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Hi everyone,
I have a table like the next one:
ID | Class | Points | Points_Norm |
1 | A | 50 | 0 |
2 | A | 800 | 0.1372455 |
3 | A | 911 | 0.15755784 |
4 | B | 456152 | 83.4639301 |
5 | B | 1521 | 0.26918418 |
6 | B | 123 | 0.01335856 |
7 | C | 14894 | 2.71636296 |
8 | C | 4561 | 0.82548594 |
9 | C | 546516 | 100 |
10 | C | 146516 | 26.8023994 |
Also, I have a slicer for the column "Class". My objective is to put the variable "Points_norm "in a graph (it is just the values of "Points" normalized between 0 and 100).
What I'm looking for is that, when I select one of the classes with my slicer, I get the normalized values just for the filtered results. In this example, if I select Class==A with the slicer, what I would get is:
ID | Class | Points | Points_Norm |
1 | A | 50 | 0 |
2 | A | 800 | 87.1080139 |
3 | A | 911 | 100 |
Because the normalization is done just for those values I calculated. Does anyone know how to get this in Power BI?
Thank you all
So the idea would be, how to get a measure that scales between 0 and 100 the values that affected the slicer?
@Anonymous , have slicer using what if parameter
assume you need it for points and ID is you min level
Try like
total point = sum(Table[Points])
measure =
var _min = minx(allselected(whatif), whatif[value])
var _max = maxx(allselected(whatif), whatif[value])
return
sumx(values(Table[ID]) , if([total point]>=_min && [total point] <=_max, [total point], blank()))
or like this, here you can add more than one group by
measure =
var _min = minx(allselected(whatif), whatif[value])
var _max = maxx(allselected(whatif), whatif[value])
return
sumx(filter(summarize(Table, Table[ID], "_1", sum(Table[Points])) , [_1]>=_min && [_1] <=_max),[_1])
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