Forum Discussion
Please help in Creating a Chart without Aggregating Values in Power BI
Table named Premium
contains three columns namely
MonthName,
Year ,
AmountTotal
So when I choose
Axis: MonthName
Legend : year
Values : AmountTotal ,
the Amounttotal is aggregated . My question is it should not be aggreagted and show as it is. How can it be achieved
7 Replies
Please anyone help on this ... need to deliver the report and its causing me headache with this aggregation
can you share sample data, it can be done but still need to see the data.
One main thing I want to see if there is more than one row for each month?
This is the sample data , I want the amount total not to be aggregated in the chartPolicyTreaty FiscalMonthNumPerfect Year Sum of EarnTotal
14-15 1 2014 34000
14-15 1 2015 35000
14-15 1 2016 36000
14-15 1 2017 37000
14-15 2 2014 38000
14-15 2 2015 39000
14-15 2 2016 40000
14-15 2 2017 41000
14-15 3 2014 42000
14-15 3 2015 43000
14-15 3 2016 44000
14-15 3 2017 45000
14-15 4 2014 46000
14-15 4 2015 47000
14-15 4 2016 48000
14-15 4 2017 49000
14-15 5 2014 50000
14-15 5 2015 51000
14-15 5 2016 52000
14-15 5 2017 53000
14-15 6 2014 54000
14-15 6 2015 55000
14-15 6 2016 56000
14-15 6 2017 57000
14-15 7 2014 58000
14-15 7 2015 59000
14-15 7 2016 60000
14-15 8 2014 61000
14-15 8 2015 62000
14-15 8 2016 63000
14-15 9 2014 64000
14-15 9 2015 65000
14-15 9 2016 66000
14-15 10 2015 67000
14-15 10 2016 68000
14-15 10 2017 69000
14-15 11 2015 70000
14-15 11 2016 71000
14-15 11 2017 72000
14-15 12 2015 73000
14-15 12 2016 74000
14-15 12 2017 75000
15-16 1 2015 76000
15-16 1 2016 77000
15-16 1 2017 78000
15-16 2 2015 79000
15-16 2 2016 80000
15-16 2 2017 81000
15-16 3 2015 82000
15-16 3 2016 83000
15-16 3 2017 84000
15-16 4 2015 85000
15-16 4 2016 86000
15-16 4 2017 87000
15-16 5 2015 88000
15-16 5 2016 89000
15-16 5 2017 90000
15-16 6 2015 91000
15-16 6 2016 92000
15-16 6 2017 93000
15-16 7 2015 94000
15-16 7 2016 95000
15-16 8 2015 96000
15-16 8 2016 97000
15-16 9 2015 98000
15-16 9 2016 99000
15-16 10 2016 100000
15-16 10 2017 101000
15-16 11 2016 102000
15-16 11 2017 103000
15-16 12 2016 104000
15-16 12 2017 105000
16-17 1 2016 106000
16-17 1 2017 107000
16-17 2 2016 108000
16-17 2 2017 109000
16-17 3 2016 110000
16-17 3 2017 111000
16-17 4 2016 112000
16-17 4 2017 113000
16-17 5 2016 114000
16-17 5 2017 115000
16-17 6 2016 116000
16-17 6 2017 117000
16-17 7 2016 118000
16-17 8 2016 119000
16-17 9 2016 120000
16-17 10 2017 121000
16-17 11 2017 122000
16-17 12 2017 123000
17-18 1 2017 124000
17-18 2 2017 125000
17-18 3 2017 126000
17-18 4 2017 127000
17-18 5 2017 128000
17-18 6 2017 129000
