Forum Discussion
Conditional Formatting in Matrix Visual
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...
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 :
- Please create a month column if it is not already present in the dataset :
- Create below 2 measures (Max_CPU_Average and ConditionalFormatting1) and follow the steps given in previous reply to use the ConditionalFormatting1 measure to get the background color
If this resolves your problem, please select it as the solution
Thanks,
Ankita
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 |