Power BI is turning 10! Tune in for a special live episode on July 24 with behind-the-scenes stories, product evolution highlights, and a sneak peek at what’s in store for the future.
Save the dateEnhance your career with this limited time 50% discount on Fabric and Power BI exams. Ends August 31st. Request your voucher.
Hi everybody,
this is my first post.
please help me,
i would like to distinct count vendorNo, with leadtime filter
here is my table
year, vendorNo, Account, Leadtime
2020 | 0007000995 | 7570004000 | 1 |
2020 | 0003000871 | 7520002000 | 1 |
2020 | 0007000316 | 7570003000 | 1 |
2020 | 0007000316 | 7520002001 | 1.5 |
2020 | 0003002554 | 7410009000 | 2 |
2020 | 0003000871 | 7520004001 | 2 |
2020 | 0003002554 | 7570001000 | 2.33333333333333 |
2020 | 0003000871 | 7570003000 | 2.35593220338983 |
2020 | 0003002554 | 7520001000 | 2.5 |
and here is my DAX :
Solved! Go to Solution.
Hi, @Kagechiyo
Please correct me if I am wrong.
I think the result should be 3.
I am not sure about how you wrote your AVGLT measure, but please kindly check the below measure if it is suitable for you.
DAXcountofVendor =
VAR removeGL =
FILTER (
SUMMARIZE (
'average lead time',
'average lead time'[vendor_No],
"avglt", AVERAGEX ( 'average lead time', 'average lead time'[Leadtime] )
),
[avglt] > 0
&& [avglt] <= 2
)
RETURN
COUNTROWS ( removeGL )
Hi, My name is Jihwan Kim.
If this post helps, then please consider accept it as the solution to help other members find it faster.
Hi, @Kagechiyo
Please correct me if I am wrong.
I think the result should be 3.
I am not sure about how you wrote your AVGLT measure, but please kindly check the below measure if it is suitable for you.
DAXcountofVendor =
VAR removeGL =
FILTER (
SUMMARIZE (
'average lead time',
'average lead time'[vendor_No],
"avglt", AVERAGEX ( 'average lead time', 'average lead time'[Leadtime] )
),
[avglt] > 0
&& [avglt] <= 2
)
RETURN
COUNTROWS ( removeGL )
Hi, My name is Jihwan Kim.
If this post helps, then please consider accept it as the solution to help other members find it faster.
thank you, @Jihwan_Kim
after some modification i manage to get what i want..
but i understand that there is another way to count the distinct.
is by grouping.
thanx=]
2020 | ;0007000995 | ;7570004000 | ;1 |
2020 | ;0003003612 | ;7520002000 | ;1 |
2020 | ;0003003638 | ;7570003000 | ;1 |
2020 | ;0007000316 | ;7520002001 | ;1.5 |
2020 | ;0003002480 | ;7410009000 | ;2 |
2020 | ;0003000871 | ;7520004001 | ;2 |
2020 | ;0003002554 | ;7570001000 | ;2.33333333333333 |
2020 | ;0003000871 | ;7570003000 | ;2.35593220338983 |
2020 | ;0003002554 | ;7520001000 | ;2.5 |
User | Count |
---|---|
22 | |
11 | |
8 | |
6 | |
6 |
User | Count |
---|---|
25 | |
12 | |
11 | |
8 | |
6 |