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hi everyone im having issue to show the visual below as im pretty new to Power BI
i would like to show by country (legend) the simple moving averages (value ) and the shared axis being the report run date.
below is the sample data
Payer Number | CountryCode | Report Run Date | TotalExposureUSD |
1 | SK01 | 31-08-20 | 0.022227 |
1 | SK01 | 28-08-20 | 0.022227 |
1 | SK01 | 26-08-20 | 0.022227 |
1 | SK01 | 25-08-20 | 0.022227 |
1 | SK01 | 21-08-20 | 0.022227 |
1 | SK01 | 19-08-20 | 0.022227 |
1 | SK01 | 17-08-20 | 0.022227 |
1 | SK01 | 14-08-20 | 0.022227 |
1 | SK01 | 12-08-20 | 0.022227 |
1 | SK01 | 10-08-20 | 0.022227 |
1 | SK01 | 07-08-20 | 0.022227 |
1 | SK01 | 05-08-20 | 0.022227 |
1 | SK01 | 03-08-20 | 0.022227 |
1 | SK01 | 31-07-20 | 0.01667 |
1 | SK01 | 29-07-20 | 0.01667 |
1 | SK01 | 27-07-20 | 0.01667 |
1 | SK01 | 22-07-20 | 0.01667 |
1 | SK01 | 20-07-20 | 0.01667 |
1 | SK01 | 17-07-20 | 0.01667 |
1 | SK01 | 15-07-20 | 0.01667 |
1 | SK01 | 13-07-20 | 0.01667 |
1 | SK01 | 10-07-20 | 0.01667 |
1 | SK01 | 08-07-20 | 0.01667 |
1 | SK01 | 06-07-20 | 0.01667 |
1 | SK01 | 03-07-20 | 0.01667 |
1 | SK01 | 01-07-20 | 0.01667 |
1 | SK01 | 29-06-20 | 0.011113 |
1 | SK01 | 24-06-20 | 0.011113 |
1 | SK01 | 22-06-20 | 0.011113 |
1 | SK01 | 19-06-20 | 0.011113 |
1 | SK01 | 17-06-20 | 0.011113 |
1 | SK01 | 15-06-20 | 0.011113 |
1 | SK01 | 12-06-20 | 0.011113 |
1 | SK01 | 10-06-20 | 0.011113 |
1 | SK01 | 08-06-20 | 0.011113 |
1 | SK01 | 01-06-20 | 0.011113 |
1 | SK01 | 29-05-20 | 0.005557 |
1 | SK01 | 22-05-20 | 0.005557 |
1 | SK01 | 15-05-20 | 0.005557 |
1 | SK01 | 08-05-20 | 0.005557 |
1 | SK01 | 30-04-20 | 0 |
1 | SK01 | 24-04-20 | 0 |
1 | SK01 | 16-04-20 | 0 |
1 | SK01 | 07-04-20 | 0 |
2 | SK01 | 03-07-20 | 0.270229 |
2 | SK01 | 06-07-20 | 0.270229 |
2 | SK01 | 08-07-20 | 0.270229 |
2 | SK01 | 10-07-20 | 0.32537 |
2 | SK01 | 13-07-20 | 0.32537 |
2 | SK01 | 22-07-20 | 0.370226 |
2 | SK01 | 15-07-20 | 0.32537 |
2 | SK01 | 27-07-20 | 0.370226 |
2 | SK01 | 17-07-20 | 0.370226 |
2 | SK01 | 29-07-20 | 0.370226 |
2 | SK01 | 07-04-20 | 0 |
2 | SK01 | 16-04-20 | 0 |
2 | SK01 | 24-04-20 | 0 |
2 | SK01 | 30-04-20 | 0 |
2 | SK01 | 08-05-20 | 0.005557 |
2 | SK01 | 15-05-20 | 0.005557 |
2 | SK01 | 22-05-20 | 0.057414 |
2 | SK01 | 29-05-20 | 0.057414 |
2 | SK01 | 01-06-20 | 0.06297 |
2 | SK01 | 08-06-20 | 0.11458 |
2 | SK01 | 10-06-20 | 0.11458 |
2 | SK01 | 12-06-20 | 0.11458 |
2 | SK01 | 15-06-20 | 0.163029 |
2 | SK01 | 19-08-20 | 0.412584 |
2 | SK01 | 17-06-20 | 0.163029 |
2 | SK01 | 19-06-20 | 0.213209 |
2 | SK01 | 22-06-20 | 0.213209 |
2 | SK01 | 24-06-20 | 0.213209 |
2 | SK01 | 29-06-20 | 0.264672 |
2 | SK01 | 01-07-20 | 0.270229 |
2 | SK01 | 20-07-20 | 0.370226 |
2 | SK01 | 31-07-20 | 0.370226 |
2 | SK01 | 03-08-20 | 0.412584 |
2 | SK01 | 05-08-20 | 0.412584 |
2 | SK01 | 07-08-20 | 0.412584 |
2 | SK01 | 10-08-20 | 0.412584 |
2 | SK01 | 12-08-20 | 0.412584 |
2 | SK01 | 14-08-20 | 0.412584 |
2 | SK01 | 17-08-20 | 0.412584 |
2 | SK01 | 21-08-20 | 0.412584 |
2 | SK01 | 25-08-20 | 0.412584 |
2 | SK01 | 26-08-20 | 0.412584 |
2 | SK01 | 28-08-20 | 0.412584 |
2 | SK01 | 31-08-20 | 0.412584 |
4 | IN02 | 01-06-20 | 0.1234 |
4 | IN02 | 02-06-20 | 0.564 |
4 | IN02 | 03-06-20 | 0.225 |
4 | IN02 | 07-07-20 | 0.1553 |
4 | IN02 | 08-07-20 | 0.169 |
4 | IN02 | 09-07-20 | 0.122 |
4 | IN02 | 01-08-20 | 0.1365 |
4 | IN02 | 02-08-20 | 0.188 |
4 | IN02 | 03-08-20 | 0.889 |
4 | IN02 | 04-08-20 | 0.954 |
4 | IN02 | 05-08-20 | 0.44 |
many thanks for the help provided 🙂
Solved! Go to Solution.
