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I have data as below,
is there any way to elimate the first two rows data and Keep only Unique values in the visual.
please help.
Thanks in advance
Hi @BhavyaM ,
I seem to be a bit confused about your description. As shown in the screenshot below, according to your requirement, you need to group Product by category and then delete the rows whose Value values add up to 0. If the same Product has more than one column with the same value, how do I do it and what are the conditions based on?
Please solve my confusion, so that I can do further testing. Looking forward to your feedback.
Best Regards,
Henry
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Yes, If the same Product has more than one column with the same value we have to show only that non zero values. There is no other conditions only based on Category and Product we have to show the values which are not equal to 0
Can anyone having solution. Please help on this.
Using the above query it will elimate the Min date values. But what i want to show is for one category there will be multiple product and for each product there will be multiple date from and date to.
If any product is having different date from and date to or same date from and date to with below scenario
-13,700 +13,700 it will be = 0. So i want to remove this kind of data and keep only Unique values.
@BhavyaM , Create this measure and use in visual level filter and check for non blank
if( max(Table[Date from]) = calculate(max(Table[Date From]), filter(allselected(Table), Table[Category Id] = max(Table[Category ID]))) , 1,balnk())
Using the above query it will elimate the Min date values. But what i want to show is for one category there will be multiple product and for each product there will be multiple date from and date to.
If any product is having different date from and date to or same date from and date to with below scenario
-13,700 +13,700 it will be = 0. So i want to remove this kind of data and keep only Unique values.
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