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I have created a New Card visual that includes an SVG image as in Terry Kolosko example (here)
When I apply a dimension to create small multiples, the callout values show the correct values - i.e. it is filtered by the small multiple field.
However, the measure that creates the SVG image is evaluated in the outer filter context - i.e. it is not filtered by the small multiple field.
As a consequence, all SVG images are the same 😞 , which is not correct.
It seems that this other post refers to the same issue.
Hi,
has anyone updates on the progress of this bug?
thanks for any feedback,
regards Kevin
This issue has now been corrected in the March 2025 release of Power BI Desktop.
unfortunately still not solved!
Hi all,
As mentioned in the post below: It should be solved in the next releases of Power BI.
Solved: Conditional Formatting - New Card Visual - Ref Lab... - Microsoft Fabric Community
If you want to follow up on the progress of the fix as soon as possible. You can create a support ticket and a dedicated Microsoft engineer will come to solve the problem for you.
It would be great if you continue to share in this issue to help others with similar problems after you know the root cause or solution.
The link of Power BI Support: https://powerbi.microsoft.com/en-us/support/
For how to create a support ticket, please refer to How to create a support ticket in Power BI - Microsoft Fabric Community
Best Regards,
Stephen Tao
I just installed the January 25 release of Power BI Desktop ( version 2.139.1576.0 ).
To my disapointment, the bug related to the CF of images is still there.
I installed the Jan 25 release as well. While the bug on the card hasn't been fixed yet, the svg images are now being rendered properly in the tile slicer so this might be your alternative in the meantime.
Thanks for the suggestion. If Microsoft already have the solution for the tile slicer, it will hopefully not take them too long to correct the new card visual as well.
Anyway, I have opened a support ticket (TrackingID#2501141420001257) . So they are now fully aware of the issue.
Hello there! This is my first time talking in the forum.
I've been searching if someone had the same problem I have, and I'm glad (well, not too much) that I was not alone.
SVG Measure works fine in:
- Matrix
- Tile Slicers
- Table
SVG Measures are not working in Card (new) visual.
I did not prove in other visuals.
As far as I've seen, I think it's a problem when the visual has to "propagate the filter context" to the measure, before that measure is calculated in memory. Just a theory considering a few little checks I did, and that it gives the same value for every small multiple.
I hope this get solved soon.
Image attached to show other instance of the same bug.
I'm sticking to the tile slicers in the meantime. There are elements though that are in the card but not in the slicer so they need to be added to the SVG code.
Did you got any solution ?I also have the same issue.It's showing same image for all small multiples
Here is ss as i am unable to upload powerbi file
Did you got any solution ?I also have the same issue.It's showing same image for all small multiples
I am using the latest available version: Version: 2.138.1452.0 64-bit (November 2024)
When splitting the visual in 3 distinct ones, each filtered on a single value, the sparklines and the callout values match together. This clearly indicates that when using small multiples, the CF measure for the image is not evaluated in the correct filter context.
So it appears that it isn't with the SVG images only but with conditional formatting as well. https://community.fabric.microsoft.com/t5/Desktop/Conditional-Formatting-New-Card-Visual-Ref-Labels/...
Hi @bdarbo78
I noticed that as well, so I opted for a matrix visualization to replicate the functionality. Meanwhile, the SVG URLs for images on slicer buttons appear blank.
Hi @bdarbo78 ,
Thanks for reaching out.
Is your Power BI Desktop the latest version?
Sometimes common issues can be solved by reinstalling it.
Is there any screenshot with issues for reference? It's important to pay attention to data privacy.
Best Regards,
Stephen Tao
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly