The ultimate Microsoft Fabric, Power BI, Azure AI, and SQL learning event: Join us in Stockholm, September 24-27, 2024.
Save €200 with code MSCUST on top of early bird pricing!
Find everything you need to get certified on Fabric—skills challenges, live sessions, exam prep, role guidance, and more. Get started
I have a simple Sankey Chart that shows vehicle trips flowing between 11 district orgins and destinations. It looks like this with no filters.
Which is too dense to understand.
When I filter to only OD pairs >=1 it looks like this. with Anne Arundel County moved to the far right. This is just wrong because there are still two layers of information.
Can someone exlain how to fix this, or why it is happening? Or should I go back to R and python?
Solved! Go to Solution.
Hi, @Gutbucketeer
This may be caused by a closed loop in your data.
Try to modify your original table column from
Source | Destination |
Washington Dc | Howard |
Anne Arundel Co | Washington Dc |
to
New Source | New Destination |
Washington Dc _Source | Howard_Destination |
Anne Arundel Co_Source | Washington Dc_Destination |
New Source = 'Table'[Source] & "_Source"
New Destination = 'Table'[Destination] & "_Destination"
Best Regards,
Community Support Team _ Eason
Hi, @Gutbucketeer
This may be caused by a closed loop in your data.
Try to modify your original table column from
Source | Destination |
Washington Dc | Howard |
Anne Arundel Co | Washington Dc |
to
New Source | New Destination |
Washington Dc _Source | Howard_Destination |
Anne Arundel Co_Source | Washington Dc_Destination |
New Source = 'Table'[Source] & "_Source"
New Destination = 'Table'[Destination] & "_Destination"
Best Regards,
Community Support Team _ Eason
I think that will fix it. The p[roblem arose when I filtered out all but 1 o to d flow in the data. it created a separate tier.
Join the community in Stockholm for expert Microsoft Fabric learning including a very exciting keynote from Arun Ulag, Corporate Vice President, Azure Data.
Check out the August 2024 Power BI update to learn about new features.
User | Count |
---|---|
108 | |
77 | |
73 | |
47 | |
39 |
User | Count |
---|---|
137 | |
108 | |
69 | |
64 | |
56 |