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I am looking for a formula to return a vol that matches the date 01/08/25 and the ID BEL_14667/0 from the table below when forecast A matches forecast b
| BEL_14667/0 | |||
| 01/08/2025 | #NAME? | ||
| ID | forecast A | forecast b | Vol |
| BEL_14667/0 | 01/07/2025 | 01/07/2025 | 232,932 |
| BEL_14667/0 | 01/07/2025 | 01/08/2025 | 195,613 |
| BEL_14667/0 | 01/07/2025 | 01/09/2025 | 239,887 |
| BEL_14667/0 | 01/07/2025 | 01/10/2025 | 294,476 |
| BEL_14667/0 | 01/07/2025 | 01/11/2025 | 327,610 |
| BEL_14667/0 | 01/07/2025 | 01/12/2025 | 149,035 |
| BEL_14667/0 | 01/08/2025 | 01/08/2025 | 220,000 |
| BEL_14667/0 | 01/08/2025 | 01/09/2025 | 239,887 |
| BEL_14667/0 | 01/08/2025 | 01/10/2025 | 294,476 |
Solved! Go to Solution.
Hi @Julier,
Try below DAX:-
Vol_Match =
CALCULATE(
MAX(Table[Vol]),
Table[ID] = "BEL_14667/0",
Table[forecast A] = Table[forecast b],
Table[forecast b] = DATE(2025,8,1)
)
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Hello !
Thank you for posting on Fabric community.
You can filter the table to just the rows where ID = BEL_14667/0 and forecastA = forecastB = #date(2025,8,1)
and from that filtered table, take the first match vol value if no row matches return null.
= let
Source =
#table(
type table [ID = text, forecastA = date, forecastB = date, Vol = number],
{
{"BEL_14667/0", #date(2025, 7, 1), #date(2025, 7, 1), 232932},
{"BEL_14667/0", #date(2025, 7, 1), #date(2025, 8, 1), 195613},
{"BEL_14667/0", #date(2025, 7, 1), #date(2025, 9, 1), 239887},
{"BEL_14667/0", #date(2025,10, 1), #date(2025,10, 1), 294476},
{"BEL_14667/0", #date(2025,11, 1), #date(2025,11, 1), 327610},
{"BEL_14667/0", #date(2025,12, 1), #date(2025,12, 1), 149035},
{"BEL_14667/0", #date(2025, 8, 1), #date(2025, 8, 1), 220000},
{"BEL_14667/0", #date(2025, 8, 1), #date(2025, 9, 1), 239887},
{"BEL_14667/0", #date(2025, 8, 1), #date(2025,10, 1), 294476}
}
),
TargetID = "BEL_14667/0",
TargetDate = #date(2025, 8, 1),
Filtered = Table.SelectRows(
Source,
each [ID] = TargetID and [forecastA] = TargetDate and [forecastB] = TargetDate
),
ResultVol = if Table.IsEmpty(Filtered) then null else Filtered{0}[Vol]
in
ResultVol
you can find the solution in the pbix file.
Hi @Julier ,
I wanted to check if you had the opportunity to review the information provided by @AmiraBedh, @grazitti_sapna . Please feel free to contact us if you have any further questions.
Thank you and continue using Microsoft Fabric Community Forum.
Hello !
Thank you for posting on Fabric community.
You can filter the table to just the rows where ID = BEL_14667/0 and forecastA = forecastB = #date(2025,8,1)
and from that filtered table, take the first match vol value if no row matches return null.
= let
Source =
#table(
type table [ID = text, forecastA = date, forecastB = date, Vol = number],
{
{"BEL_14667/0", #date(2025, 7, 1), #date(2025, 7, 1), 232932},
{"BEL_14667/0", #date(2025, 7, 1), #date(2025, 8, 1), 195613},
{"BEL_14667/0", #date(2025, 7, 1), #date(2025, 9, 1), 239887},
{"BEL_14667/0", #date(2025,10, 1), #date(2025,10, 1), 294476},
{"BEL_14667/0", #date(2025,11, 1), #date(2025,11, 1), 327610},
{"BEL_14667/0", #date(2025,12, 1), #date(2025,12, 1), 149035},
{"BEL_14667/0", #date(2025, 8, 1), #date(2025, 8, 1), 220000},
{"BEL_14667/0", #date(2025, 8, 1), #date(2025, 9, 1), 239887},
{"BEL_14667/0", #date(2025, 8, 1), #date(2025,10, 1), 294476}
}
),
TargetID = "BEL_14667/0",
TargetDate = #date(2025, 8, 1),
Filtered = Table.SelectRows(
Source,
each [ID] = TargetID and [forecastA] = TargetDate and [forecastB] = TargetDate
),
ResultVol = if Table.IsEmpty(Filtered) then null else Filtered{0}[Vol]
in
ResultVol
you can find the solution in the pbix file.
Hi @Julier,
Try below DAX:-
Vol_Match =
CALCULATE(
MAX(Table[Vol]),
Table[ID] = "BEL_14667/0",
Table[forecast A] = Table[forecast b],
Table[forecast b] = DATE(2025,8,1)
)
🌟 I hope this solution helps you unlock your Power BI potential! If you found it helpful, click 'Mark as Solution' to guide others toward the answers they need.
💡 Love the effort? Drop the kudos! Your appreciation fuels community spirit and innovation.
🎖 As a proud SuperUser and Microsoft Partner, we’re here to empower your data journey and the Power BI Community at large.
🔗 Curious to explore more? [Discover here].
Let’s keep building smarter solutions together!
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