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aoifoc
Frequent Visitor

Different values when entered in card / clustered column chart (Count Distinct)

I am working on a dashboard about student interactions with gym facilities, and I have included a clustered column chart showing both total sessions (individual gym visits) and unique users (distinct students, based on their unique ID).

 

The clustered column chart seems to be displaying incorrect values for the number of unique users. In the screenshot below you will see that a simple card visual set to show "Count (Distinct) of Unique User ID" will correctly count a total of 2252 unique users.

 

However the clustered column chart values in green, which has the exact same setting ("Count (Distinct) of Unique User ID") comes to 2255 when added up.

 

I've double checked filters and there is no reason why the Count (Distinct) total in the card should be different from the Count (Distinct) total in the chart.

 

Any ideas - or could this be a problem with the chart itself?

 

Clustered chart error

1 ACCEPTED SOLUTION

How is the relationship between students and faculties?

One possible explaination could be, that one student is member of more than one faculty. In particular in your case: 3 students (the difference between 2255 and 2252) are member of two different faculties each. Or one student is member of 4 faculties.

Markus Ehrenmueller-Jensen
@MEhrenmueller

View solution in original post

3 REPLIES 3

How is the relationship between students and faculties?

One possible explaination could be, that one student is member of more than one faculty. In particular in your case: 3 students (the difference between 2255 and 2252) are member of two different faculties each. Or one student is member of 4 faculties.

Markus Ehrenmueller-Jensen
@MEhrenmueller

Thanks Markus, that turned out to be the exact problem! I had (wrongly) assumed that because my card visual was showing the right total, the issue was with Power BI rather than my own dataset. I've marked your reply as the solution - thanks again!

You are welcome @aoifoc!

 

I ran into similar problems just too often - so now it's one of the first things I check. 🙂

 

 

Markus Ehrenmueller-Jensen
@MEhrenmueller

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