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Anonymous
Not applicable

Calculate Running Total based on 2 Date Columns

Hi,

 

I have a Leavers list in Table having their Month of Leaving and Month of Joining.

 * My Date table is linked to Month of Leaving.

 

I want a monthly trend / Running Total showing Sum of Leavers (who left in last 3 months and their month of joining is also in the last 3 months).

 

I am quite new to Power BI, can someone help me with the solution please?

1 ACCEPTED SOLUTION

Hi @Anonymous,

Based on my test, you could refer to below steps:

Create a date table and create relationship:

Date = CALENDARAUTO()

1.PNG

Create below calculated columns:

a = CALCULATE (
    SUM ( Table1[joiners]),
    DATESINPERIOD('Date'[Date],'Table1'[Month],-3,MONTH))
b = CALCULATE (
    SUM ( Table1[Leavers]),
    DATESINPERIOD('Date'[Date],'Table1'[Month],-3,MONTH))

Result:

1.PNG

Regards,

Daniel He

Community Support Team _ Daniel He
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

View solution in original post

3 REPLIES 3
v-danhe-msft
Employee
Employee

Hi @Anonymous,

Could you please offer some sample data to have a test or post your data picture if possible?

 

Regards,

Daniel He

Community Support Team _ Daniel He
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Anonymous
Not applicable

Please find the sample, thanks in advance for help:

 

Sample.jpg

Hi @Anonymous,

Based on my test, you could refer to below steps:

Create a date table and create relationship:

Date = CALENDARAUTO()

1.PNG

Create below calculated columns:

a = CALCULATE (
    SUM ( Table1[joiners]),
    DATESINPERIOD('Date'[Date],'Table1'[Month],-3,MONTH))
b = CALCULATE (
    SUM ( Table1[Leavers]),
    DATESINPERIOD('Date'[Date],'Table1'[Month],-3,MONTH))

Result:

1.PNG

Regards,

Daniel He

Community Support Team _ Daniel He
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

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