FROM - Using PIVOT and UNPIVOT
Applies to: 
SQL Server
Azure SQL Database
Azure SQL Managed Instance
Azure Synapse Analytics
Analytics Platform System (PDW)
SQL analytics endpoint in Microsoft Fabric
Warehouse in Microsoft Fabric
SQL database in Microsoft Fabric
You can use the PIVOT and UNPIVOT relational operators to change a table-valued expression into another table. PIVOT rotates a table-valued expression by turning the unique values from one column in the expression into multiple columns in the output. PIVOT also runs aggregations where they're required on any remaining column values that are wanted in the final output. UNPIVOT carries out the opposite operation to PIVOT, by rotating columns of a table-valued expression into column values.
The syntax for PIVOT is easier and more readable than the syntax that might otherwise be specified in a complex series of SELECT...CASE statements. For a complete description of the syntax for PIVOT, see FROM clause.
Note
Repeated use of PIVOT/UNPIVOT within a single T-SQL statement can negatively impact query performance.
The Transact-SQL code samples in this article use the AdventureWorks2022 or AdventureWorksDW2022 sample database, which you can download from the Microsoft SQL Server Samples and Community Projects home page.
Syntax
This section summarizes how to use the PIVOT and UNPIVOT operator.
Syntax for the PIVOT operator.
SELECT [ <non-pivoted column> [ AS <column name> ] , ]
...
[ <first pivoted column> [ AS <column name> ] ,
[ <second pivoted column> [ AS <column name> ] , ]
...
[ <last pivoted column> [ AS <column name> ] ] ]
FROM
( <SELECT query that produces the data> )
AS <alias for the source query>
PIVOT
(
<aggregation function> ( <column being aggregated> )
FOR <column that contains the values that become column headers>
IN ( <first pivoted column>
, <second pivoted column>
, ... <last pivoted column> )
) AS <alias for the pivot table>
[ <optional ORDER BY clause> ]
[ ; ]
Syntax for the UNPIVOT operator.
SELECT [ <non-pivoted column> [ AS <column name> ] , ]
...
[ <output column for names of the pivot columns> [ AS <column name> ] , ]
[ <new output column created for values in result of the source query> [ AS <column name> ] ]
FROM
( <SELECT query that produces the data> )
AS <alias for the source query>
UNPIVOT
(
<new output column created for values in result of the source query>
FOR <output column for names of the pivot columns>
IN ( <first pivoted column>
, <second pivoted column>
, ... <last pivoted column> )
)
[ <optional ORDER BY clause> ]
[ ; ]
Remarks
The column identifiers in the UNPIVOT clause follow the catalog collation.
For Azure SQL Database, the collation is always
SQL_Latin1_General_CP1_CI_AS.For SQL Server partially contained databases, the collation is always
Latin1_General_100_CI_AS_KS_WS_SC.
If the column is combined with other columns, then a collate clause (COLLATE DATABASE_DEFAULT) is required to avoid conflicts.
In Microsoft Fabric and Azure Synapse Analytics pools, queries with PIVOT operator fail if there's a GROUP BY on the nonpivot column output by PIVOT. As a workaround, remove the nonpivot column from the GROUP BY. Query results are the same, as this GROUP BY clause is a duplicate.
Basic PIVOT example
The following code example produces a two-column table that has four rows.
USE AdventureWorks2022;
GO
SELECT DaysToManufacture, AVG(StandardCost) AS AverageCost
FROM Production.Product
GROUP BY DaysToManufacture;
Here's the result set.
DaysToManufacture AverageCost
------------------ ------------
0 5.0885
1 223.88
2 359.1082
4 949.4105
No products are defined with a value of 3 for DaysToManufacture.
The following code displays the same result, pivoted so that the DaysToManufacture values become the column headings. A column is provided for three ([3]) days, even though the results are NULL.
-- Pivot table with one row and five columns
SELECT 'AverageCost' AS CostSortedByProductionDays,
[0], [1], [2], [3], [4]
FROM (
SELECT DaysToManufacture,
StandardCost
FROM Production.Product
) AS SourceTable
PIVOT (
AVG(StandardCost) FOR DaysToManufacture IN
([0], [1], [2], [3], [4])
) AS PivotTable;
Here's the result set.
