From 675a73715d3c8adb9d9a9dce5f76a2db5106790c Mon Sep 17 00:00:00 2001
From: Mortada Mehyar <mortada.mehyar@gmail.com>
Date: Fri, 10 Jun 2016 00:23:34 -0700
Subject: [PATCH] [DOCUMENTATION] fixed groupby aggregation example for pyspark

## What changes were proposed in this pull request?

fixing documentation for the groupby/agg example in python

## How was this patch tested?

the existing example in the documentation dose not contain valid syntax (missing parenthesis) and is not using `Column` in the expression for `agg()`

after the fix here's how I tested it:

```
In [1]: from pyspark.sql import Row

In [2]: import pyspark.sql.functions as func

In [3]: %cpaste
Pasting code; enter '--' alone on the line to stop or use Ctrl-D.
:records = [{'age': 19, 'department': 1, 'expense': 100},
: {'age': 20, 'department': 1, 'expense': 200},
: {'age': 21, 'department': 2, 'expense': 300},
: {'age': 22, 'department': 2, 'expense': 300},
: {'age': 23, 'department': 3, 'expense': 300}]
:--

In [4]: df = sqlContext.createDataFrame([Row(**d) for d in records])

In [5]: df.groupBy("department").agg(df["department"], func.max("age"), func.sum("expense")).show()

+----------+----------+--------+------------+
|department|department|max(age)|sum(expense)|
+----------+----------+--------+------------+
|         1|         1|      20|         300|
|         2|         2|      22|         600|
|         3|         3|      23|         300|
+----------+----------+--------+------------+

Author: Mortada Mehyar <mortada.mehyar@gmail.com>

Closes #13587 from mortada/groupby_agg_doc_fix.
---
 docs/sql-programming-guide.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/sql-programming-guide.md b/docs/sql-programming-guide.md
index 940c1d77045ad..efdf873c34556 100644
--- a/docs/sql-programming-guide.md
+++ b/docs/sql-programming-guide.md
@@ -2221,7 +2221,7 @@ import pyspark.sql.functions as func
 
 # In 1.3.x, in order for the grouping column "department" to show up,
 # it must be included explicitly as part of the agg function call.
-df.groupBy("department").agg("department"), func.max("age"), func.sum("expense"))
+df.groupBy("department").agg(df["department"], func.max("age"), func.sum("expense"))
 
 # In 1.4+, grouping column "department" is included automatically.
 df.groupBy("department").agg(func.max("age"), func.sum("expense"))