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Hello, I have a matrix where the rows section have 2 different components, lets say name and subname, 1 dependent of the other, and the colums are the weeks of the year so fat. Inside what it is calculating is the times this subname appears on the original data. So it looks like this:
I want to filter the data an see only the cells that show 7 or less, something like this
I have used all my knowledge but the visual filter only "reads" the total column and does not care about the cell value.
Can somebody please help me?
Solved! Go to Solution.
Hi @gorjegzz,
1. I would suggest you have an independent date table.
2. A measure is needed in your scenario.
Measure =
VAR amount =
COUNT ( 'table'[acceso_id] )
RETURN
IF ( amount < 7, amount, BLANK () )
3. You can filter out the blanks if you want to.
Best Regards,
Dale
This seems to be possible. Can you share some sample data and expected matrix before/ after filtering for the sample data?
Thanks
Raj
Hi Raj, thanks for the answer. Here is a sample picture of the data. So it has many ID numbers and many different acceso_id numbers, every day they should create a log and have a date, unless they did not connect. So what Im doing is dividing the year in weeks and then using weeks as the columns; then, in the interior of the matrix I count the number of acceso_id per combination of ID + acceso_id so it should be 7 each week if the machines worked properly. With the matrix I want to see only the ones who did not worked the 7 days.
I'm not sure if i made myself clear?
Thanks for the help
Hi @gorjegzz,
1. I would suggest you have an independent date table.
2. A measure is needed in your scenario.
Measure =
VAR amount =
COUNT ( 'table'[acceso_id] )
RETURN
IF ( amount < 7, amount, BLANK () )
3. You can filter out the blanks if you want to.
Best Regards,
Dale
Works perfectly
Thank you very much Dale
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