diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 6de808d9a73fa..251bc6587872d 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -5995,33 +5995,6 @@ def _aggregate(self, arg, axis=0, *args, **kwargs):
 
     agg = aggregate
 
-    _transform_doc = dedent("""
-    Examples
-    --------
-    >>> df = pd.DataFrame(np.random.randn(10, 2), columns=['A', 'B'],
-    ...                   index=pd.date_range('1/1/2000', periods=10))
-    >>> df.iloc[3:7] = np.nan
-
-    >>> df.transform(lambda x: (x - x.mean()) / x.std())
-                       A         B
-    2000-01-01  0.579457  1.236184
-    2000-01-02  0.370357 -0.605875
-    2000-01-03  1.455756 -0.277446
-    2000-01-04       NaN       NaN
-    2000-01-05       NaN       NaN
-    2000-01-06       NaN       NaN
-    2000-01-07       NaN       NaN
-    2000-01-08 -0.498658  1.274522
-    2000-01-09 -0.540524 -1.012676
-    2000-01-10 -1.366388 -0.614710
-
-    See also
-    --------
-    pandas.DataFrame.aggregate
-    pandas.DataFrame.apply
-    """)
-
-    @Appender(_transform_doc)
     @Appender(_shared_docs['transform'] % _shared_doc_kwargs)
     def transform(self, func, axis=0, *args, **kwargs):
         axis = self._get_axis_number(axis)
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 23f14aaa02c75..10761ca5daf0b 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -4583,9 +4583,6 @@ def pipe(self, func, *args, **kwargs):
     func : function, string, list of string/functions or dictionary
         Function to use for transforming the data. If a function, must either
         work when passed a %(klass)s or when passed to %(klass)s.apply.
-        The function (or each function in a list/dict) must return an
-        object with the same length for the provided axis as the
-        calling %(klass)s.
 
         Accepted combinations are:
 
@@ -4606,6 +4603,43 @@ def pipe(self, func, *args, **kwargs):
     Raises
     ------
     ValueError: if the returned %(klass)s has a different length than self.
+
+    Examples
+    --------
+    >>> df = pd.DataFrame({'A': range(10), 'B': range(10, 0, -1)},
+    ...                   index=pd.date_range('1/1/2000', periods=10))
+    >>> df.iloc[3:7] = np.nan
+
+    >>> df.transform(lambda x: (x - x.mean()) / x.std())
+                       A         B
+    2000-01-01 -1.143001  1.143001
+    2000-01-02 -0.889001  0.889001
+    2000-01-03 -0.635001  0.635001
+    2000-01-04       NaN       NaN
+    2000-01-05       NaN       NaN
+    2000-01-06       NaN       NaN
+    2000-01-07       NaN       NaN
+    2000-01-08  0.635001 -0.635001
+    2000-01-09  0.889001 -0.889001
+    2000-01-10  1.143001 -1.143001
+
+    It is only required for the axis specified in the ``axis`` parameter
+    to have the same length for output and for self. The other axis may have a
+    different length:
+
+    >>> s = pd.Series(range(5))
+    >>> s.transform([np.sqrt, np.exp])
+           sqrt        exp
+    0  0.000000   1.000000
+    1  1.000000   2.718282
+    2  1.414214   7.389056
+    3  1.732051  20.085537
+    4  2.000000  54.598150
+
+    See also
+    --------
+    pandas.%(klass)s.aggregate
+    pandas.%(klass)s.apply
     """)
 
     # ----------------------------------------------------------------------
diff --git a/pandas/core/series.py b/pandas/core/series.py
index b8920619cf96b..cc22be9db95da 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -3098,33 +3098,6 @@ def aggregate(self, func, axis=0, *args, **kwargs):
 
     agg = aggregate
 
-    _transform_doc = dedent("""
-    Examples
-    --------
-    >>> s = pd.Series(range(5))
-    >>> s.transform(lambda x: (x - x.mean()) / x.std())
-    0   -1.264911
-    1   -0.632456
-    2    0.000000
-    3    0.632456
-    4    1.264911
-    dtype: float64
-
-    >>> s.transform([np.sqrt, np.exp])
-           sqrt        exp
-    0  0.000000   1.000000
-    1  1.000000   2.718282
-    2  1.414214   7.389056
-    3  1.732051  20.085537
-    4  2.000000  54.598150
-
-    See also
-    --------
-    pandas.Series.aggregate
-    pandas.Series.apply
-    """)
-
-    @Appender(_transform_doc)
     @Appender(generic._shared_docs['transform'] % _shared_doc_kwargs)
     def transform(self, func, axis=0, *args, **kwargs):
         # Validate the axis parameter