Pivot Assistance Required - sql

Question

I have a table like this . Table 1.
Customer Product Value Quantity Order Number
Dave Product 1 15 1 154
Dave Product 2 25 5 154
Dave Product 3 45 4 15
Rob Product 2 222 33 233
Now I want this , Table 2.
Customer Product 1 Quantity Product 1 Value Price per item ( Value /Quantity) for Product 1 Product 2 Quantity Product 2 Value Price per item ( Value /Quantity) for Product 2 Product 3 Quantity Product 3 Value Price per item ( Value /Quantity) for Product 3 Order Number
Dave 1 15 15 5 25 5 null null null 154
Dave null null null null null Null 4 45 11.25 15
Rob null null null 33 222 6.727272727 null null null 233
I was thinking about some pivot but wasn't sure how to construct it . Also the number of products is not fixed and change in Table 1.

Answer 1

In order to get the result, I would advise applying both an unpivot and a pivot to the data.
The UNPIVOT will convert the column data from your table into rows. Once the data is unpivoted, then you can apply a pivot.
Since you are using SQL Server 2008+ you can use CROSS APPLY with the VALUES clause to unpivot. Prior to 2008, you could use the UNPIVOT function. The code to unpivot the data is:
select t.customer,
replace(t.product, ' ', '')+'_'+c.col piv_col,
c.val,
t.ordernumber
from table1 t
cross apply
(
values
('value', cast(value as varchar(10))),
('quantity', cast(quantity as varchar(10))),
('PricePerUnit', cast((value/quantity) *1.0 as varchar(10)))
) c (col, val);
See Demo. This converts the data into the following format:
| CUSTOMER | PIV_COL | VAL | ORDERNUMBER |
---------------------------------------------------------
| Dave | Product1_value | 15 | 154 |
| Dave | Product1_quantity | 1 | 154 |
| Dave | Product1_PricePerUnit | 15.0 | 154 |
| Dave | Product2_value | 25 | 154 |
You can see that the row for Dave order 154 has been turned into rows and I have created the new column names that will be used for the pivot (piv_col). This column has concatenated the Product Name to the from of the previous column headers (value, quantity).
Since the data is in a single row, you can easily apply the pivot function to the data. The final code will be:
select customer,
Product1_quantity, Product1_value, Product1_PricePerUnit,
Product2_quantity, Product2_value, Product2_PricePerUnit,
Product3_quantity, Product3_value, Product3_PricePerUnit,
orderNumber
from
(
select t.customer,
replace(t.product, ' ', '')+'_'+c.col piv_col,
c.val,
t.ordernumber
from table1 t
cross apply
(
values
('value', cast(value as varchar(10))),
('quantity', cast(quantity as varchar(10))),
('PricePerUnit', cast((value/quantity) *1.0 as varchar(10)))
) c (col, val)
) d
pivot
(
max(val)
for piv_col in(Product1_quantity, Product1_value, Product1_PricePerUnit,
Product2_quantity, Product2_value, Product2_PricePerUnit,
Product3_quantity, Product3_value, Product3_PricePerUnit)
) piv;
See SQL Fiddle with Demo.
The above works great if you have a known number of products, but if not, then you will need to use dynamic SQL.
DECLARE #cols AS NVARCHAR(MAX),
#query AS NVARCHAR(MAX)
select #cols = STUFF((SELECT ',' + QUOTENAME(replace(t.product, ' ', '')+'_'+c.col)
from Table1 t
cross apply
(
values ('value', 1), ('quantity', 0),('PricePerUnit', 3)
) c (col, so)
group by product, col, so
order by product, so
FOR XML PATH(''), TYPE
).value('.', 'NVARCHAR(MAX)')
,1,1,'')
set #query = 'SELECT customer, ' + #cols + ', ordernumber
from
(
select t.customer,
replace(t.product, '' '', '''')+''_''+c.col piv_col,
c.val,
t.ordernumber
from table1 t
cross apply
(
values
(''value'', cast(value as varchar(10))),
(''quantity'', cast(quantity as varchar(10))),
(''PricePerUnit'', cast((value/quantity) *1.0 as varchar(10)))
) c (col, val)
) d
pivot
(
max(val)
for piv_col in (' + #cols + ')
) p '
execute(#query);
See SQL Fiddle with Demo. These queries give the result:
| CUSTOMER | PRODUCT1_QUANTITY | PRODUCT1_VALUE | PRODUCT1_PRICEPERUNIT | PRODUCT2_QUANTITY | PRODUCT2_VALUE | PRODUCT2_PRICEPERUNIT | PRODUCT3_QUANTITY | PRODUCT3_VALUE | PRODUCT3_PRICEPERUNIT | ORDERNUMBER |
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
| Dave | (null) | (null) | (null) | (null) | (null) | (null) | 4 | 45 | 11.0 | 15 |
| Dave | 1 | 15 | 15.0 | 5 | 25 | 5.0 | (null) | (null) | (null) | 154 |
| Rob | (null) | (null) | (null) | 33 | 222 | 6.0 | (null) | (null) | (null) | 233 |