Hi @Ishallown ,
You can create this measure:
Measure =
CALCULATE(
AVERAGE('Table'[Total Exposure USD]),
ALLEXCEPT(
'Table',
'Table'[Report Run Date]
)
)
Use a line chart to show the result:
Attached a sample file in the below, hopes to help you.
Best Regards,
Yingjie Li
If this post helps then please consider Accept it as the solution to help the other members find it more quickly.
Hi @Ishallown ,
You can create this measure:
Measure =
CALCULATE(
AVERAGE('Table'[Total Exposure USD]),
ALLEXCEPT(
'Table',
'Table'[Report Run Date]
)
)
Use a line chart to show the result:
Attached a sample file in the below, hopes to help you.
Best Regards,
Yingjie Li
If this post helps then please consider Accept it as the solution to help the other members find it more quickly.
@Ishallown , not sure what is the challenge , refer this
https://docs.microsoft.com/en-us/power-bi/visuals/power-bi-visualization-combo-chart
You can have Avg like
Cumm Avg= CALCULATE(Average(Sales[Sales Amount]),filter(date,date[date] <=maxx(date,date[date])))
Cumm Avg= CALCULATE(Average(Sales[Sales Amount]),filter(date,date[date] <=max(Sales[Sales Date])))
Cumm Sales = CALCULATE(Sum(Sales[Sales Amount]),filter(date,date[date] <=max(Sales[Sales Date]))) / CALCULATE(distinctcount(Sales[Sales Date]]),filter(date,date[date] <=max(Sales[Sales Date])))
Rolling 7 day = CALCULATE(sum(Sales[Sales Amount]),DATESINPERIOD('Date'[Date],MAX(Sales[Sales Date]),-7,Day)) /7
Rolling 7 day = CALCULATE(Average(Sales[Sales Amount]),DATESINPERIOD('Date'[Date],MAX(Sales[Sales Date]),-7,Day))
@Ishallown
Add a Dates Table to your model and link to your date and create the below formula, I made the past 7 days average, you can change as necessary.
Moving AVerage =
AVERAGEX(
DATESINPERIOD('Calendar'[Date] , LASTDATE('Calendar'[Date] ) ,-7,DAY),
CALCULATE(SUM('Table'[TotalExposureUSD])
)
)
________________________
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Hi Fowmy,
would you be able to explain in terms of what is going on within the formula as i want to learn what is going on . sorry for the trouble im a newbie with dax
thanks !
The measure calculates the average based on the date window of the past 7 days.
The DATESINPERIOD function creates that date window from the current point on the axis -t days if you are on the chart say 10th July, it takes from 10th July back to 4th July.
Then, the AVERAGEX add each USD Value and gives the average of it
------------------------------------------------------
Moving AVerage =
AVERAGEX(
DATESINPERIOD('Calendar'[Date] , LASTDATE('Calendar'[Date] ) ,-7,DAY),
CALCULATE(
SUM('Table'[TotalExposureUSD])
)
)
________________________
If my answer was helpful, please consider Accept it as the solution to help the other members find it
Click on the Thumbs-Up icon if you like this reply 🙂
⭕ Subscribe and learn Power BI from these videos
⚪ Website ⚪ LinkedIn ⚪ PBI User Group
Hi @Ishallown ,
Could you please tell me the logic of your simple moving averages?
It's better to clarify it using your sample data and please also help to show the desired results.
Thanks.
Aiolos Zhao
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