Data without Pivot

Question

Hi

I want to display data like below without Pivot. Locations can be more. How it can be done without using Pivot

		Location 1	Location 2	Location 3	Location 4

Item1	Event1	10		20
Item2	Event2		30		10

Thanks

Ramco Ramco · Answer

Hi Can you please help with code. Thanks

Daniel Wright · Answer

To display data in a tabular format without using Pivot, especially when dealing with potentially varying numbers of locations, you can achieve this by structuring the table in a way that accommodates a dynamic number of locations without relying on the Pivot function. One approach to achieving this is by setting up your table with specific rows and columns dedicated to each aspect you want to display. For your specific example, you can structure it as follows: 1. Rows : - Each row represents a unique combination of Item and Event. - There will be a row for each combination of Item and Event you want to display. 2. Columns : - Define columns for all the Locations you want to include. - You can add columns dynamically based on the actual locations present in your dataset. 3. Data Cells : - Populate the table with the appropriate data in the respective cells. By following this approach, you can create a table similar to the one you provided, without using the Pivot function. This method allows you to have flexibility in adding more locations without the need to modify the table structure significantly. Here's a simplified example to showcase how you can structure your table without Pivot: | Item | Event | Location 1 | Location 2 | Location 3 | Location 4 | |--------|--------|------------|------------|------------|------------| | Item1 | Event1 | 10 | | 20 | | | Item2 | Event2 | | 30 | | 10 | By organizing your table in this manner, you can accommodate multiple locations and their corresponding values for each Item and Event combination without relying on the Pivot function. This structure provides a clear and concise representation of your data while allowing for scalability as more locations are added to your dataset. I hope this explanation helps! If you need further clarification or have any more questions, feel free to ask.