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Hello there,
I want to do something that seems simple, but I just can't figure it out.
I want to count instances where a value is >= 90% and also separately count values that are below that
I have this data in the table: Production:
| Plant | Material | Production% |
| Plant1 | Material1 | 0.8034 |
| Plant2 | Material2 | 0.9532 |
| Plant1 | Material3 | 0.9804 |
| Plant1 | Material4 | 1.0000 |
| Plant2 | Material5 | 0.7532 |
If Production% is >= 90% (.9000) then count it as 1 pass. If < 90% then count as 1 fail, and sum and display both in a Matrix like this:
| Plant | Pass >=90 | Fail <90 |
| Plant 1 | 2 | 1 |
| Plant 2 | 1 | 1 |
Thanks.
Solved! Go to Solution.
Hi @Anonymous ,
You can create the following 2 measures for calculating the counts of instances( >= 90%) and instances( < 90%) separately, and put them on Values tab of matrix:
Pass =
CALCULATE (
COUNTROWS ( 'Production' ),
FILTER ( 'Production', 'Production'[Production%] >= 0.9 )
)
Fail =
CALCULATE (
COUNTROWS ( 'Production' ),
FILTER ( 'Production', 'Production'[Production%] < 0.9 )
)
Best Regards
Rena
Hi @Anonymous ,
You can create the following 2 measures for calculating the counts of instances( >= 90%) and instances( < 90%) separately, and put them on Values tab of matrix:
Pass =
CALCULATE (
COUNTROWS ( 'Production' ),
FILTER ( 'Production', 'Production'[Production%] >= 0.9 )
)
Fail =
CALCULATE (
COUNTROWS ( 'Production' ),
FILTER ( 'Production', 'Production'[Production%] < 0.9 )
)
Best Regards
Rena
Usually people prefer measures over calculated columns, but this might be a case where a calculated column would come in handy.
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