Last 12 months data from current month

Hi Anonymous ,

Please try below steps:

1. below is my test table

Table:

2. create measure with below dax formula

Combine =
VAR cur_date =
    SELECTEDVALUE ( 'Table'[Date] )
VAR _value =
    YEAR ( cur_date ) * 100
        + MONTH ( cur_date )
RETURN
    _value

RK = RANKX(ALL('Table'),[Combine],,ASC,Dense)

Measure =
VAR last_date =
    MAXX ( ALL ( 'Table' ), [Date] )
VAR rk =
    CALCULATE ( [RK], FILTER ( ALL ( 'Table' ), [Date] = last_date ) )
VAR tmp =
    CALCULATETABLE (
        VALUES ( 'Table'[Date] ),
        FILTER ( ALL ( 'Table' ), [RK] > rk - 12 )
    )
VAR cur_date =
    SELECTEDVALUE ( 'Table'[Date] )
RETURN
    IF ( cur_date IN tmp, 1, 0 )

Year and Qtr =
VAR cur_date =
    SELECTEDVALUE ( 'Table'[Date] )
VAR cur_qtr = [Qtr]
VAR _value =
    YEAR ( cur_date ) * 100 + cur_qtr
RETURN
    _value

RK For Qtr = RANKX(ALL('Table'),[Year and Qtr],,ASC,Dense)

Condition for Qtr =
VAR last_date =
    MAXX ( ALL ( 'Table' ), [Date] )
VAR rk =
    CALCULATE ( [RK For Qtr], FILTER ( ALL ( 'Table' ), [Date] = last_date ) )
VAR tmp =
    CALCULATETABLE (
        VALUES ( 'Table'[Date] ),
        FILTER ( ALL ( 'Table' ), [RK For Qtr] > rk - 4 )
    )
VAR cur_date =
    SELECTEDVALUE ( 'Table'[Date] )
RETURN
    IF ( cur_date IN tmp, 1, 0 )

Year and Week Num =
VAR cur_data =
    SELECTEDVALUE ( 'Table'[Date] )
VAR wn = [Week Num]
RETURN
    YEAR ( cur_data ) * 100 + wn

RK for Week Num = RANKX(ALL('Table'),[Year and Week Num],,ASC,Dense) 

Condition for Week Num =
VAR last_date =
    MAXX ( ALL ( 'Table' ), [Date] )
VAR rk =
    CALCULATE ( [RK for Week Num], FILTER ( ALL ( 'Table' ), [Date] = last_date ) )
VAR tmp =
    CALCULATETABLE (
        VALUES ( 'Table'[Date] ),
        FILTER ( ALL ( 'Table' ), [RK for Week Num] > rk - 52 )
    )
VAR cur_date =
    SELECTEDVALUE ( 'Table'[Date] )
RETURN
    IF ( cur_date IN tmp, 1, 0 )

3. add a table visual with fields, add measure to it filter pane

Please refer the attached .pbix file.

Best regards,
Community Support Team_ Binbin Yu
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