In [42]: frame=pd.DataFrame({'a':range(7),'b':range(7,0,-1),
    ...: 'c':['one','one','one','two','two','two','two'],
    ...: 'd':[0,1,2,0,1,2,3]})

In [43]: frame
Out[43]:
   a  b    c  d
0  0  7  one  0
1  1  6  one  1
2  2  5  one  2
3  3  4  two  0
4  4  3  two  1
5  5  2  two  2
6  6  1  two  3

DataFrame的set_index( )函数会将一个或多个列转换为行索引

In [44]: frame.set_index(['c','d'])
Out[44]:
       a  b
c   d
one 0  0  7
    1  1  6
    2  2  5
two 0  3  4
    1  4  3
    2  5  2
    3  6  1

默认情况下，转换的列会从DataFrame中移除，但也可以将其保留下来

In [47]: frame.set_index(['c','d'],drop=False)
Out[47]:
       a  b    c  d
c   d
one 0  0  7  one  0
    1  1  6  one  1
    2  2  5  one  2
two 0  3  4  two  0
    1  4  3  two  1
    2  5  2  two  2
    3  6  1  two  3

reset_index( )是set_index( )的逆运算

In [45]: frame.set_index(['c','d']).reset_index()
Out[45]:
     c  d  a  b
0  one  0  0  7
1  one  1  1  6
2  one  2  2  5
3  two  0  3  4
4  two  1  4  3
5  two  2  5  2
6  two  3  6  1

转载地址：

《利用Python进行数据分析》

1. 查询出来要转换的数据

SELECT name FROM dbo.base_pay_type WHERE is_enabled = 1

数据如图：

2.将查询到的数据转换成行，以逗号隔开，以【】包裹

SELECT STUFF((SELECT  '[' + name + '],'  
FROM(SELECT name FROM dbo.base_pay_type WHERE is_enabled = 1) a  FOR  XML PATH('')  ), 1,0, '') AS Name 

数据如图：

3，去掉最后一个逗号

SELECT LEFT(a.Name,LEN(a.Name)-1) AS Name FROM (SELECT STUFF((SELECT  '[' + name + '],'  
FROM(SELECT name FROM dbo.base_pay_type WHERE is_enabled = 1) a  FOR  XML PATH('')  ), 1,0, '') AS Name ) AS a

数据如图：

4，这一行形成新的列，用PIVOT实现

SELECT * FROM (
 select sellerid,pay_type_name,cast(sum(amount) as decimal(18,2)) as payamout from (
 SELECT distinct oi.order_guid,ss.SellerId,bs.name AS pay_type_name,op.amount
 FROM dbo.shop_sellers AS ss
 LEFT JOIN dbo.order_item oi ON ss.SellerId=oi.tracking_id
 LEFT JOIN dbo.order_list ol ON ol.order_guid = oi.order_guid
 LEFT JOIN dbo.order_pay op ON ol.order_guid=op.order_guid
 LEFT JOIN dbo.base_pay_type bs ON op.pay_type_id=bs.pay_type_id
 INNER JOIN dbo.shops s ON s.ShopGuid=ol.owner
 WHERE bs.is_enabled=1 AND op.is_received=1 AND order_status='finished' and pay_status='paid' 
 and s.ShopId IN(SELECT ShopId FROM dbo.shops WHERE 1=1 and shopid=15 or ParentShopId=15) 
 AND ol.order_time between '2018-01-17' and '2018-08-17 23:59:59') a
 GROUP BY SellerId,pay_type_name) AS PA PIVOT(MAX( payamout ) FOR 
 pay_type_name IN ([现金],[支付宝],[微信支付],[会员卡],[康品汇会员卡],[银联扫码支付]))PPA

数据如图：

5，C#后台代码，先将一列转换成一行，以逗号隔开，【】包裹

string SQL = "SELECT LEFT(a.Name,LEN(a.Name)-1) AS Name FROM (SELECT STUFF((SELECT  '[' + name + '],' FROM(SELECT name FROM dbo.base_pay_type WHERE is_enabled = 1) a  FOR  XML PATH('')  ), 1, 0, '') AS Name ) AS a";
DataTable dt = dbAccess.ExecuteTable(SQL);
string filwes = dt.Rows[0]["name"].ToString();
得到的结果如上面标题3,然后拼接SQL,将filwes作为参数输入下面SQL语句
SELECT * FROM (
select sellerid,pay_type_name,cast(sum(amount) as decimal(18,2)) as payamout from (
SELECT distinct oi.order_guid,ss.SellerId,bs.name AS pay_type_name,op.amount
FROM dbo.shop_sellers AS ss
LEFT JOIN dbo.order_item oi ON ss.SellerId=oi.tracking_id
LEFT JOIN dbo.order_list ol ON ol.order_guid = oi.order_guid
LEFT JOIN dbo.order_pay op ON ol.order_guid=op.order_guid
LEFT JOIN dbo.base_pay_type bs ON op.pay_type_id=bs.pay_type_id
INNER JOIN dbo.shops s ON s.ShopGuid=ol.owner
WHERE bs.is_enabled=1 AND op.is_received=1 AND order_status='finished' and pay_status='paid' 
and s.ShopId IN(SELECT ShopId FROM dbo.shops WHERE 1=1 {1}) {2}) a
GROUP BY SellerId,pay_type_name) AS PA PIVOT(MAX( payamout ) FOR pay_type_name IN (‘“+filwes+”’))PPA

#define _CRT_SECURE_NO_WARNINGS
#include<stdlib.h>
#include<stdio.h>
#include<string.h>

//把三行四列输出为四行三列
void main(void)
{
	int s[3][4]={{1,1,1,1},{2,2,2,2},{3,3,3,3}},i,j;
	int *p = s[0];//指向0的位置
	printf("下列是三行四列的输出\r\n");
	for (i = 0; i < 12; i++)
	{
		printf("%d ",*(p+i));
		if((i+1) % 4 == 0)//如果是行输出够了四个就换行
		{
			printf("\r\n");
		}
	}
	printf("下列是四行三列!!\n");
	for (i = 0; i < 4; i++)//四行
	{
		for (j = 0; j < 3; j++)//三列
		{
			printf("%d ",*(p+i+j*4));
		}
		printf("\r\n");
	}
	system("pause");
}