DOC: Adding examples to DataFrameGroupBy.rank #38972 (#42402)

* DOC: Adding examples to DataFrameGroupBy.rank #38972

* DOC: Adding examples to DataFrameGroupBy.rank #38972

* DOC: made the suggested changes

* DOC: changed as suggested

* DOC: changed as suggested

* DOC: updating with black output

* DOC: updating with black output

* DOC: corrected docstring order

Author: debnathshoham

pandas/core/groupby/groupby.py

@@ -2637,7 +2637,7 @@ def cumcount(self, ascending: bool = True):
 
     @final
     @Substitution(name="groupby")
-    @Appender(_common_see_also)
+    @Substitution(see_also=_common_see_also)
     def rank(
         self,
         method: str = "average",
@@ -2671,6 +2671,41 @@ def rank(
         Returns
         -------
         DataFrame with ranking of values within each group
+        %(see_also)s
+        Examples
+        --------
+        >>> df = pd.DataFrame(
+        ...     {
+        ...         "group": ["a", "a", "a", "a", "a", "b", "b", "b", "b", "b"],
+        ...         "value": [2, 4, 2, 3, 5, 1, 2, 4, 1, 5],
+        ...     }
+        ... )
+        >>> df
+          group  value
+        0     a      2
+        1     a      4
+        2     a      2
+        3     a      3
+        4     a      5
+        5     b      1
+        6     b      2
+        7     b      4
+        8     b      1
+        9     b      5
+        >>> for method in ['average', 'min', 'max', 'dense', 'first']:
+        ...     df[f'{method}_rank'] = df.groupby('group')['value'].rank(method)
+        >>> df
+          group  value  average_rank  min_rank  max_rank  dense_rank  first_rank
+        0     a      2           1.5       1.0       2.0         1.0         1.0
+        1     a      4           4.0       4.0       4.0         3.0         4.0
+        2     a      2           1.5       1.0       2.0         1.0         2.0
+        3     a      3           3.0       3.0       3.0         2.0         3.0
+        4     a      5           5.0       5.0       5.0         4.0         5.0
+        5     b      1           1.5       1.0       2.0         1.0         1.0
+        6     b      2           3.0       3.0       3.0         2.0         3.0
+        7     b      4           4.0       4.0       4.0         3.0         4.0
+        8     b      1           1.5       1.0       2.0         1.0         2.0
+        9     b      5           5.0       5.0       5.0         4.0         5.0
         """
         if na_option not in {"keep", "top", "bottom"}:
             msg = "na_option must be one of 'keep', 'top', or 'bottom'"