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Anonymous
Not applicable

Creating Bins in Direct Query

Greetings,

I am using direct query as part of my dashboard/reports, and I am struggling to create bins of a column that contains accuracy metrics. The column is just numbers of two decimal places and measures the accuracy of a forecast vs actual. I'd like to bin up accuracy values such as:

  • 0- 20
  • 21- 40
  • 41 - 60
  • 61+  and so on.

The error I get is:

ra67052_0-1610549707788.png

 

I think this is just symptomatic of using direct query but is there another way I can do this in direct query?

1 ACCEPTED SOLUTION
parry2k
Super User
Super User

@Anonymous I would recommend creating a column in your backend, maybe use a view and put this logic in there. 

 

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View solution in original post

2 REPLIES 2
parry2k
Super User
Super User

@Anonymous I would recommend creating a column in your backend, maybe use a view and put this logic in there. 

 

Check my latest blog post Year-2020, Pandemic, Power BI and Beyond to get a summary of my favourite Power BI feature releases in 2020

I would  Kudos if my solution helped. 👉 If you can spend time posting the question, you can also make efforts to give Kudos to whoever helped to solve your problem. It is a token of appreciation!

Visit us at https://perytus.com, your one-stop-shop for Power BI-related projects/training/consultancy.



Subscribe to the @PowerBIHowTo YT channel for an upcoming video on List and Record functions in Power Query!!

Learn Power BI and Fabric - subscribe to our YT channel - Click here: @PowerBIHowTo

If my solution proved useful, I'd be delighted to receive Kudos. When you put effort into asking a question, it's equally thoughtful to acknowledge and give Kudos to the individual who helped you solve the problem. It's a small gesture that shows appreciation and encouragement! ❤


Did I answer your question? Mark my post as a solution. Proud to be a Super User! Appreciate your Kudos 🙂
Feel free to email me with any of your BI needs.

Anonymous
Not applicable

Thanks, I created a new table and used a distinct function to pull the unique values and then created a column to count them. 

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