具有多个列聚合的SQL Server数据透视表 [英] SQL Server Pivot Table with multiple column aggregates
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问题描述
我有一张桌子:
create table mytransactions(country varchar(30), totalcount int, numericmonth int, chardate char(20), totalamount money)
该表具有以下记录:
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Australia', 36, 7, 'Jul-12', 699.96)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Australia', 44, 8, 'Aug-12', 1368.71)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Australia', 52, 9, 'Sep-12', 1161.33)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Australia', 50, 10, 'Oct-12', 1099.84)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Australia', 38, 11, 'Nov-12', 1078.94)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Australia', 63, 12, 'Dec-12', 1668.23)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Austria', 11, 7, 'Jul-12', 257.82)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Austria', 5, 8, 'Aug-12', 126.55)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Austria', 7, 9, 'Sep-12', 92.11)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Austria', 12, 10, 'Oct-12', 103.56)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Austria', 21, 11, 'Nov-12', 377.68)
Go
insert into mytransactions(country, totalcount, numericmonth, chardate, totalamount) values('Austria', 3, 12, 'Dec-12', 14.35)
Go
这是select *的样子:
This is what a select * looks like:
Country TotalCount numericmonth chardate totalamount
--------- ---------- ----------- -------- -----------
Australia 36 7 Jul-12 699.96
Australia 44 8 Aug-12 1368.71
Australia 52 9 Sep-12 1161.33
Australia 50 10 Oct-12 1099.84
Australia 38 11 Nov-12 1078.94
Australia 63 12 Dec-12 1668.23
Austria 11 7 Jul-12 257.82
Austria 5 8 Aug-12 126.55
Austria 7 9 Sep-12 92.11
Austria 12 10 Oct-12 103.56
Austria 21 11 Nov-12 377.68
Austria 3 12 Dec-12 14.35
我想旋转此记录集，使其看起来像这样:
I want to pivot this record set so it looks like this:
Australia Australia Austria Austria
# of Transactions Total $ amount # of Transactions Total $ amount
----------------- -------------- ----------------- --------------
Jul-12 36 699.96 11 257.82
Aug-12 44 1368.71 5 126.55
Sep-12 52 1161.33 7 92.11
Oct-12 50 1099.84 12 103.56
Nov-12 38 1078.94 21 377.68
Dec-12 63 1668.23 3 14.35
这是我到目前为止提出的关键代码:
This is the pivot code I've come up with so far:
select * from mytransactions
pivot (sum (totalcount) for country in ([Australia], [Austria])) as pvt
这就是我得到的:
numericmonth chardate totalamount Australia Austria
----------- -------- ---------- --------- -------
7 Jul-12 257.82 NULL 11
7 Jul-12 699.96 36 NULL
8 Aug-12 126.55 NULL 5
8 Aug-12 1368.71 44 NULL
9 Sep-12 92.11 NULL 7
9 Sep-12 1161.33 52 NULL
10 Oct-12 103.56 NULL 12
10 Oct-12 1099.84 50 NULL
11 Nov-12 377.68 NULL 21
11 Nov-12 1078.94 38 NULL
12 Dec-12 14.35 NULL 3
12 Dec-12 1668.23 63 NULL
我可以在表变量循环中手动聚合记录，但是看来ivot可以做到这一点.
I can manually aggregate the records in a table variable loop, however it seems that pivot might be able to do this.
是否可以使用数据透视表获取我想要的记录集，或者是否有我不知道的其他工具?
Is is possible to get the record set I want using pivot or is there another tool that I'm not aware of?
谢谢
推荐答案
我将通过同时应用UNPIVOT和PIVOT函数来获得最终结果，从而略有不同. unpivot 从totalcount和totalamount列中获取值，并将它们放入具有多行的一列中.然后，您可以根据这些结果进行分析.
I would do this slightly different by applying both the UNPIVOT and the PIVOT functions to get the final result. The unpivot takes the values from both the totalcount and totalamount columns and places them into one column with multiple rows. You can then pivot on those results.:
select chardate,
Australia_totalcount as [Australia # of Transactions],
Australia_totalamount as [Australia Total $ Amount],
Austria_totalcount as [Austria # of Transactions],
Austria_totalamount as [Austria Total $ Amount]
from
(
select
numericmonth,
chardate,
country +'_'+col col,
value
from
(
select numericmonth,
country,
chardate,
cast(totalcount as numeric(10, 2)) totalcount,
cast(totalamount as numeric(10, 2)) totalamount
from mytransactions
) src
unpivot
(
value
for col in (totalcount, totalamount)
) unpiv
) s
pivot
(
sum(value)
for col in (Australia_totalcount, Australia_totalamount,
Austria_totalcount, Austria_totalamount)
) piv
order by numericmonth
请参见带演示的SQL小提琴.
如果您有数量未知的country名称，则可以使用动态SQL:
If you have an unknown number of country names, then you can use dynamic SQL:
DECLARE @cols AS NVARCHAR(MAX),
@colsName AS NVARCHAR(MAX),
@query AS NVARCHAR(MAX)
select @cols = STUFF((SELECT distinct ',' + QUOTENAME(country +'_'+c.col)
from mytransactions
cross apply
(
select 'TotalCount' col
union all
select 'TotalAmount'
) c
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')
select @colsName
= STUFF((SELECT distinct ', ' + QUOTENAME(country +'_'+c.col)
+' as ['
+ country + case when c.col = 'TotalCount' then ' # of Transactions]' else 'Total $ Amount]' end
from mytransactions
cross apply
(
select 'TotalCount' col
union all
select 'TotalAmount'
) c
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')
set @query
= 'SELECT chardate, ' + @colsName + '
from
(
select
numericmonth,
chardate,
country +''_''+col col,
value
from
(
select numericmonth,
country,
chardate,
cast(totalcount as numeric(10, 2)) totalcount,
cast(totalamount as numeric(10, 2)) totalamount
from mytransactions
) src
unpivot
(
value
for col in (totalcount, totalamount)
) unpiv
) s
pivot
(
sum(value)
for col in (' + @cols + ')
) p
order by numericmonth'
execute(@query)
请参见带有演示的SQL小提琴
两者都给出结果:
| CHARDATE | AUSTRALIA # OF TRANSACTIONS | AUSTRALIA TOTAL $ AMOUNT | AUSTRIA # OF TRANSACTIONS | AUSTRIA TOTAL $ AMOUNT |
--------------------------------------------------------------------------------------------------------------------------------------
| Jul-12 | 36 | 699.96 | 11 | 257.82 |
| Aug-12 | 44 | 1368.71 | 5 | 126.55 |
| Sep-12 | 52 | 1161.33 | 7 | 92.11 |
| Oct-12 | 50 | 1099.84 | 12 | 103.56 |
| Nov-12 | 38 | 1078.94 | 21 | 377.68 |
| Dec-12 | 63 | 1668.23 | 3 | 14.35 |
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