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I have the following table call [Table]:
Where Number and Date are given
IE and FE are calculated columns and are given by the user.
IE = DATE(2019;09;01)
FE = DATE(2020;01;01)
And total is calculated column and is:
Total = IF(AND('Table'[Date]<'Table'[FE];'Table'[Date]>'Table'[IE]);DATEDIFF('Table'[Date];'Table'[FE];HOUR);0)
Then i create the following measure:
Medida = AVERAGE('Table'[Total])
Now, I add to the model the following table call [Dates]:
What I need is evaluate [Medida] with IE=FI and FE=FF, this means repeat the formula in the measure [Medida] changing the inputs IE and FE depending on which row of [Table] is and store the result in a new table or column.
My expected results if I store the result in a new column in [Table] (for the first rows are):
I already try a calculated column in table like this:
Columna = CALCULATE(FORMAT([Medida];"General Number");FILTER('Table';AND('Table'[IE]=Dates[FI];'Table'[FE]=Dates[FF])))
But it does not work because IE and FE in [Table] (First image in the post) are the same date in every row.
Do you have any idea?
Thanks.
Solved! Go to Solution.
I solved it with the following function:
Tabla = ADDCOLUMNS(SUMMARIZE(Dates;Dates[FF];Dates[FI]);"A1";AVERAGEX('Table';IF(AND('Table'[Date]>Dates[FI];'Table'[Date]<Dates[FF]);DATEDIFF('Table'[Date];Dates[FF];HOUR);0)))
It´s not the best way to do it but it was the only I can create consistent results.
😃
Hi,
I have a similar issue: forecast table with a measure which calculate dinamically Net
Model | 1-Arrears before week 2403 | Week 2404 21/01/24 27/01/24 | Week 2405 28/01/24 03/02/24 | Week 2406 04/02/24 10/02/24 | Week 2407 11/02/24 17/02/24 | ||||||||||||
Part | Description | Tot Stock | Demand | Supply | Net | Demand | Supply | Net | Demand | Supply | Net | Demand | Supply | Net | Demand | Supply | Net |
R0042001599 | BANANAS | 48207 | 440 | 40000 | 87767 | 5478 | 82289 | 6800 | 20000 | 95489 | 9072 | 86417 | 13608 | 72809 | |||
R0042001619 | APPLES | 13607 | 58 | 1600 | 15149 | 15149 | 720 | 14429 | 400 | 14029 | 312 | 13717 | |||||
R0042001649 | PEARS | 20193 | 1868 | 18325 | 2200 | 12000 | 28125 | 1386 | 8000 | 34739 | 3150 | 31589 | 3780 | 27809 |
The current Net measure works fine
Current measure
Net measure: =
VAR _initialstock =
MAX ( 'Net measure V2'[TOTSTOCK] )
VAR _newtablesupplydemand =
SUMX (
FILTER (
ALL ( 'Net measure V2' ),
'Net measure V2'[Item] = MAX ( 'Net measure V2'[Item] )
&& 'Net measure V2'[Week] <= MAX ( 'Net measure V2'[Week] )
),
'Net measure V2'[Supply] - 'Net measure V2'[Demand]
)
RETURN
_initialstock + _newtablesupplydemand
What I would like to achieve is a next step forecast: is there some way from week 1 to know Net of week 4 (basically next month)
Here an example: for item APPLE At first week I would like to know forecast week 2406 Net is 86417
Model 01 | 1-Arrears before week 2403 | Week 2406 04/02/24 10/02/24 | ||||||
Part | Description | Tot Stock | Demand | Supply | Net | Demand | Supply | Net |
R0042001599 | BANANAS | 48207 | 440 | 40000 | 87767 | 9072 | 86417 |
I solved it with the following function:
Tabla = ADDCOLUMNS(SUMMARIZE(Dates;Dates[FF];Dates[FI]);"A1";AVERAGEX('Table';IF(AND('Table'[Date]>Dates[FI];'Table'[Date]<Dates[FF]);DATEDIFF('Table'[Date];Dates[FF];HOUR);0)))
It´s not the best way to do it but it was the only I can create consistent results.
😃
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