Forum Discussion
NORM.DIST Issues
anyone able to help me with this function.
im getting different results on my data set compared to someone else.
is it okay to have multiple values for X?
i made another fake set of data that only ever has 1 value for X and it doesn't seem to have this problem
Also, when making the calculated column. for NORM .DIST. does it interact with filters?
I noticed when i hard code in 0 and 113 from the unfiltered page and then bring that curve into a page with the measure one, they both have the same curve.
we used the Python visual instead. This visual is dynamic 🙂
5 Replies
Also, when making the calculated column. for NORM .DIST. does it interact with filters?Calculated columns do not react to filters by themselves. But they can be used in a measure that is impacted by filters.
yeah i need this is a measure, is there anyway to use NORM.DIST as a measure?
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Hi Robert14358 ,
Thanks lbendlin answer , and I have some other suggestions:
The DIST function is designed to use a single value for each calculation, X. If you enter an array or multiple values for X in a single function call, it may not work as expected. For datasets in which X can accept multiple values, you would typically apply the NORM.DIST function to iterate over each value of X separately, either by iterating in a script or by iterating in a column of the computation that handles each row separately.
As for the interaction with filters, calculated columns in Power BI are calculated during data refresh and are not dynamically recalculated when filters are applied in the report. This means that values in calculated columns, such as with the NORM.DIST function, remain static and do not change based on filters applied in the report view. However, metrics in Power BI interact with filters and are recalculated based on the current filter context.
If you observe that the hard-coded value generates the same curve regardless of the filter applied, it is consistent with the expected behavior of the calculated column. For dynamic interactions with filters, consider using metric values instead of computed columns where feasible.
Best Regards,
Xianda Tang
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we used the Python visual instead. This visual is dynamic 🙂
