1996,7 +1997,9 @@ def _can_hold_element(self, element: Any) -> bool:
                 and not issubclass(tipo.type, (np.datetime64, np.timedelta64))
                 and self.dtype.itemsize >= tipo.itemsize
             )
-        return is_integer(element)
+        # We have not inferred an integer from the dtype
+        # check if we have a builtin int or a float equal to an int
+        return is_integer(element) or (is_float(element) and element.is_integer())
 
 
 class DatetimeLikeBlockMixin:

pandas/tests/frame/methods/test_replace.py

@@ -974,6 +974,31 @@ def test_replace_for_new_dtypes(self, datetime_frame):
                     }
                 ),
             ),
+            # GH 35376
+            (
+                DataFrame([[1, 1.0], [2, 2.0]]),
+                1.0,
+                5,
+                DataFrame([[5, 5.0], [2, 2.0]]),
+            ),
+            (
+                DataFrame([[1, 1.0], [2, 2.0]]),
+                1,
+                5,
+                DataFrame([[5, 5.0], [2, 2.0]]),
+            ),
+            (
+                DataFrame([[1, 1.0], [2, 2.0]]),
+                1.0,
+                5.0,
+                DataFrame([[5, 5.0], [2, 2.0]]),
+            ),
+            (
+                DataFrame([[1, 1.0], [2, 2.0]]),
+                1,
+                5.0,
+                DataFrame([[5, 5.0], [2, 2.0]]),
+            ),
         ],
     )
     def test_replace_dtypes(self, frame, to_replace, value, expected):