Pivoting

Pivoting in Power BI, often referred to as "unpivoting" in the context of reshaping data, allows you to transform your data table so that rows become columns or vice versa. This is particularly useful when dealing with datasets that have columns representing different values over time or categories that you want to analyze more effectively.

Example 

Let's assume you have a sales dataset where the sales amounts for each month are stored in separate columns:

Transform this data so that each month's sales appear in a single column with an additional column indicating the month.

Step 1: Load Data into Power BI

             Open PowerBI Desktop

             Get Data

             Click on "Home" > "Get Data" > "Text/CSV".

             Import the Sales Data CSV file.

Step 2: Unpivot Columns

             Go to the query editor

             Click on "Home" > "Transform data" to open Power Query Editor.

               Select columns to Unpivot

               In the Query Editor, select the columns you want to keep as-is (ProductID, ProductName, Region).

               Right-click on any of the selected columns and choose "Unpivot Other Columns".

                Rename columns:

               The columns JanSales, FebSales, and MarSales will be unpivoted into two columns: Attribute and Value.

               Rename the Attribute column to Month.

               Rename the Value column to SalesAmount.

    

              Apply changes:

             Click "Home" > "Close & Apply" to load the transformed data back into Power BI.

Step 3: Create a Visual Using the Unpivoted Data
   

             Create a Table Visual:

            In the "Report" view, select the table visual from the "Visualizations" pane.

            Drag ProductName, Region, Month, and SalesAmount to the table fields.

Unpivoting data in Power BI is a powerful way to reshape your dataset, allowing for more effective analysis and visualization. By following the steps outlined above, you can easily transform your data from a wide format to a long format, making it suitable for various types of analyses and visualizations.