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I have a matrix visual showing data of 4 months. Computers name in row field, dates of 4 months in Column field and CPU average of every computer in Value field. I want to change background colour of highest CPU average for every month . How can I achieve this in Power BI ?
Solved! Go to Solution.
Hi @Anonymous ,
Thanks for sharing the dataset again. Using the dataset, the output is coming for FEB month as below :
For March:
Please follow the steps given below to get the above output :
If this resolves your problem, please select it as the solution
Thanks,
Ankita
Hi @Anonymous ,
If your expected output is as shown below where the max value is highlighted in the matrix :
Then please follow below steps :
If this resolves your issue, please select the reply as your solution.
Hi ,
I have followed the same steps but still it's not working.
Hi @Anonymous ,
Thanks for sharing the dataset again. Using the dataset, the output is coming for FEB month as below :
For March:
Please follow the steps given below to get the above output :
If this resolves your problem, please select it as the solution
Thanks,
Ankita
Could you please share the error or DAX that you have implemented?
Please find the below DAX which we created based on your reference:
Note: CPU AVG is a table name , CPU Avg is a column name
Hello @Anonymous , and thank you for sharing a question with the Community. The following is informational. Please remember to adhere to the decorum of the Community Forum when asking a question.
Please provide your work-in-progress Power BI Desktop file (with sensitive information removed) that covers your issue or question completely in a usable format (not as a screenshot). You can upload the PBIX file to a cloud storage service such as OneDrive, Google Drive, Dropbox, or to a Github repository, and then share a file’s URL.
https://community.fabric.microsoft.com/t5/Community-Blog/How-to-provide-sample-data-in-the-Power-BI-Forum/ba-p/963216
Please show the expected outcome based on the sample data you provided.
https://community.fabric.microsoft.com/t5/Desktop/How-to-Get-Your-Question-Answered-Quickly/m-p/1447523/highlight/true#M607150
This allows members of the Forum to assess the state of the model, report layer, relationships, and any DAX applied.
Hi,
As requested due to some restriction i'm unable to upload excel file however i have attached the dataset in this message body.
Row Labels | 01-Feb | 02-Feb | 03-Feb | 04-Feb | 05-Feb | 06-Feb | 07-Feb | 08-Feb | 09-Feb | 10-Feb | 11-Feb | 12-Feb | 13-Feb | 14-Feb | 15-Feb | 16-Feb | 17-Feb | 18-Feb | 19-Feb | 20-Feb | 21-Feb | 22-Feb | 23-Feb | 24-Feb | 25-Feb | 26-Feb | 27-Feb | 28-Feb | 29-Feb |
ABC | 3.245776 | 2.93106 | 2.948109 | 2.906601 | 2.994802 | 3.08809 | 3.052478 | 3.033193 | 3.020442 | 2.960306 | 3.022792 | 2.995876 | 3.046906 | 3.120445 | 3.057552 | 2.995227 | 3.022975 | 2.985178 | 3.041812 | 3.100819 | 3.2454 | 3.22864 | 3.453313 | 3.395911 | 3.414993 | 3.233346 | 3.326281 | 3.230541 | 3.209912 |
EFG | 7.019671 | 6.954742 | 6.874146 | 6.944771 | 6.945359 | 6.986665 | 6.964015 | 6.83828 | 6.852804 | 6.97712 | 6.955708 | 6.92042 | 6.981649 | 7.10423 | 7.092111 | 7.090595 | 7.747339 | 7.391184 | 6.655784 | 6.641957 | 6.793372 | 6.606365 | 6.744089 | 6.83737 | 6.859716 | 6.842978 | 6.787913 | 6.782014 | 6.930302 |
HIG | 4.215081 | 4.205673 | 4.352842 | 4.303439 | 4.338703 | 4.369363 | 4.13554 | 4.115388 | 4.088186 | 7.487878 | 7.1475 | 6.916914 | 7.08097 | 7.150508 | 7.052956 | 7.061769 | 7.971821 | 8.391133 | 6.889737 | 7.088427 | 7.335072 | 7.401137 | 7.536386 | 7.75915 | 7.696268 | 8.233905 | 7.953249 | 7.666672 | 7.713544 |
Hi,
I am re-phrasing my problem area again.
