Line Segment and Legend Color Based on Measures
Conditional formatting in Power BI just got a solid upgrade. In the July 2026 update, conditional formatting now works on Line Charts and visuals with Legends. This was one of the most requested features. It lets you apply data-driven colors across multiple visual types and keep colors consistent throughout your reports. Up until recently, when I used to interview Power BI professionals with a lot of experience in visualization, I had a good way to test them. I'd ask one of these questions: Which visuals don't support conditional formatting? I made some changes to my visual and now the conditional formatting option isn't showing. Why? How do you apply conditional formatting on Line and Pie visuals? It was an easy way to catch gaps. Conditional formatting wasn't supported on legends. For Pie visuals, the workaround was to apply it on a Bar chart first and then switch to Pie. For Line visuals, we used to get extra color markers the same way. Power BI has been improving its visualization experience steadily over the last two years, with big updates coming regularly. This long-awaited feature finally made it into the July 2026 update. Conditional formatting is now supported on Line visuals and Legends. Why it was needed on Line visuals Just like any other visual, you sometimes need line segments to change color based on a condition. This helps explain things like margins going down or current year vs previous year comparisons. Why it was needed on Legends Say your company always uses one color and your competitor uses another. On a report showing market share, you'd always want your company represented by the same color. That was possible for axis values but not for legends. This update fixes that. You can now apply conditional formatting on Pie, Stacked, and any other visual that uses a legend. Please find the file where I have used different measures to do conditional formatting on Line and Legends Measure used Brand Color = SWITCH ( TRUE (), Max('Item'[Brand])= "Brand 1", "Yellow", Max('Item'[Brand])= "Brand 2", "Green", Max('Item'[Brand])= "Brand 3", "Blue", Max('Item'[Brand])= "Brand 4", "Red", Max('Item'[Brand])= "Brand 5", "Orange", Max('Item'[Brand])= "Brand 6", "Purple", Max('Item'[Brand])= "Brand 7", "Pink", Max('Item'[Brand])= "Brand 8", "Cyan", Max('Item'[Brand])= "Brand 9", "Lime", Max('Item'[Brand])= "Brand 10", "Brown", Max('Item'[Brand])= "Brand 11", "Gray", Max('Item'[Brand])= "Brand 12", "Teal", Max('Item'[Brand])= "Brand 13", "Magenta", "Other" ) Category Measure Category Color = SWITCH ( TRUE (), Max('Item'[Category] )= "Category 1", "Red", Max('Item'[Category] )= "Category 2", "Green", Max('Item'[Category] )= "Category 3", "Blue", Max('Item'[Category] )= "Category 4", "Yellow", Max('Item'[Category] )= "Category 5", "Orange", "Black" ) Color Year Max Year = max('Date'[Year]) You can also check the video on the same - https://www.youtube.com/watch?v=SDX1gUpcJaw&list=PLPaNVDMhUXGYo50Ajmr4SgSV9HIQLxc8L&index=1
Better Rolling Average
Continuing with exploring alternatives to Power BI's default quick measures that don't involve the CALCULATE function, such as Better Running Total, Better Average per Category, Better Weighted Average per Category, Better Filtered Value, Better Sales from New Customers, and Year to Date Total and Year Over Year Change, this one tackles Rolling Average. Power BI's Rolling Average quick measure returns something like this: Value rolling average = IF( ISFILTERED('Dates'[Date]), ERROR("Time intelligence quick measures can only be grouped or filtered by the Power BI-provided date hierarchy or primary date column."), VAR __LAST_DATE = ENDOFMONTH('Dates'[Date].[Date]) VAR __DATE_PERIOD = DATESBETWEEN( 'Dates'[Date].[Date], STARTOFMONTH(DATEADD(__LAST_DATE, -3, MONTH)), __LAST_DATE ) RETURN AVERAGEX( CALCULATETABLE( SUMMARIZE( VALUES('Dates'), 'Dates'[Date].[Year], 'Dates'[Date].[QuarterNo], 'Dates'[Date].[Quarter], 'Dates'[Date].[MonthNo], 'Dates'[Date].[Month] ), __DATE_PERIOD ), CALCULATE(SUM('Table'[Value]), ALL('Dates'[Date].[Day])) ) ) Perhaps a better way: Better Rolling Average = VAR __EndDate = MAX('Table'[Date]) VAR __3MonthsAgo = EOMONTH(__EndDate, -3) VAR __StartDate = DATE(YEAR(__3MonthsAgo), MONTH(__3MonthsAgo), 1) VAR __Table = SUMMARIZE( FILTER(ALL('Table'),[Date]>=__StartDate && [Date]<=__EndDate), 'Table'[Month], "__Value",SUM('Table'[Value]) ) RETURN AVERAGEX(__Table,[__Value]) And the video: eyJrIjoiZjc5MDlhYjktOWYzZi00YzM3LWFlYWEtYWMyMGQyNzM4NGYwIiwidCI6IjRhMDQyNzQzLTM3M2EtNDNkMi04MjdiLTAwM2Y0YzdiYTFlNSIsImMiOjN9Patient Cohort (AND Slicer)
