Forum Discussion
Monthly in progress ticket
Hello,
I have a measure that counts the monthly in-progress tickets as below :
Inprogress=
CALCULATE (
COUNTA(BugRun[created]);
FILTER( ALLSELECTED(BugRun);
(BugRun[resolutiondate] = BLANK() || BugRun[resolutiondate]> Max (Calendrier[DateSlicer] ))
&& BugRun[createddate]<=Max ( Calendrier[DateSlicer] )
)
)
The report doesn't stop at the current month, it continues until Dec. I tried to remove the function FILTER, but I have the error :
A function 'MAX' has been used in a True/False expression that is used as a table filter expression. This is not allowed.
Could you please advise?
Many thanks in advance.
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4 Replies
- amitchandak
Super User
Try Maxx in place of max
Maxx ( Calendrier,Calendrier[DateSlicer] )
Appreciate your Kudos. In case, this is the solution you are looking for, mark it as the Solution. In case it does not help, please provide additional information and mark me with @
Thanks. - v-yuta-msft
Community Support
Anonymous ,
No sample data so I'm not sure if code below can achieve your requirement:
Inprogress = CALCULATE ( COUNTA ( BugRun[created] ); FILTER ( ALLSELECTED ( BugRun ); ( BugRun[resolutiondate] = BLANK () || BugRun[resolutiondate] > CALCULATE ( MAX ( Calendrier[DateSlicer] ); ALLSELECTED ( Calendrier ) ) ) && BugRun[createddate] <= CALCULATE ( MAX ( Calendrier[DateSlicer] ); ALLSELECTED ( Calendrier ) ) ) )Community Support Team _ Jimmy Tao
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
- AnonymousNot applicable
Hi v-yuta-msft ,
The data is simple:
created resolutiondate 03/10/2019 13:08:51 null 24/09/2019 16:37:18 10/10/2019 15:42:18 23/09/2019 15:04:10 null 20/09/2019 10:59:42 25/09/2019 16:48:58 20/09/2019 15:36:53 08/10/2019 18:21:26 13/09/2019 11:32:54 20/09/2019 15:20:38 10/09/2019 11:13:42 08/10/2019 15:25:20 10/05/2017 10:01:22 19/10/2018 17:34:33 24/09/2018 12:17:24 16/01/2019 18:31:04 27/03/2018 17:17:50 26/03/2019 18:00:04 17/05/2018 19:10:40 03/06/2019 09:41:22 13/09/2018 11:51:43 16/01/2019 18:30:56 08/10/2018 11:42:11 06/02/2019 12:21:55 08/10/2019 15:20:03 null 08/10/2019 08:34:12 null 30/09/2019 15:26:11 07/10/2019 17:57:11 27/09/2019 09:50:46 null 11/09/2019 09:16:08 11/10/2019 09:32:46 16/09/2019 11:14:48 null 12/07/2019 10:21:56 null 17/09/2018 14:23:38 09/11/2018 14:45:05 30/03/2018 11:51:33 08/03/2019 09:53:41 05/01/2018 15:53:19 23/10/2018 08:39:21 26/03/2018 18:00:42 04/03/2019 17:32:54 08/10/2019 14:46:50 null 07/10/2019 09:46:58 null 01/10/2019 11:31:47 01/10/2019 18:56:07 25/09/2019 16:36:14 null 13/09/2019 11:32:23 null 13/09/2019 19:05:49 null 09/09/2019 09:30:01 08/10/2019 10:40:56 17/01/2018 20:12:41 23/10/2018 12:04:04 12/06/2018 11:42:09 20/11/2018 16:15:22 13/03/2018 18:40:01 16/01/2019 18:31:12 12/10/2018 10:54:14 05/11/2018 18:09:00 04/10/2019 11:58:14 null 25/09/2019 17:39:51 null 12/09/2019 14:28:07 19/09/2019 11:52:24 06/09/2019 09:30:42 12/09/2019 11:38:40 16/08/2018 16:36:51 09/11/2018 15:49:27 17/05/2018 11:37:20 16/01/2019 18:30:55 I tried your measure, but it gives me the same amount of inprogress tickets for all time.
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- AnonymousNot applicable
tHi v-yuta-msft ,
The date is simple as below :
created resolutiondate 03/10/2019 13:08:51 null 24/09/2019 16:37:18 10/10/2019 15:42:18 23/09/2019 15:04:10 null 24/09/2018 12:17:24 16/01/2019 18:31:04 27/03/2018 17:17:50 26/03/2019 18:00:04 17/05/2018 19:10:40 03/06/2019 09:41:22 13/09/2018 11:51:43 16/01/2019 18:30:56 08/10/2018 11:42:11 06/02/2019 12:21:55 08/10/2019 15:20:03 null 08/10/2019 08:34:12 null 30/09/2019 15:26:11 07/10/2019 17:57:11 27/09/2019 09:50:46 null 11/09/2019 09:16:08 11/10/2019 09:32:46 16/09/2019 11:14:48 null 12/07/2019 10:21:56 null 17/09/2018 14:23:38 09/11/2018 14:45:05 30/03/2018 11:51:33 08/03/2019 09:53:41 05/01/2018 15:53:19 23/10/2018 08:39:21 26/03/2018 18:00:42 04/03/2019 17:32:54 08/10/2019 14:46:50 null 07/10/2019 09:46:58 null 01/10/2019 11:31:47 01/10/2019 18:56:07 25/09/2019 16:36:14 null 13/09/2019 11:32:23 null 13/09/2019 19:05:49 null 09/09/2019 09:30:01 08/10/2019 10:40:56 17/01/2018 20:12:41 23/10/2018 12:04:04 12/06/2018 11:42:09 20/11/2018 16:15:22 13/03/2018 18:40:01 16/01/2019 18:31:12 12/10/2018 10:54:14 05/11/2018 18:09:00 04/10/2019 11:58:14 null 25/09/2019 17:39:51 null 12/09/2019 14:28:07 19/09/2019 11:52:24 I tried your suggested measure, but it gives the same amount of tickets all the time.
please advise.
Thanks