What is the Power BI DAX function IGNORE?
The DAX function IGNORE is used to ignore a specified set of values in a column while performing a calculation. It comes in handy when you want to exclude certain data points from calculations without removing them from the visualization.
How to Use the Power BI DAX function IGNORE
The syntax for the IGNORE function in DAX is straightforward. Here’s an example:
IGNORE(❰table❱[❰column❱], [❰value1❱], [❰value2❱], …)
The function takes two arguments:
- The calculation expression that you want to perform
- The column from which you want to exclude specific values
You can specify one or more values to exclude from the calculation in the square brackets. For example, if you want to exclude the values “John” and “Alice” from the calculation, you can write:
IGNORE(❰table❱[❰column❱], [“John”], [“Alice”])
You can also use a measure for the calculation expression. Here’s an example:
Total Sales =
SUM ( Sales[Amount] ),
IGNORE ( Sales[Region], [Region] )
In the example above, we are calculating the total sales, excluding the sales data from a specific region. The measure uses the IGNORE function to exclude the values from the Sales[Region] column that are equal to the current context value of [Region].
The IGNORE function in DAX is a powerful tool that allows you to exclude specific values from calculations without removing them from the visualization. It comes in handy when you want to perform calculations on subsets of data.
Here are some key takeaways to keep in mind when using the Power BI DAX function IGNORE:
- The syntax for the function is straightforward
- You can specify one or more values to exclude from the calculation
- The function can be used with measures and expressions
- The function allows you to perform calculations on subsets of data without removing them from the visualization
The Power BI DAX function IGNORE is a valuable tool for any data modeler or analyst using Power BI. It provides an easy way to exclude specific values from calculations without removing them from the visualization. By following the guidelines outlined in this article, you can make the most of this function and create more effective data models.