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Hello,
The values of the same measure seems to be different, when the parameters of the visuals are different.
The data come from a table in Project Online. It is resource demands day by day. I have several lines for each day because of many projects and many resources
I calculate the sum of values day by day and take the maximum of this sum on the period of a month in that case. I have calculated this with several DAX formulas. For exemple :
ResourceDemand Dailypeak 2 =
MAXX(
KEEPFILTERS(VALUES(timeSet[TimeByDay])),
CALCULATE(
SUM(
ResourceDemandTimephasedDataSet[ResourceDemand]
),
DISTINCT(
ResourceDemandTimephasedDataSet[TimeByDay]
)
)
)
Then I use a line and stacked column chart without any column legend. The maximum of the column is correct.
In another visual I use a line and stacked column chart with Project Name in the column legend. The maximum is bigger.
Could you help me to have the correct values with Project Name in column legend ?
Thank you in advance for your help
Nicole
Solved! Go to Solution.
When you add the project as the legend then the measure will have to filter by that project, which will then change the result ever so slightly. You would have to use separate charts per project (small multiples for example) to arrive at a more truthy representation. The difference is not that big though.
I used a slightly simple version of your measure
Peak Day = maxx(SUMMARIZE(Days,Days[Date],"s",sum(Days[Resource Demand])),[s])
see attached
Hello @lbendlin
This is a sample of data for the months of January 2023 and a generic resource. I replace Project Name and Task Name to hide real data.
We calculate the sum of Resource Demand day by day and take the maximum of this sum for the month of January 2023, in this sample of data
The first visual gives the Monthly Peak Units %. This is the real peak unit in the month.
The second visual gives the Peak Units per Project. The value of the maximum is too high : it calculates the maximum by project. Then, it calculates the sum of this value
Project Name | Task Name | Duration | Start Date | Finish date | Resource Demand | Monthly Peak Units % | Peak Units % per Projects |
449 | 477 | ||||||
107-01 | T1 | 3,2 months | 13 Jan '23 | 21 Apr '23 | 4% | 4 | 4 |
140-15 | T2 | 4 months | 16 Sep '22 | 17 Jan '23 | 5% | 0 | 5 |
140-15 | T3 | 41 months | 28 Jun '21 | 10 Dec '24 | 7% | 7 | 7 |
184-08 | T4 | 62 months | 03 Jan '22 | 25 Mar '27 | 10% | 10 | 10 |
195-02 | T5 | 6 months | 19 Sep '22 | 22 Mar '23 | 8% | 8 | 8 |
195-02 | T6 | 9 months | 20 Dec '22 | 22 Sep '23 | 25% | 25 | 25 |
195-02 | T7 | 9 months | 04 Jul '22 | 06 Apr '23 | 2% | 2 | 2 |
300-01 | T8 | 32 months | 03 Nov '21 | 15 Jul '24 | 6% | 6 | 6 |
416-01 | T9 | 28 months | 28 May '21 | 09 Oct '23 | 9% | 9 | 9 |
416-01 | T10 | 3 months | 03 Oct '22 | 02 Jan '23 | 15% | 0 | 15 |
430-01 | T11 | 34 months | 01 Mar '21 | 11 Jan '24 | 9% | 9 | 9 |
433-03 | T12 | 12 months | 31 May '22 | 02 Jun '23 | 51% | 51 | 51 |
476-01 | T13 | 8 months | 06 Sep '22 | 09 May '23 | 5% | 5 | 5 |
482-06 | T14 | 51 months | 19 May '22 | 04 Sep '26 | 5% | 5 | 5 |
482-08 | T15 | 18 months | 06 Jul '22 | 10 Jan '24 | 15% | 15 | 15 |
483-01 | T16 | 12 months | 06 Jan '23 | 10 Jan '24 | 61% | 61 | 61 |
493-01 | T17 | 3 months | 17 Nov '22 | 16 Feb '23 | 30% | 30 | 30 |
495-01 | T18 | 12 months | 26 Jan '23 | 30 Jan '24 | 11% | 11 | 11 |
497-01 | T19 | 12 months | 21 Jul '22 | 25 Jul '23 | 11% | 11 | 11 |
497-01 | T20 | 9 months | 12 Apr '22 | 12 Jan '23 | 8% | 0 | 8 |
497-01 | T21 | 12 months | 17 Jun '22 | 21 Jun '23 | 23% | 23 | 23 |
497-01 | T22 | 10 months | 22 Aug '22 | 23 Jun '23 | 27% | 27 | 27 |
497-02 | T23 | 9 months | 07 Dec '22 | 08 Sep '23 | 15% | 15 | 15 |
497-03 | T24 | 12 months | 08 Dec '22 | 12 Dec '23 | 8% | 8 | 8 |
497-03 | T25 | 12 months | 08 Dec '22 | 12 Dec '23 | 11% | 11 | 11 |
497-04 | T26 | 52 months | 15 Mar '21 | 31 Jul '25 | 2% | 2 | 2 |
549-16 | T27 | 16 months | 12 Nov '21 | 20 Mar '23 | 23% | 23 | 23 |
594-18 | T28 | 16 months | 15 Oct '21 | 20 Feb '23 | 17% | 17 | 17 |
594-18 | T29 | 9 months | 20 Jun '22 | 22 Mar '23 | 25% | 25 | 25 |
Other | T30 | 24 months | 03 Jan '22 | 10 Jan '24 | 10% | 10 | 10 |
Other | T31 | 24 months | 03 Jan '22 | 10 Jan '24 | 9% | 9 | 9 |
I think I have a problem with the filter context. But I can not find how to correct this
Thank you very much for your help
Nicole
Do you have a calendar table in your data model that identifies working days?
When you add the project as the legend then the measure will have to filter by that project, which will then change the result ever so slightly. You would have to use separate charts per project (small multiples for example) to arrive at a more truthy representation. The difference is not that big though.
I used a slightly simple version of your measure
Peak Day = maxx(SUMMARIZE(Days,Days[Date],"s",sum(Days[Resource Demand])),[s])
see attached
Hello @lbendlin,
Thank you very much.
You confirm to me that we can not have the same value by adding the projects as legend.
Nicole
Rethink your use of DISTINCT() - it will yield different results at different granularity levels.
Hello @lbendlin
How could I modify this DAX formula, to avoid this problem?
Moreover I have calculated the same measure with this other DAX formula:
I have the same différence between the 2 line and stacked column charts
Nicole
Hello,
In the second visual it takes the maximum of the sum project by project.
Nicole
Please provide sanitized sample data that fully covers your issue.
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