In the healthcare field, it is often desireable to identify a cohort of patients with similar, multiple diagnoses. This quick measure returns a comma-delimited list of patients that have all been identified with the same diagnoses. The tricky part here is that this allows the user to select from a slicer the diagnoses for which the user is interested in obtaining a cohort. Identified patients have had diagnoses that meet all of the selected criteria. In other words, all patients have had diagnoses for all of the selected diagnoses in the slicer. Essentially creates an AND for the slicer as opposed to the normal OR. Cohort = VAR tmpTable1 = GENERATE(VALUES(Diagnosis[Patient]), EXCEPT( VALUES(Diagnosis[Diagnosis]), CALCULATETABLE(VALUES(Diagnosis[Diagnosis])))) VAR tmpTable2 = SUMMARIZE(tmpTable1,Diagnosis[Patient]) VAR tmpTable3 = EXCEPT(VALUES(Diagnosis[Patient]),tmpTable2) RETURN CONCATENATEX(tmpTable3,[Patient],",") This quick measure would take two inputs, the column for the ID to return (Patient) and the column for the slicer selection (Diagnosis) Also included is the trivial variation, Count of Cohort: Count of Cohort = VAR tmpTable1 = GENERATE(VALUES(Diagnosis[Patient]), EXCEPT( VALUES(Diagnosis[Diagnosis]), CALCULATETABLE(VALUES(Diagnosis[Diagnosis])))) VAR tmpTable2 = SUMMARIZE(tmpTable1,Diagnosis[Patient]) VAR tmpTable3 = EXCEPT(VALUES(Diagnosis[Patient]),tmpTable2) RETURN COUNTROWS(tmpTable3) eyJrIjoiZWYwNzZlNzctOTc5NC00ZWU1LWI2OWMtYTZjYTI0MjIzMjEzIiwidCI6IjRhMDQyNzQzLTM3M2EtNDNkMi04MjdiLTAwM2Y0YzdiYTFlNSIsImMiOjN9create measures with filters
Hello, I need to create measures using some filter to be able to make some card visuals. here is what I did: I have my date base with all years information, so for making the "sales per year" i made to measures: 2025 = SUM(...) and filtered in 2025 poryjected sales. 2024 = CALCULATE([Facturación],SAMEPERIODLASTYEAR('Calendar'[Date])) - I created a measure of get the sales of previous year. than I made a measure to get the difference between both 2024 adn 2025 sales. WHAT I SHOULD DO: I made to charts one "increasing of sales" detailed all the "clientes" that has a positive result and I was using the filter panel. and another of "lost sales" with all the negative results. I need to add some cards to summarize the totals. I have one showing the total of sales in 2025 I need a card showing the total of increaisng sales that is "2,066,314" and a card showing the total of lost sales that is "-919,865" thank you!
Dashboard Template
A Power BI template featuring a heatmap as a calendar-formatted matrix and buttons that reference bookmarks for day, week, month, quarter, and year to adjust the date timeline selection and the X-axis date hierarchy on trend charts. It includes date filtering options based on timeframes and ageing. This template was developed for on-premises Power BI Report Server but also works in the Service. The test data was created by using https://mockaroo.com/ .Visuals not displaying any data
Hello everyone, I've built a report that is to be used to summarise various economic data. I have been trying to add a slicer into my Power BI report to filter by country across all pages. I had managed to do this, but as soon as I deselected that country and chose another, the visuals wouldn't load. Having deleted the slicer, I cannot revert back either and now all visuals (charts/graphs) that would have been affected by the fitler are now blank. How do I rectify this? - My look clean (None across all pages, 'all' selected on each visual, etc.) - Table mapping of relationships appears correct - Table validation is also okay (e.g. for Italy there is GDP data, it just won't show in the visual) Am I missing something obvious? Thanks in advance!