I have a matrix visual showing data of 4 months. Computers name in row field, dates of 4 months in Column field and CPU average of every computer in Value field. I want to change background colour of highest value for every month and for every comupter name i.e; each row should have 4 values should get highligted and same could be applicable for all rows in the matrix. Kindly Help me with the resolution
Here i'm attaching the whole data set for better understanding
Row Labels | 01-Feb | 02-Feb | 03-Feb | 04-Feb | 05-Feb | 06-Feb | 07-Feb | 08-Feb | 09-Feb | 10-Feb | 11-Feb | 12-Feb | 13-Feb | 14-Feb | 15-Feb | 16-Feb | 17-Feb | 18-Feb | 19-Feb | 20-Feb | 21-Feb | 22-Feb | 23-Feb | 24-Feb | 25-Feb | 26-Feb | 27-Feb | 28-Feb | 29-Feb | 01-Mar | 02-Mar | 03-Mar | 04-Mar | 05-Mar | 06-Mar | 07-Mar | 08-Mar | 09-Mar | 10-Mar | 11-Mar | 12-Mar | 13-Mar | 14-Mar | 15-Mar | 16-Mar | 17-Mar | 18-Mar | 19-Mar | 20-Mar | 21-Mar | 22-Mar | 23-Mar | 24-Mar | 25-Mar | 26-Mar | 27-Mar | 28-Mar | 29-Mar | 30-Mar | 31-Mar | 01-Apr | 02-Apr | 03-Apr | 04-Apr | 05-Apr | 06-Apr | 07-Apr | 08-Apr | 09-Apr | 10-Apr | 11-Apr | 12-Apr | 13-Apr | 14-Apr | 15-Apr | 16-Apr | 17-Apr | 18-Apr | 19-Apr | 20-Apr | 21-Apr | 22-Apr | 23-Apr | 24-Apr | 25-Apr | 26-Apr | 27-Apr | 28-Apr | 29-Apr | 30-Apr | 01-May | 02-May | 03-May | 04-May | 05-May | 06-May | 07-May | 08-May | 09-May | 10-May | 11-May | 12-May | 13-May | 14-May | 15-May | 16-May | 17-May | 18-May | 19-May | 20-May | 21-May | 22-May | 23-May | 24-May | 25-May | 26-May | 27-May | 28-May | 29-May | 30-May | 31-May |
ABC | 3.245776 | 2.93106 | 2.948109 | 2.906601 | 2.994802 | 3.08809 | 3.052478 | 3.033193 | 3.020442 | 2.960306 | 3.022792 | 2.995876 | 3.046906 | 3.120445 | 3.057552 | 2.995227 | 3.022975 | 2.985178 | 3.041812 | 3.100819 | 3.2454 | 3.22864 | 3.453313 | 3.395911 | 3.414993 | 3.233346 | 3.326281 | 3.230541 | 3.209912 | 3.06939 | 3.086276 | 3.214992 | 3.332429 | 3.531987 | 4.38017 | 4.454582 | 4.203712 | 4.227627 | 4.171633 | 4.164295 | 4.33894 | 4.191572 | 4.200447 | 4.127775 | 4.178199 | 4.222138 | 4.33298 | 4.512986 | 4.283242 | 3.061361 | 3.113764 | 3.065813 | 3.06866 | 3.736458 | 3.01604 | 2.819998 | 2.629012 | 2.573457 | 2.61235 | 2.746112 | 2.847828 | 2.949404 | 2.991171 | 3.043321 | 3.02626 | 3.153112 | 3.122201 | 3.259399 | 3.160183 | 3.187581 | 3.598452 | 3.246137 | 3.266416 | 3.336474 | 3.304811 | 3.230829 | 4.04198 | 3.824973 | 3.190845 | 3.050627 | 2.926364 | 2.977929 | 3.007047 | 3.018291 | 2.956035 | 2.876966 | 2.907845 | 2.850654 | 2.936649 | 2.931553 | 2.91897 | 2.936427 | 3.021741 | 3.010562 | 2.849408 | 2.820951 | 2.740197 | 2.801853 | 2.870882 | 2.904315 | 2.923612 | 2.856269 | 2.829312 | 2.733721 | 2.736908 | 2.949609 | 3.251045 | 2.902697 | 3.03528 | 2.981083 | 2.942972 | 2.888551 | 2.850221 | 2.984866 | 3.004355 | 2.881654 | 2.926332 | 2.984451 | 3.002878 | 4.019996 | 4.093973 |
DEF | 7.019671 | 6.954742 | 6.874146 | 6.944771 | 6.945359 | 6.986665 | 6.964015 | 6.83828 | 6.852804 | 6.97712 | 6.955708 | 6.92042 | 6.981649 | 7.10423 | 7.092111 | 7.090595 | 7.747339 | 7.391184 | 6.655784 | 6.641957 | 6.793372 | 6.606365 | 6.744089 | 6.83737 | 6.859716 | 6.842978 | 6.787913 | 6.782014 | 6.930302 | 6.641757 | 6.718469 | 6.947947 | 6.846355 | 6.972591 | 6.909307 | 6.964281 | 6.910415 | 7.003529 | 6.983161 | 6.974363 | 7.043452 | 6.939253 | 6.98831 | 6.91065 | 8.350034 | 7.382284 | 7.300735 | 7.30439 | 7.785113 | 7.321004 | 7.325001 | 