diff --git a/pandas/core/generic.py b/pandas/core/generic.py index 44cddd7bea81c..dee71a4f000e5 100644 --- a/pandas/core/generic.py +++ b/pandas/core/generic.py @@ -10640,6 +10640,7 @@ def mad(self, axis=None, skipna=None, level=None): name2=name2, axis_descr=axis_descr, notes="", + examples="", ) def sem( self, @@ -10662,6 +10663,7 @@ def sem( name2=name2, axis_descr=axis_descr, notes="", + examples="", ) def var( self, @@ -10680,11 +10682,12 @@ 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, notes=_std_notes, + examples=_std_examples, ) def std( self, @@ -11176,7 +11179,8 @@ def _doc_params(cls): Returns ------- {name1} or {name2} (if level specified) \ -{notes} +{notes}\ +{examples} """ _std_notes = """ @@ -11186,6 +11190,34 @@ 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}