topic DAX sum with filter in DAX Commands and Tips

DAX sum with filter

Anonymous — Thu, 02 Feb 2023 08:00:24 GMT

Hi,

I have a dataset which looks like this:

I basically need a DAX formula which add's the columns "Order gedaan picking" and "Orders openstaand picking" and filters it for a specific time from the column "Meting van".

Hope you can help.

Re: DAX sum with filter

ValtteriN — Thu, 02 Feb 2023 08:38:04 GMT

Hi,

You can use a simple SUM dax like this:

Measure 30 = SUM('Table (24)'[Order gedaan picking])+SUM('Table (24)'[Orders openstaand picking])

I hope this post helps to solve your issue and if it does consider accepting it as a solution and giving the post a thumbs up!

My LinkedIn: https://www.linkedin.com/in/n%C3%A4ttiahov-00001/

Now place the Time into slicer and you can get the values you want.

Re: DAX sum with filter

Anonymous — Thu, 02 Feb 2023 09:10:23 GMT

ValtteriN

Thank you for for time and efford and i understand what you mean, however to explain better what i need i'll show you what the outcome of this is. (Purple line)

This is incorrect as i would like to see the new orderlines that were generated during the intervals. For 12:30 the correct outcome should be the outcome of he current formule - the outcome of the previous timestamp, in this case 12:00.

Hope you can help.

Re: DAX sum with filter

ValtteriN — Thu, 02 Feb 2023 10:53:34 GMT

Hi,

In that case, something like this should do:

Measure 30 =

var _cur =

SUM('Table (24)'[Order gedaan picking])+SUM('Table (24)'[Orders openstaand picking]) //current time's value

var _prevTime = CALCULATE(MAX('Table (24)'[Time]),ALL('Table (24)'[Time]),'Table (24)'[Time]<MAX('Table (24)'[Time])) //previous time

var _prev = CALCULATE(SUM('Table (24)'[Order gedaan picking]),ALL('Table (24)'[Time]),'Table (24)'[Time]=_prevTime) + CALCULATE(SUM('Table (24)'[Orders openstaand picking]),ALL('Table (24)'[Time]),'Table (24)'[Time]=_prevTime) //previous time's values

return

_cur-_prev

Re: DAX sum with filter

Anonymous — Fri, 03 Feb 2023 08:08:11 GMT

Hi ValtteriN

This is absolutely amazing, thank you very much!