9.403349 | 7.298425 | 7.495832 | 7.86525 | 7.487628 | 7.528857 | 7.657393 | 7.510195 | 9.286267 | 7.225247 | 7.89622 | 7.882157 | 7.895736 | 7.764631 | 7.886143 | 7.981145 | 7.848593 | 7.866019 | 7.821803 | 7.899974 | 7.85886 | 7.910327 | 8.132237 | 8.07512 | 8.013101 | 8.090156 | 7.929945 | 7.853242 | 8.932072 | 9.25461 | 8.081871 | 8.033737 | 7.823791 | 7.726944 | 7.878582 | 7.830606 | 7.878461 | 7.880838 | 8.412342 | 7.443304 | 8.00961 | 7.974067 | 8.248611 | 8.043625 | 8.094024 | 8.097409 | 8.01078 | 8.228728 | 9.3273 | 9.00056 | 9.036677 | 9.154088 | 9.45481 | 8.758509 | 8.763528 | 8.656596 | 8.38026 | 8.437169 | 8.389222 | 8.398948 | 8.445884 | 8.854428 | 8.72204 | 8.508143 | 8.637486 | 8.707839 | 8.502716 | 8.497472 | 8.690714 | 9.198497 |
GHI | 4.215081 | 4.205673 | 4.352842 | 4.303439 | 4.338703 | 4.369363 | 4.13554 | 4.115388 | 4.088186 | 7.487878 | 7.1475 | 6.916914 | 7.08097 | 7.150508 | 7.052956 | 7.061769 | 7.971821 | 8.391133 | 6.889737 | 7.088427 | 7.335072 | 7.401137 | 7.536386 | 7.75915 | 7.696268 | 8.233905 | 7.953249 | 7.666672 | 7.713544 | 7.460795 | 7.519606 | 7.683715 | 7.594292 | 7.910269 | 7.961773 | 7.999784 | 7.830665 | 7.983932 | 8.170864 | 8.439053 | 8.309834 | 8.276048 | 8.415485 | 8.459459 | 8.565166 | 7.001095 | 6.891004 | 7.291339 | 7.817413 | 7.107717 | 7.121167 | 7.118648 | 7.291354 | 7.451692 | 7.523231 | 7.593439 | 7.461174 | 7.557248 | 7.521386 | 8.83043 | 7.309711 | 7.998509 | 8.077515 | 8.349378 | 8.373889 | 8.337172 | 8.612138 | 8.461116 | 8.590288 | 8.335542 | 8.460844 | 8.399891 | 8.346152 | 8.502693 | 8.569057 | 8.609424 | 8.52866 | 8.456807 | 8.53165 | 9.239362 | 7.587701 | 9.041251 | 7.679485 | 7.829651 | 7.60095 | 7.734413 | 7.697742 | 7.590675 | 7.672729 | 8.188152 | 7.984101 | 8.077937 | 8.156973 | 8.125922 | 7.893885 | 8.029476 | 8.149572 | 7.947239 | 8.130045 | 9.132759 | 9.030305 | 9.085874 | 8.939794 | 9.294367 | 8.435759 | 8.714246 | 8.820995 | 8.90232 | 9.13037 | 9.21427 | 9.35914 | 9.45922 | 9.801244 | 9.956006 | 9.939951 | 9.855377 | 9.961893 | 10.81999 | 9.625897 | 10.23691 | 10.11735 |
JKL | 6.985512 | 6.771179 | 6.420013 | 6.599174 | 6.921434 | 6.692304 | 6.648354 | 6.672106 | 6.83702 | 6.375073 | 6.451194 | 6.697211 | 6.911699 | 6.940217 | 6.850909 | 6.932908 | 6.869187 | 6.865522 | 6.926739 | 6.955289 | 6.992228 | 7.020785 | 7.100226 | 7.138665 | 7.185774 | 7.116879 | 7.15579 | 7.075233 | 7.081223 | 6.539243 | 6.303909 | 6.655766 | 6.858507 | 6.843406 | 6.76681 | 6.882103 | 7.503482 | 7.090046 | 7.153272 | 6.705873 | 6.986562 | 6.932012 | 7.243966 | 7.130281 | 7.210777 | 7.278994 | 7.388262 | 7.418765 | 7.342044 | 7.379343 | 7.393087 | 7.333223 | 7.440471 | 7.448555 | 7.523805 | 7.37266 | 7.388847 | 7.516759 | 7.34294 | 7.392543 | 7.370179 | 7.826197 | 7.801821 | 7.898813 | 7.86241 | 8.172781 | 7.747136 | 7.957314 | 7.853387 | 7.759688 | 7.855832 | 7.866072 | 9.086322 | 7.604269 | 7.484297 | 7.619321 | 7.682413 | 9.237487 | 7.626125 | 7.639379 | 7.61254 | 7.551986 | 7.735046 | 7.649145 | 7.605315 | 7.689857 | 7.645417 | 7.776051 | 7.76002 | 7.76519 | 7.563851 | 7.671823 | 7.831358 | 7.850886 | 7.546145 | 7.68857 | 7.790866 | 7.689947 | 7.923901 | 8.932606 | 8.746556 | 8.858991 | 8.784737 | 8.662896 | 8.571929 | 8.811523 | 8.724541 | 8.834073 | 8.790575 | 8.897497 | 8.74917 | 8.999323 | 8.906557 | 8.989048 | 8.846009 | 9.052123 | 9.145074 | 8.756013 | 8.850691 | 8.801747 | 8.743147 |
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