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Hello,
I have a Power BI line chart that displays lines for specific activities (called drops) each quarter. Each drop is depicted as a trend that shows cumulatively, how many products were sold during that drop. The Date Dimension has a Year->Quarter->Drop Hierarchy. The Drop for the Quarter attribute is a collection of cumulative daily sales points that begin on a specific day in the quarter. Finally, there are four drops per quarter, labeled 1, 2, 3, and 4.
The configuration of the line chart is:
Axis: Elapsed days since drop began
Legend: Drop number
Values: Cumulative sales
Finally, my line chart has three slicers:
1. Year
2. Quarter
3. Drop
My issue is that when I try to plot the values as described above, I end up with drops aggregated when I select multiple quarters and/or multiple years. For example, if I select Drop 1 for all four quarters of 2019, I expect to see FOUR trend lines. However, instead, I see ONE aggregated line.
How can I display the correct trend lines for each distinct drop?
P.S. It has occured to me that I can add a column to my table that contains strings that concatenate the year-quarter-drop (e.g., 2019-1-1) and use that for the legend instead of the drop number, but I would much rather try to see if there is an elegant/simpler solution in Power BI that prevents this aggregation.
Hi, @jondalar
Have you tried to modify the aggregation type as 'Don't summerize'? For further information, please show us your sample data. Do mask sensitive data before uploading. Thanks
Best Regards
Allan
Thanks for your replies. Here are some screenshots that better describe the issue. The first picture shows what the TWO trendlines SHOULD look like. Notice that by making the drop number unique (in the legend), I get two distinct lines for drop 1 in quarters 3 and 4.
In the next screenshot the drop number is simply 1, while still selecting quarters 3 and 4, and as you can see, I only get one trend line. I did set the Summarization property (on the Column tools tab) to "Don't summarize" for both the drop number and cumulative_qrr columns (i.e., the trendline is the cumulative QRR for each drop), but this had no effect.
Can you explain with screen shots?