diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index c3ad87082c8ed..6e0e74249f61b 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -10685,10 +10685,11 @@ def var(
             _num_ddof_doc,
             desc="Return sample standard deviation over requested axis."
             "\n\nNormalized by N-1 by default. This can be changed using the "
-            "ddof argument",
+            "ddof argument.",
             name1=name1,
             name2=name2,
             axis_descr=axis_descr,
+            examples=_std_examples,
             notes=_std_notes,
         )
         def std(
@@ -11191,6 +11192,34 @@ def _doc_params(cls):
 To have the same behaviour as `numpy.std`, use `ddof=0` (instead of the
 default `ddof=1`)"""
 
+_std_examples = """
+Examples
+--------
+>>> df = pd.DataFrame({'person_id':[0,1,2,3],
+...                   'age':[21,25,62,43],
+...                   'height':[1.61,1.87,1.49,2.01]}
+...                  ).set_index('person_id')
+>>> df
+           age  height
+person_id
+0           21    1.61
+1           25    1.87
+2           62    1.49
+3           43    2.01
+
+The standard deviation of the columns can be found as follows.
+
+>>> df.std()
+age       18.786076
+height     0.237417
+
+Alternatively, `ddof=0` can be set to normalize by N instead of N-1.
+
+>>> df.std(ddof=0)
+age       16.269219
+height     0.205609
+"""
+
 _bool_doc = """
 {desc}
 
@@ -11771,7 +11800,6 @@ def _doc_params(cls):
     ``min_count`` non-NA values are present the result will be NA.
 """
 
-
 def _align_as_utc(
     left: NDFrameT, right: NDFrameT, join_index: Index | None
 ) -> tuple[NDFrameT, NDFrameT]: