This is best Fabric, Power BI, SQL and AI community event. How do we know? The last event sold out! Save €200 with code FABCMTY200.
Register nowA new Data Days event is coming soon! This time we’re going bigger than ever. Fabric, Power BI, SQL, AI and more. Don't miss out.
Hi everyone,
I am new to PowerBI and I am doing a project for my master. My issue is the following:
I have a table like the following:
| cluster | color | value1 | weights |
| A | blu | 6,8 | 44 |
| A | green | 7,8 | 10 |
| D | blu | 7,9 | 22 |
| B | green | 8,2 | 34 |
| C | green | 8,4 | 23 |
| C | blu | 6,8 | 22 |
| B | blu | 8,4 | 23 |
| A | green | 7,8 | 11 |
The idea is to select one of the 4 clusters (i.e. A) as a filter and have a measure that computes the weighted average of value1 with the weights of the rest of the clusters (B C D).
I've tried several things but I am not even sure if something like this is possible.
The formula that I want to apply is:
SUM(table[value1 (filtered for cluster A)] * table[weights (notA)]) / SUM[weights(notA)]
Thank you in advance 🙂
edit: wrong first term in sum
Solved! Go to Solution.
Hi @Anonymous ,
According to your descriptin, in my understanding, if A is selected in the filter, your expected result is (6.8*44+7.8*10+7.8*11) / (22+34+23+22+23). Here is my solution.
Create a measure.
Measure =
VAR _select =
SUMX (
FILTER ( ALL ( 'myTable' ), 'myTable'[cluster] IN VALUES ( myTable[cluster] ) ),
'myTable'[value1] * 'myTable'[weights]
)
VAR _unselect =
SUMX (
FILTER (
ALL ( 'myTable' ),
NOT ( 'myTable'[cluster] IN VALUES ( myTable[cluster] ) )
),
'myTable'[weights]
)
RETURN
DIVIDE ( _select, _unselect )
Get the result.
I attach my sample below for reference.
Best Regards,
Community Support Team _ kalyj
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi @Anonymous ,
According to your descriptin, in my understanding, if A is selected in the filter, your expected result is (6.8*44+7.8*10+7.8*11) / (22+34+23+22+23). Here is my solution.
Create a measure.
Measure =
VAR _select =
SUMX (
FILTER ( ALL ( 'myTable' ), 'myTable'[cluster] IN VALUES ( myTable[cluster] ) ),
'myTable'[value1] * 'myTable'[weights]
)
VAR _unselect =
SUMX (
FILTER (
ALL ( 'myTable' ),
NOT ( 'myTable'[cluster] IN VALUES ( myTable[cluster] ) )
),
'myTable'[weights]
)
RETURN
DIVIDE ( _select, _unselect )
Get the result.
I attach my sample below for reference.
Best Regards,
Community Support Team _ kalyj
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hey @Anonymous ,
it would be easier with a real file or tables. But the following approach should do it:
Weighted Average =
VAR vSelectedClusters = VALUES ( myTable[cluster] )
VAR vWeightNotCluster =
CALCULATE (
SUM ( myTable[weights] ),
ALL ( myTable ),
NOT ( myTable[weights] ) IN vSelectedClusters
)
RETURN
( SUM ( myTable[weights] ) * vWeightNotCluster ) / vWeightNotCluster
If you need any help please let me know.
If I answered your question I would be happy if you could mark my post as a solution ✔️ and give it a thumbs up 👍
Best regards
Denis
Blog: WhatTheFact.bi
Follow me: twitter.com/DenSelimovic
Hi, thanks for your reply!
I tried this answer and it says there's an error:
Error Message:
MdxScript(Model) (47, 45) Calculation error in measure 'overall_pivot_table'[Weighted Average]:
The function 'CONTAINSROW' does not support the comparison between values of type Text and type Integer.
Try to use the functions VALUE or FORMAT to convert one of the values.
I translated from italian.
I edit my post with the right formula.
Sign up to receive a private message when registration opens and key events begin.
If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.
| User | Count |
|---|---|
| 33 | |
| 26 | |
| 21 | |
| 20 | |
| 15 |
| User | Count |
|---|---|
| 63 | |
| 43 | |
| 28 | |
| 24 | |
| 22 |