Forum Discussion

Anonymous's avatar
Anonymous
Not applicable
9 months ago
Solved

Creating a visual using several filters

Hi   Im trying to create a table or stacked bar chart which shows data for multiple criteria.   So as an example i have a dataset which has numerous contracts and some data is missing in various ...
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  • nielsvdc's avatar
    nielsvdc
    9 months ago

    Hi Anonymous,

     

    You might want to create a calculated column named IsMissingData in the table, that checks rows for missing column data. The calculated column checks every required column for missing values. If any required column is missing data, you can set the column value to TRUE. You can use this column to show any rows with missing data.

    IsMissingData =
VAR colA = IF(ISBLANK([Column A]), TRUE, FALSE)
VAR colB = IF(ISBLANK([Column B]), TRUE, FALSE)
VAR colC = IF(ISBLANK([Column C]), TRUE, FALSE)

RETURN
  AND(AND(colA, colB), colC)

     

    You can also create a create a calculated column named NumberOfColumnsMissingData in the table, that counts the number of required columns that are missing data.

    NumberOfColumnsMissingData = 
VAR colA = IF(ISBLANK([Column A]), 1, 0)
VAR colB = IF(ISBLANK([Column B]), 1, 0)
VAR colC = IF(ISBLANK([Column C]), 1, 0)

RETURN
  colA+colB+colC

     

    Hope this helps. If so, please give a Kudos 👍 and mark as Accepted Solution ✔️.

Anonymous's avatar
Anonymous
Not applicable
9 months ago

Hi Anonymous ,

Thank you for reaching out to the Microsoft fabric community forum.

 

The behavior you are seeing is expected because applying multiple filters on missing values works as an intersection, so only records where all selected fields are blank are returned.

To achieve your requirement of showing individual missing counts per column for each owner within one visual, you will need to create row-level indicators (calculated columns or measures) for each missing field and then use those fields in your visual. This enables independent aggregation instead of intersection filtering.

If you can provide a small sample dataset, we can validate the model and share the exact DAX pattern aligned to your structure.

Also thank you nielsvdc and PhilipTreacy  for you response.

 

Thank you.