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SQUILES Frequent Visitor

## sum range date

HI, everyone...

I have have a table with dates and values, i need to calculate (column) two totals.

total1 = current value  + sum(13 days previous of this date)

total2 = sum(next 14 days of the previous of that date)

Example:

Total1 for 7/1/2019 = value of 7/1/2019 + range 6/30/2019 - 6/18/2019 (13 days)

Total2 for 7/1/2019 = range from 6/17/2019 to 6/4/2019 (next 14 days)

Any help 1 ACCEPTED SOLUTION

Accepted Solutions
Highlighted Community Support Team

## Re: sum range date

Hi @SQUILES ,

To create measures as below.

```total1 =
VAR dat =
DATE ( 2019, 07, 01 )
VAR last13 = dat - 13
RETURN
CALCULATE (
SUM ( 'Table'[vale] ),
FILTER ( 'Table', 'Table'[date] >= last13 && 'Table'[date] <= dat )
)
```
```total 2 =
VAR d =
DATE ( 2019, 07, 01 )
VAR a = d - 14
VAR c = a - 13
RETURN
CALCULATE (
SUM ( 'Table'[vale] ),
FILTER ( 'Table', 'Table'[date] <= a && 'Table'[date] >= c )
)
``` Community Support Team _ Frank
If this post helps, then please consider Accept it as the solution to help the others find it more quickly.
3 REPLIES 3 Super User

## Re: sum range date

You are going to need to use EARLIER. See my article on Mean Time Between Failure (MTBF) which uses EARLIER: http://community.powerbi.com/t5/Community-Blog/Mean-Time-Between-Failure-MTBF-and-Power-BI/ba-p/3395...

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Proud to be a Datanaut!

Highlighted Community Support Team

## Re: sum range date

Hi @SQUILES ,

To create measures as below.

```total1 =
VAR dat =
DATE ( 2019, 07, 01 )
VAR last13 = dat - 13
RETURN
CALCULATE (
SUM ( 'Table'[vale] ),
FILTER ( 'Table', 'Table'[date] >= last13 && 'Table'[date] <= dat )
)
```
```total 2 =
VAR d =
DATE ( 2019, 07, 01 )
VAR a = d - 14
VAR c = a - 13
RETURN
CALCULATE (
SUM ( 'Table'[vale] ),
FILTER ( 'Table', 'Table'[date] <= a && 'Table'[date] >= c )
)
``` Community Support Team _ Frank
If this post helps, then please consider Accept it as the solution to help the others find it more quickly.
SQUILES Frequent Visitor

## Re: sum range date

@v-frfei-msft  thanks, very much....

The Dax work excellent!!! very grateful!!! thanks again.

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