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SUM (SalesAmount ) FOR IN (, ,, ,, ) ) AS P The script below shows this scenario and the image below shows NULLs for the years 20 as there is no data for these years. In that case, you can still use the pivot column values, which are expected to come (or which are still not available in the original dataset) in the future though you will see NULL for its values. But what if some additional values are expected to come in the future, for example 20, etc. If you notice in the above script, we have provided values (2005, 2006, 20) for pivot columns as these values are available in the original datasets.
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SUM (SalesAmount ) FOR IN (, ,, ) ) AS P Please note the use of brackets for pivot column values these are required. Though we have used the SUM aggregation function, in this case there is no summation, as there is only one row for each unique combination for country and year. Now by using the PIVOT operator, we will convert row values into column values with the script given below and the results as shown in the image below. Analysis Services PowerShell Provider (SQLAS) in SQL Server 2012.Contained Database Authentication in SQL Server 2012.The Format() Function in SQL Server 2012.Also, if you notice, for each country and for each year there is a separate row. As you can see in the image below, it has sales information for some countries for a couple of years. With the script below, let’s create a table and load some data into it. The basic syntax for a PIVOT relational operator looks like this: SELECT > FROM >ĪggregateFunction (>) FOR PivotColumn IN (>) ) AS > It also allows performing aggregations, wherever required, for column values that are expected in the final output. SQL Server has a PIVOT relational operator to turn the unique values of a specified column from multiple rows into multiple column values in the output (cross-tab), effectively rotating a table. In this article, I demonstrate how you can convert rows values into columns values (PIVOT) and columns values into rows values (UNPIVOT) in SQL Server. In my last article “Converting Comma Separated Value to Rows and Vice Versa in SQL Server”, I talked about how you can convert comma separated (or separated with some other character) values in a single column into rows and vice versa.