How to Convert Rows to Columns in SQL Server Using PIVOT?

Using SQL Server's PIVOT Function to Restructure Data

SQL Server's powerful PIVOT function offers a streamlined way to transform data from a row-based structure to a column-based one. This is particularly useful for creating more easily readable and analyzed tabular reports.

Imagine a table with store numbers, week numbers, and a value (let's call it xCount). The goal is to reorganize this data so store numbers are listed vertically (rows) and week numbers horizontally (columns).

Static PIVOT (Known Week Numbers):

If you already know the specific week numbers you need, a straightforward PIVOT query can be used:

<code class="language-sql">SELECT *
FROM (
  SELECT store, week, xCount
  FROM yt
) src
PIVOT (SUM(xcount) FOR week IN ([1], [2], [3])) piv;</code>

This query sums the xCount values for each store and week. The IN clause specifies the weeks ([1], [2], [3] in this example).

Dynamic PIVOT (Unknown Week Numbers):

When the week numbers are dynamic (not known beforehand), a more flexible approach is needed:

<code class="language-sql">DECLARE @cols AS NVARCHAR(MAX),
    @query  AS NVARCHAR(MAX)

SELECT @cols = STUFF((SELECT ',' + QUOTENAME(Week) 
                    FROM yt
                    GROUP BY Week
                    ORDER BY Week
            FOR XML PATH(''), TYPE
            ).value('.', 'NVARCHAR(MAX)') 
        ,1,1,'')

SET @query = 'SELECT store,' + @cols + ' FROM (
                SELECT store, week, xCount
                FROM yt
            ) x
            PIVOT (
                SUM(xCount)
                FOR week IN (' + @cols + ')
            ) p '

EXECUTE(@query);</code>

This dynamic query first builds a comma-separated list of unique week numbers from the yt table. This list is then incorporated into a larger query that uses the PIVOT function to create the desired column-based output. The result is a pivot table showing stores as rows and weeks as columns, with corresponding xCount values. This method adapts to any number of weeks present in the data.

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