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Hello Community,
I have below Sales metric data source in one database table:
Metric Name | City Name | Target | Actual | Time Period |
New Clients | New York | 25% | 15% | Jan-20 |
New Clients | New York | 25% | 10% | Feb-20 |
New Clients | New York | 25% | 10% | Mar-20 |
New Clients | Boston | 25% | 20% | Jan-20 |
New Clients | Boston | 25% | 30% | Feb-20 |
New Clients | Boston | 25% | 35% | Mar-20 |
Returning Clients | New York | 40% | 55% | Jan-20 |
Returning Clients | New York | 40% | 35% | Feb-20 |
Returning Clients | New York | 40% | 40% | Mar-20 |
Returning Clients | Boston | 40% | 35% | Jan-20 |
Returning Clients | Boston | 40% | 25% | Feb-20 |
Returning Clients | Boston | 40% | 60% | Mar-20 |
I am trying to achieve the below result in Matrix Visual which shows totals for the rows but Average for the Metric Name category:
Metric Name | Target | City Name | Jan-20 | Feb-20 | Mar-20 |
New Clients | 25% | New York | 15% | 10% | 10% |
Boston | 20% | 30% | 35% | ||
Average | 18% | 20% | 23% | ||
Returning Clients | 40% | New York | 55% | 35% | 40% |
Boston | 35% | 25% | 60% | ||
Average | 45% | 30% | 50% |
In matrix visual I find it challenging to have the first two columns and also having average as a sub-total but sum as a total for cities. Any guidance will be appreciated.
Thanks,
Jay
Solved! Go to Solution.
Hi @Anonymous ,
If you use the matrix visual of Power BI, the [Target] field cannot be displayed independently. So you may need to create two matrix.
If you cannot accept this, you may need to use a custom matrix visual.
Best regards,
Lionel Chen
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi @Anonymous ,
If you use the matrix visual of Power BI, the [Target] field cannot be displayed independently. So you may need to create two matrix.
If you cannot accept this, you may need to use a custom matrix visual.
Best regards,
Lionel Chen
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
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