DOC: Added MultiIndex Example for Series Min

pandas/core/generic.py

@@ -9602,7 +9602,7 @@ def compound(self, axis=None, skipna=None, level=None):
             """This method returns the minimum of the values in the object.
             If you want the *index* of the minimum, use ``idxmin``. This is
             the equivalent of the ``numpy.ndarray`` method ``argmin``.""",
-            nanops.nanmin)
+            nanops.nanmin, _min_examples)
 
     @classmethod
     def _add_series_only_operations(cls):
@@ -10397,43 +10397,50 @@ def _doc_parms(cls):
 Series([], dtype: bool)
 """
 
-_sum_examples = """\
+_shared_docs['stat_func_example'] = """\
 Examples
 --------
-``MultiIndex`` series example of monthly rainfall
+``MultiIndex`` series example.
 
->>> index = pd.MultiIndex.from_product(
-...     [['London', 'New York'], ['Jun', 'Jul', 'Aug']],
-...     names=['city', 'month'])
->>> s = pd.Series([47, 35, 54, 112, 117, 113], index=index)
+>>> index = pd.MultiIndex.from_arrays([
+...     ['Warm', 'Warm', 'Cold', 'Cold'],
+...     ['Dog', 'Falcon', 'Fish', 'Spider']],
+...     names=['Blooded', 'Animal'])
+>>> s = pd.Series([4, 2, 0, 8], name='Legs', index=index)
 >>> s
-city      month
-London    Jun       47
-          Jul       35
-          Aug       54
-New York  Jun      112
-          Jul      117
-          Aug      113
-dtype: int64
-
->>> s.sum()
-478
-
-Sum using level names, as well as indices
-
->>> s.sum(level='city')
-city
-London      136
-New York    342
-dtype: int64
-
->>> s.sum(level=1)
-month
-Jun    159
-Jul    152
-Aug    167
-dtype: int64
+Blooded  Animal
+Warm     Dog       4
+         Falcon    2
+Cold     Fish      0
+         Spider    8
+Name: Legs, dtype: int64
+
+>>> s.{stat_func}()
+{default_output}
+
+{verb} using level names, as well as indices.
+
+>>> s.{stat_func}(level='Blooded')
+Blooded
+Warm    {level_output_0}
+Cold    {level_output_1}
+Name: Legs, dtype: int64
+
+>>> s.{stat_func}(level=0)
+Blooded
+Warm    {level_output_0}
+Cold    {level_output_1}
+Name: Legs, dtype: int64
+"""
+
+_sum_examples = _shared_docs['stat_func_example'].format(
+    stat_func='sum',
+    verb='Sum',
+    default_output=14,
+    level_output_0=6,
+    level_output_1=8)
 
+_sum_examples += """
 By default, the sum of an empty or all-NA Series is ``0``.
 
 >>> pd.Series([]).sum()  # min_count=0 is the default
@@ -10455,6 +10462,20 @@ def _doc_parms(cls):
 nan
 """
 
+_max_examples = _shared_docs['stat_func_example'].format(
+    stat_func='max',
+    verb='Max',
+    default_output=8,
+    level_output_0=4,
+    level_output_1=8)
+
+_min_examples = _shared_docs['stat_func_example'].format(
+    stat_func='min',
+    verb='Min',
+    default_output=0,
+    level_output_0=2,
+    level_output_1=0)
+
 _prod_examples = """\
 Examples
 --------
@@ -10478,45 +10499,6 @@ def _doc_parms(cls):
 nan
 """
 
-_max_examples = """\
-Examples
---------
-``MultiIndex`` series example of monthly rainfall
-
->>> index = pd.MultiIndex.from_product(
-...     [['London', 'New York'], ['Jun', 'Jul', 'Aug']],
-...     names=['city', 'month'])
->>> s = pd.Series([47, 35, 54, 112, 117, 113], index=index)
->>> s
-city      month
-London    Jun       47
-          Jul       35
-          Aug       54
-New York  Jun      112
-          Jul      117
-          Aug      113
-dtype: int64
-
->>> s.max()
-117
-
-Max using level names, as well as indices
-
->>> s.max(level='city')
-city
-London       54
-New York    117
-dtype: int64
-
->>> s.max(level=1)
-month
-Jun    112
-Jul    117
-Aug    113
-dtype: int64
-"""
-
-
 _min_count_stub = """\
 min_count : int, default 0
     The required number of valid values to perform the operation. If fewer than