I am having an issue using the Distinctcount function in DAX. I have a table with a total of 1,154,493 rows. I have a measure created to count the number of distinct values in column 1. I have another measure created to count the number of distinct values in column 1 with filters. I have a 3rd and final measure created to count the number of distinct values of column 1 with different filters. The issue I am running into is the count of measure 2 + measure 3 should equal measure 1 however added together they are GREATER than the value of measure 1 which is just a grand total. How is this possible? Unfortunately I can't share the table but below is the code I am using for the two measures:
Measure1=distinctcount('Table1'[Column1])
Measure2=calculate(distinctcount('Table1'[Column1]),'Table1'[CTest] = 1,'Table1'[CTest2] = "07")
Measure3=calculate(distinctcount('Table1'[Column1]),'Table1'[CTest] = 2,'Table1'[CTest2] = "07")
I am at a loss. Thank you in advance!!
For troubleshooting you should identify values of Column1 with Measure2 and Measure3 > 0, those are being added twice.
I needed to replace this measure:
CALCULATE([GM % YTD], SAMEPERIODLASTYEAR('Date'[Date]))
By this one:
VAR VAR1 = ADDCOLUMNS( VALUES(Revenue[Key_Client]),
"Col1", CALCULATE([GM % YTD], SAMEPERIODLASTYEAR('Date'[Date]),
REMOVEFILTERS(Revenue[Type],Revenue[SectorType]))
)
RETURN AVERAGEX(VAR1, [Col1])
Both measures point to GM % YTD, which is:
CALCULATE([GM %], DATESYTD('Date'[Date],"31/05"))
I get this, when I display them side by side:
The values are ok, my problem is with the Total. I am unable to find how/where is the aggregation on the left column done... How is that 73,2% achieved? It doesn't seem to be average...
Also… how can I force the measure on the right to do the same aggregation?
In the ADDCOLUMNS version, you are iterating over each Revenue[Key_Client] and only averaging after the [GM % YTD] has been calculated for each one separately. For a single client, there's only one thing to average, so the value isn't affected by that step.
Generally, you want to compute the measure over all clients together rather than averaging the individual numbers together to get a standard weighted average rather than an average where all clients are weighted equally.
I am trying to get my head around DAX and am struggling. I have a PowerBI Matrix in which I need to calculate the average of a measure. The measure is '% of population' and on the surface it appears to work exactly as expected.
It calculates correctly in the top matrix for the two levels and also summarises correctly in the bottom table.
As an example, I have highlighted in red the order of calculations for "A3"
For the record the % population is set to
% of Population = sum(Data[Value])/sum('Level'[Population])
The problem occurs when I filter on the Country and only select Country 2...
Country 2 does not have data for "D13". Although the Values sum up correctly (170), the Sum of the Population includes the 300 from the missing D13 row making a total of 600 and the '% population' of 28.33% (instead of 170 / 300 = 57%)
I am happy to turn off the group totals in the top grid so that the 28.33 does not show; so my real problem is actually with the bottom grid.
I think I need a new measure to be displayed in the bottom grid. I think it simply needs to sum up the values and divide by the sum of the populations - but only when the value is present. How do I do that?
Or am I totally on the wrong track and there is an obvious answer that I am missing?
The PowerBI file can be downloaded from here
Thanks in advance.
The reason this is happening is that the Country table does not filter the Level table in the relationship diagram since they both only filter one way to the Data table and there are no other relationships.
Without changing your data model, one way to fix this in DAX is to specify that you only want to count Population where Level[LevelId] matches a Data[SecondLevelId] in your current filter context.
Population =
DIVIDE (
SUM ( Data[Value] ),
CALCULATE (
SUM ( 'Level'[Population] ),
'Level'[LevelId] IN VALUES ( Data[SecondLevelId] )
)
)
I can't get a division correct with this sample data:
Calculated column Another calc. column
48 207
257 370
518 138
489 354
837 478
1,005 648
1,021 2,060
1,463 2,164
2,630 1,818
2,993 2,358
3,354 3,633
4,332 5,234
4,885 6,108
4,514 6,008
4,356 6,888
4,824 7,382
7,082 5,988
7,498 6,059
4,865
4,192
3,816
2,851
2,768
2,093
2,207
770
397
149
178
336
167
124
18
What I'm trying to do is to create a new calculated column.
For each row I want to get the value of Calculated column and divide it by the Total of Another calc. column.
The Total of Another calc. column = 82826
This is the desired output in a brand new calculated column, let's call it % Column:
% Column
0,000579528167484
0,003102890396735
0,006254074807428
.
.
.
