From b639ded7505fa62c34935425876ca73dbc43eeff Mon Sep 17 00:00:00 2001
From: Patrick Hoefler <patrick_hoefler@gmx.net>
Date: Tue, 20 Jun 2023 22:34:15 +0200
Subject: [PATCH] CoW: Series.transform not respecting CoW

---
 doc/source/whatsnew/v2.1.0.rst         |  1 +
 pandas/core/series.py                  |  3 ++-
 pandas/tests/copy_view/test_methods.py | 26 ++++++++++++++++++++++++++
 3 files changed, 29 insertions(+), 1 deletion(-)

diff --git a/doc/source/whatsnew/v2.1.0.rst b/doc/source/whatsnew/v2.1.0.rst
index 44691e4265f5b..140e9d5b2205b 100644
--- a/doc/source/whatsnew/v2.1.0.rst
+++ b/doc/source/whatsnew/v2.1.0.rst
@@ -19,6 +19,7 @@ Enhancements
 Copy-on-Write improvements
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
 
+- :meth:`Series.transform` not respecting Copy-on-Write when ``func`` modifies :class:`Series` inplace (:issue:`53747`)
 - Calling :meth:`Index.values` will now return a read-only NumPy array (:issue:`53704`)
 - Setting a :class:`Series` into a :class:`DataFrame` now creates a lazy instead of a deep copy (:issue:`53142`)
 - The :class:`DataFrame` constructor, when constructing a DataFrame from a dictionary
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 959c153561572..40c19a57466fe 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -4499,7 +4499,8 @@ def transform(
     ) -> DataFrame | Series:
         # Validate axis argument
         self._get_axis_number(axis)
-        result = SeriesApply(self, func=func, args=args, kwargs=kwargs).transform()
+        ser = self.copy(deep=False) if using_copy_on_write() else self
+        result = SeriesApply(ser, func=func, args=args, kwargs=kwargs).transform()
         return result
 
     def apply(
diff --git a/pandas/tests/copy_view/test_methods.py b/pandas/tests/copy_view/test_methods.py
index 3af47d0b37338..294fd5636b7b5 100644
--- a/pandas/tests/copy_view/test_methods.py
+++ b/pandas/tests/copy_view/test_methods.py
@@ -1764,6 +1764,32 @@ def test_transpose_ea_single_column(using_copy_on_write):
     assert not np.shares_memory(get_array(df, "a"), get_array(result, 0))
 
 
+def test_transform_frame(using_copy_on_write):
+    df = DataFrame({"a": [1, 2, 3], "b": 1})
+    df_orig = df.copy()
+
+    def func(ser):
+        ser.iloc[0] = 100
+        return ser
+
+    df.transform(func)
+    if using_copy_on_write:
+        tm.assert_frame_equal(df, df_orig)
+
+
+def test_transform_series(using_copy_on_write):
+    ser = Series([1, 2, 3])
+    ser_orig = ser.copy()
+
+    def func(ser):
+        ser.iloc[0] = 100
+        return ser
+
+    ser.transform(func)
+    if using_copy_on_write:
+        tm.assert_series_equal(ser, ser_orig)
+
+
 def test_count_read_only_array():
     df = DataFrame({"a": [1, 2], "b": 3})
     result = df.count()