How To Make Each Month Its Own Column Sql

SQL Programming

Have you ever come across a scenario where you needed to display data in a tabular format, with each month of the year as its own column? If so, you’re in luck! In this article, I will guide you through the process of achieving this using SQL.

To start off, let’s consider a scenario where we have a table called “Sales” with columns such as “Month”, “Year”, and “Revenue”. Our goal is to transform this table into a format where each month becomes its own column, making it easier to analyze and compare the revenue for different months.

To achieve this, we need to make use of SQL’s powerful pivoting capabilities. Pivoting allows us to convert rows into columns, which is exactly what we need in this case.

The first step is to identify the distinct months in our “Sales” table. We can do this by using the SQL “DISTINCT” keyword along with the “MONTH” function to extract the month from the “Month” column. Here’s an example query:


After executing this query, we will have a result set containing all the distinct months in our “Sales” table.

Now that we have the distinct months, we can use them as the columns in our final result set. We can achieve this by using SQL’s “CASE” statement along with some dynamic SQL.

Here’s an example query that demonstrates this:

FROM Sales
).value('.', 'NVARCHAR(MAX)')
SET @query = 'SELECT * FROM
(SELECT Month, Revenue FROM Sales) AS s
FOR Month IN (' + @cols + ')
) AS p;'

In the above query, we first declare two variables, “@cols” and “@query”. The “@cols” variable is used to store the dynamic column names, while the “@query” variable is used to store the final SQL query.

The “STUFF” function is used to concatenate all the distinct months and enclose them within the QUOTENAME function, which adds the necessary quotes around each month. The result is then stored in the “@cols” variable.

Finally, we build the dynamic SQL query using the “@cols” variable and the “PIVOT” function. The “PIVOT” function allows us to pivot the data based on the distinct months, and the “FOR Month IN” clause specifies the columns to be created.

After executing the dynamic SQL query, we will have our desired result set, with each month as its own column.


Pivoting data in SQL can be a powerful technique to transform your data into a more meaningful and easier-to-analyze format. By using the “CASE” statement and dynamic SQL, we can achieve the desired result of having each month as its own column.

However, it’s important to note that dynamic SQL can introduce potential security risks, such as SQL injection attacks. It’s crucial to validate and sanitize user inputs before constructing and executing dynamic SQL queries.

So, the next time you come across a scenario where you need to display data with each month as its own column, give this SQL pivoting technique a try. It will surely make your data analysis much easier!