NOTE - these 3 columns: Calculated column, Another calc. column and % Column are all in the same table and are all calculated columns.
I tried lots of formulas but not a single one returned the desired output. :| I guess it's because of the nature of calculated columns or I'm not getting the gist of it.
Is this even possible or I should follow another path using a Measure?
Can you shed some light?
####### EDIT #######
I put together a sample file to help debugging this. Here it is:
https://drive.google.com/open?id=1r7kiIkwgHnI5GUssJ6KlXBAoeDRISEuC
As you see:
Earned Daily % HARDCODED works just fine because 82826 is hardcoded as the denominator.
Earned Daily % by StelioK and Earned Daily % by Alexis Olson output the same wrong value for the division when using SUM formula.
I'm using the latest Power BI Desktop version if that matters: Version: 2.70.5494.701 64-bit (June 2019)
Basically, there is nothing wrong with the calculated columns, and both Alexis and StelioK formulas are correct.
The root problem here is a confusion between calculated columns and measures. You are looking at the results in a conceptually wrong way - through the matrix visual, with several filters active on slicers. If you remove the filters, you will see that the total amount is 140,920, not 82,826. The latter number is the total for the filtered data set, not the entire table.
To get this right, you need to understand several fundamental concepts behind Power BI:
Calculated columns are always static. Once a calculation is
completed, it can not respond to slicers or other UI controls. It's
just static data, identical to data in non-calculated columns. DAX
formulas used to calculate columns are active only when you create
them, or upon data reload.
If you want your calculations to respond to slicers etc, they must be measures. It's the only way, no exceptions.
Avoid calculated columns, they are utterly useless. Power BI is all about measures; I can't think of a single reason for using calculated columns. When you add a column, you are essentially enhancing your source data, because you feel like you are missing something you need for your report. But that need can be much better addressed at the source (database or file you import), or using Power Query, which is designed exactly for this kind of tasks. The best practice is: build your columns at the source, for everything else design measures.
Another important advice: never drop fields (columns) into visuals directly. Always write a DAX measure, and then use it. Relying on Power BI auto-aggregations is a very bad practice.
You can do this by using the following DAX:
% Column =
VAR TotalSum =
SUM ( 'Table'[Another Calc column] )
RETURN
IF (
NOT ( ISBLANK ( 'Table'[Calc Column] ) ),
CALCULATE ( DIVIDE ( SUM ( 'Table'[Calc Column] ), TotalSum ) ),
0
)
Which yields the following:
I Hope it helps!!
For me the following works:
DIVIDE( Table1[Calculated column], SUM(Table1[Another calc column]) )
If that's not working, I'd need to see a file where you can reproduce the problem.
Edit: After looking at your file, the total of 82,826 is only true with the filters you've selected.
Note that calculated columns are not dynamic and cannot be responsive to filters since they are calculated only when the table is first loaded.
If you need it to be dynamic, then write it as a measure more like this:
Earned Daily =
DIVIDE (
CALCULATE (
SUM ( 'Test data'[Value] ),
'Test data'[Act Rem] = "Actual Units",
'Test data'[Type] = "Current"
),
CALCULATE (
SUM ( 'Test data'[Value] ),
ALLSELECTED ( 'Test data' ),
'Test data'[Act Rem] = "Remaining Units",
'Test data'[Type] = "PMB"
)
)
I've been struggling to find a way to achieve the result of a matrix visualization in Power BI, in a line and clustered column chart.
I have tried using ALLSELECTED, ALL, ALLEXCEPT in order to ignore one filter but no matter how I try it, I'm not reaching my end goal.
CarCountPerCategory =
CALCULATE(
DISTINCTCOUNT(Table[CarID]),
ALLSELECTED(Table[Filter])
)
This still breaks down the measure to the Filter level instead of ignoring it. I am looking for something that will give me the total distinct count regardless of the Filter column. E.g. TimesReshopped 1 - 190 on all 3 columns, TimesReshopped 2 - 182 on all 3 columns of the Filter Column series. I need this as a sidestep in order to divide the distinct car count to the total distinct car count per times reshopped in order to reach the percentage that I am looking for. (the one in the matrix)
Can someone help me with some advice? Thank you.
Try this:
[Total Category Count]:=
SUMX ( SUMMARIZE ( Table, Table[TimesReshopped] ), [Count of CarID] )
I got to the bottom of this by using ALLEXCEPT and providing all the filter that I was using:
CarCountPerCategory =
CALCULATE(
DISTINCTCOUNT(Table[CarID]),
ALLEXCEPT(Table,Table[Year],Table[Month],Table[LocationName],Table[CustCode],Table[TimeReshoped])
)