updated according to Jeff's comments

Author: maxu777

doc/source/comparison_with_sql.rst

@@ -372,8 +372,8 @@ In pandas, you can use :meth:`~pandas.concat` in conjunction with
 
     pd.concat([df1, df2]).drop_duplicates()
 
-SOME ANALYTIC AND AGGREGATE FUNCTIONS
--------------------------------------
+Pandas equivalents for some SQL analytic and aggregate functions
+----------------------------------------------------------------
 Top N rows with offset
 
 .. code-block:: sql
@@ -383,16 +383,11 @@ Top N rows with offset
     ORDER BY tip DESC
     LIMIT 10 OFFSET 5;
 
-    -- Oracle 12c+
-    SELECT * FROM tips
-    ORDER BY tip DESC
-    OFFSET 5 ROWS FETCH NEXT 10 ROWS ONLY;
-
 In pandas:
 
 .. ipython:: python
 
-    tips.sort_values(['tip'], ascending=False).head(10+5).tail(10)
+    tips.nlargest(10+5, columns='tip').tail(10)
 
 Top N rows per group
 
@@ -428,31 +423,9 @@ the same using `rank(method='first')` function
     tips['rnk'] = tips.groupby(['day'])['total_bill'].rank(method='first', ascending=False)
     tips.loc[tips['rnk'] < 3].sort_values(['day','rnk'])
 
-Top second and top third total bills per day
-
-.. code-block:: sql
-
-    -- Oracle
-    SELECT * FROM (
-      SELECT
-        t.*,
-        ROW_NUMBER() OVER(PARTITION BY day ORDER BY total_bill DESC) AS rn
-      FROM tips t
-    )
-    WHERE rn BETWEEN 2 and 3
-    ORDER BY day, rn;
-
-.. ipython:: python
-
-    tips['rn'] = tips.sort_values(['total_bill'], ascending=False) \
-                     .groupby(['day']) \
-                     .cumcount() + 1
-    tips.loc[tips['rn'].between(2, 3)].sort_values(['day','rn'])
-
-    
 .. code-block:: sql
 
-    -- Oracle
+    -- Oracle's RANK() analytic function
     SELECT * FROM (
       SELECT
         t.*,