CostSortedByProductionDays 0 1 2 3 4
--------------------------- ----------- ----------- ----------- ----------- -----------
AverageCost 5.0885 223.88 359.1082 NULL 949.4105
Complex PIVOT example
A common scenario where PIVOT can be useful is when you want to generate cross-tabulation reports to give a summary of the data. For example, suppose you want to query the PurchaseOrderHeader table in the AdventureWorks2022 sample database to determine the number of purchase orders placed by certain employees. The following query provides this report, ordered by vendor.
USE AdventureWorks2022;
GO
SELECT VendorID,
[250] AS Emp1,
[251] AS Emp2,
[256] AS Emp3,
[257] AS Emp4,
[260] AS Emp5
FROM
(
SELECT PurchaseOrderID,
EmployeeID, VendorID
FROM Purchasing.PurchaseOrderHeader
) p
PIVOT
(
COUNT (PurchaseOrderID)
FOR EmployeeID IN ([250], [251], [256], [257], [260])
) AS pvt
ORDER BY pvt.VendorID;
Here's a partial result set.
VendorID Emp1 Emp2 Emp3 Emp4 Emp5
----------- ----------- ----------- ----------- ----------- -----------
1492 2 5 4 4 4
1494 2 5 4 5 4
1496 2 4 4 5 5
1498 2 5 4 4 4
1500 3 4 4 5 4
The results returned by this subselect statement are pivoted on the EmployeeID column.
SELECT PurchaseOrderID,
EmployeeID,
VendorID
FROM PurchaseOrderHeader;
The unique values returned by the EmployeeID column become fields in the final result set. As such, there's a column for each EmployeeID number specified in the pivot clause, which are employees 250, 251, 256, 257, and 260 in this example. The PurchaseOrderID column serves as the value column, against which the columns returned in the final output, which are called the grouping columns, are grouped. In this case, the grouping columns are aggregated by the COUNT function. A warning message appears that indicates that any null values appearing in the PurchaseOrderID column weren't considered when computing the COUNT for each employee.
Important
When aggregate functions are used with PIVOT, the presence of any null values in the value column aren't considered when computing an aggregation.
UNPIVOT example
UNPIVOT carries out almost the reverse operation of PIVOT, by rotating columns into rows. Suppose the table produced in the previous example is stored in the database as pvt, and you want to rotate the column identifiers Emp1, Emp2, Emp3, Emp4, and Emp5 into row values that correspond to a particular vendor. As such, you must identify two extra columns.
The column that contains the column values that you're rotating (Emp1, Emp2, and so on) is called Employee, and the column that holds the values that currently exist under the columns being rotated, is called Orders. These columns correspond to the pivot_column and value_column, respectively, in the Transact-SQL definition. Here's the query.
-- Create the table and insert values as portrayed in the previous example.
CREATE TABLE pvt (
VendorID INT,
Emp1 INT,
Emp2 INT,
Emp3 INT,
Emp4 INT,
Emp5 INT);
GO
INSERT INTO pvt
VALUES (1, 4, 3, 5, 4, 4);
INSERT INTO pvt
VALUES (2, 4, 1, 5, 5, 5);
INSERT INTO pvt
VALUES (3, 4, 3, 5, 4, 4);
INSERT INTO pvt
VALUES (4, 4, 2, 5, 5, 4);
INSERT INTO pvt
VALUES (5, 5, 1, 5, 5, 5);
GO
-- Unpivot the table.
SELECT VendorID, Employee, Orders
FROM (
SELECT VendorID, Emp1, Emp2, Emp3, Emp4, Emp5
FROM pvt
) p
UNPIVOT
(
Orders FOR Employee IN (Emp1, Emp2, Emp3, Emp4, Emp5)
) AS unpvt;
GO
Here's a partial result set.
VendorID Employee Orders
----------- ----------- ------
1 Emp1 4
1 Emp2 3
1 Emp3 5
1 Emp4 4
1 Emp5 4
2 Emp1 4
2 Emp2 1
2 Emp3 5
2 Emp4 5
2 Emp5 5
UNPIVOT isn't the exact reverse of PIVOT. PIVOT carries out an aggregation and merges possible multiple rows into a single row in the output. UNPIVOT doesn't reproduce the original table-valued expression result, because rows have been merged. Also, NULL values in the input of UNPIVOT disappear in the output. When the values disappear, it shows that there might have been original NULL values in the input before the PIVOT operation.
The Sales.vSalesPersonSalesByFiscalYears view in the AdventureWorks2022 sample database uses PIVOT to return the total sales for each salesperson, for each fiscal year. To script the view in SQL Server Management Studio, in Object Explorer, locate the view under the Views folder for the AdventureWorks2022 database. Right-click the view name, and then select Script View as.