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.
This is the sample data that I am having, now I want to group the activities based on their 'Basecode', 'Bucket Start Date', and 'Bucket End Date', and then calculate the average count of limits within each group. I want to represent this information in a stacked chart, where the x-axis shows the time intervals (bucket weeks) and the y-axis displays the average count of limits. I cannot use the Group by function and removing duplicates as it will result in loss of other data at granular level. I want to create a measure which do the calculation for me.
| Base Code | Bucket Start Date | Bucket End Date | Limits | |
| 1 | 100 | 05-02-2024 | 29-02-2024 | Below Limit |
| 1 | 100 | 01-03-2024 | 31-03-2024 | Above Limit |
| 1 | 100 | 04-02-2024 | 05-02-2024 | Within Limit |
| 1 | 100 | 05-02-2024 | 29-02-2024 | Below Limit |
| 2 | 100 | 01-03-2024 | 31-03-2024 | Above Limit |
| 2 | 100 | 04-02-2024 | 05-02-2024 | Within Limit |
| 1 | 100 | 01-03-2024 | 31-03-2024 | Above Limit |
The output that I am looking is like this,
| Base Code | Bucket Start Date | Bucket End Date | Limits |
| 100 | 01-03-2024 | 31-03-2024 | 3(Above Limit)/3 (unique values) = 100% |
| 100 | 05-02-2024 | 29-02-2024 | 2 (Below Limit)/3 = 66.67% |
| 100 | 04-02-2024 | 05-02-2024 | 2 (Within Limit)/3 = 66.67% |
I saw we can do this using Summarize and AverageX function. Any help would be greatly appreciated.
Solved! Go to Solution.
@JunedS , Based on what I got, You need a measures like
Total Unique Limits =
DISTINCTCOUNT('Table'[Limits])
Count Above Limit =
CALCULATE(
COUNTROWS('Table'),
'Table'[Limits] = "Above Limit"
)
Count Below Limit =
CALCULATE(
COUNTROWS('Table'),
'Table'[Limits] = "Below Limit"
)
Count Within Limit =
CALCULATE(
COUNTROWS('Table'),
'Table'[Limits] = "Within Limit"
)
Percentage Above Limit =
DIVIDE(
[Count Above Limit],
[Total Unique Limits],
BLANK()
)
Percentage Below Limit =
DIVIDE(
[Count Below Limit],
[Total Unique Limits],
BLANK()
)
Percentage Within Limit =
DIVIDE(
[Count Within Limit],
[Total Unique Limits],
BLANK()
)
@JunedS , Based on what I got, You need a measures like
Total Unique Limits =
DISTINCTCOUNT('Table'[Limits])
Count Above Limit =
CALCULATE(
COUNTROWS('Table'),
'Table'[Limits] = "Above Limit"
)
Count Below Limit =
CALCULATE(
COUNTROWS('Table'),
'Table'[Limits] = "Below Limit"
)
Count Within Limit =
CALCULATE(
COUNTROWS('Table'),
'Table'[Limits] = "Within Limit"
)
Percentage Above Limit =
DIVIDE(
[Count Above Limit],
[Total Unique Limits],
BLANK()
)
Percentage Below Limit =
DIVIDE(
[Count Below Limit],
[Total Unique Limits],
BLANK()
)
Percentage Within Limit =
DIVIDE(
[Count Within Limit],
[Total Unique Limits],
BLANK()
)
Check out the May 2026 Power BI update to learn about new features.
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 |
|---|---|
| 27 | |
| 26 | |
| 22 | |
| 19 | |
| 17 |
| User | Count |
|---|---|
| 45 | |
| 42 | |
| 41 | |
| 21 | |
| 18 |