I need to Aggregate a number of multiplications which are based on the Row and Columns context. My best attempt at describing this is in pseudo-code.
For each cell in the Pivot table
SUM
Foreach ORU
Percent= Look up the multiplier for that ORU associated with the Column
SUMofValue = Add all of the Values associated with that Column/Row combination
Multiply Percent * SUMofValue
I tried a number of ways over the last few days and looked at loads of examples but am missing something.
Specifically, What won't work is:
CALCULATE(SUM(ORUBUMGR[Percent]), ORUMAP)*CALCULATE(SUM(Charges[Value]), ORUMAP)
because you're doing a sum of all the Percentages instead of the sum of the Percentages which are only associated with MGR (i.e., the column context)
Link to XLS
One way of doing that is by using nested SUMX. Add this measure to ORUBUMGR:
ValuexPercent :=
SUMX (
ORUBUMGR,
[PERCENT]
* (
SUMX (
FILTER ( CHARGES, CHARGES[ORU] = ORUBUMGR[ORU] ),
[Value]
)
)
)
For each row in ORUBUMGR you will multiply percent by ....
the sum of value for each row in Charges where ORUBUMGR ORU is the same as Charges ORU. Then you sum that product.
Related
I am working on a matrix in Power BI and I am not figuring out how to sum each column recursively until the total:
And this should be the resulting matrix (as an example, rows):
Some clarifications:
The months (columns) are dynamically generated based on the transaction month. I could filter the data to get the same data for only three months.
"Nombre proveedor" stands for "Vendor name".
I don't care about "Total" row.
These are my values:
So, I think I should create a measure with DAX to replace "Accounting Balance" to sum the previous column (month) or show nothing (to avoid zeroes).
Searching on internet I found several sites to get the running totals by rows, but not by columns.
Any suggestions?
Try Something like this:
Maesure =
CALCULATE (
[Accounting Balance],
FILTER (
ALL ( 'table' ),
'table'[Transaction month] <= MAX ( 'table'[Transaction month] )
)
)
I have the following DAX-formula to retrieve the opening and closing balance for a list of products.
=CALCULATE(MAX(transactions[Balance]);
FILTER(transactions;
transactions[ID] = MAX(transactions[ID])
)
)
This works on row level in my Pivot but when I group this och Product category level I only get one value and not the sum of all the product rows.
My data contains of rows for each transaction and each row have a columns with current balance.
How do I sum each row to get the group sum for the above category "00-01" 26784 and 283500?
One way to do this is to leverage an iterative function like a SUMX.
Assuming that your EndValue is the measure that you defined.
SUMX_Example := SUMX( VALUES ( transactions[ID] ) , [EndValue] )
Which will do the following:
Though VALUES ( transactions[ID] ) it will generate a list of your IDs
For each ID it will run your already created [EndValue] measure
Sum the result of each ID's end value
This is of course assuming [ID] does not cover categories. If ID does cross categories, then you would first do a SUMX using category, with another SUMX that does ID
This should be a fairly easy question for Power Pivot users since I'm a newbie. I am trying to do the following. After pivoting a table I get a crosstab table like this
rating count of id
A 1
B 2
Grand Total 3
You can imagine the original table only has two columns (rating and id) and three rows (1 id for A and two different id's for the B rating). What DAX formula do I have to write in order to create a measure that simply shows
rating percent of id
A 1/3
B 2/3
Grand Total 3/3
By 1/3 of course I mean 0.3333, I wrote it like that so that it is clear that I simply want that percent of id is the count for each rating divided by the total count. Thank you very much
You need to divide the count for each row by the total count.
DIVIDE (
COUNT ( Table1[ID] ),
CALCULATE ( COUNT ( Table1[ID] ), ALL ( Table1 ) )
)
For this particular calculation, you don't have to write DAX though. You can just set it in the Value Field Settings.
Summarize Value By : Count
Show Values As : % of Column Total
I'm trying to show the total closing balance by month for the dataset below:
[Tranche] [Maturity Date] [Balance]
T1 1-Jan-16 1000
T2 2-Jan-16 200
T3 1-Jan-16 3000
T3 3-Jan-16 2900
T1 31-Jan-16 1000
T2 1-Feb-16 200
T3 31-Jan-16 3000
T3 2-Feb-16 2900
I have joined the dataset (table LoanSched) with a dates lookup table (Dates).
Here's the DAX calculated field formula:
=CALCULATE (
SUM(LoanSched[Balance]),
FILTER ( Dates, Dates[FullDate] = MAX(LoanSched[Maturity Date]) )
)
However, I get the result below which is incorrect. Since Tranche T2's balance ends on a date earlier than T3, the balance is excluded in the monthly total. The way the dataset works, is that the total balance should included balances that appear on the last day of each month and tranche. I'm missing the tranche condition.
I need to calculate the correct balances (highlighted in yellow) below:
So what you have here is a form of a semi-additive measure, though I don't quite understand that grand total as it relates to the subtotals - what it says to me is that each "tranche-maturity date" combination is an independent instrument, so it doesn't entirely make sense to use traditional time intelligence - like instead of months that could just be some other arbitrary hierarchy. Is that correct?
Anyway, based on your criteria, what you want is basically
a calculated measure that returns the last non blank balance within a month for a given tranche;
another measure which adds up that measure for each tranche to get a "maturity month balance";
and then a final measure that adds up that measure for each maturing month to get a "total balance".
For #1, this is the traditional formula:
TrancheEndingBalance := CALCULATE (
SUM ( ClosingBalance[Balance]),
LASTNONBLANK (
Dates[FullDate],
CALCULATE ( SUM ( ClosingBalance[Balance] ) )
)
)
And then #2 is just a SUMX across tranches:
MaturityMonthEndingBalance :=
SUMX ( VALUES ( ClosingBalance[Tranche] ), [TrancheEndingBalance] )
And #3 a SUMX across maturity months:
TotalEndingBalance :=
SUMX ( VALUES ( Dates[MonthYear] ), [MaturityMonthEndingBalance] )
Please note these measures essentially only work for the layout you've described, but it sounds like that's the only way to get at the correct balance for a given set of tranches and maturity dates, so form follows function, as it were.
I have a requirement in Power Pivot where I need to show value based on the Dimension Column value.
If value is Selling Price then Amount Value of Selling Price from Table1 should display, if Cost Price then Cost Price Amount Should display, if it is Profit the ((SellingPrice-CostPrice)/SellingPrice) should display
My Table Structure is
Table1:-
Table2:-
Required Output:-
If tried the below option:-
1. Calculated Measure:=If(Table[Category]="CostPrice",[CostValue],If(Table1[category]="SellingPrice",[SalesValue],([SalesValue]-[CostValue]/[SalesValue])))
*[CostValue]:=Calculate(Sum(Table1[Amount]),Table1[Category]="CostPrice")
*[Sales Value]:=Calculate(Sum(Table1[Amount]),Table1[Category]="SellingPrice")
Tried this in both Calculated Column and Measure but not giving me required output.
Cost:=
CALCULATE(
SUM( Table1[Amount] )
,Table1[Category] = "CostPrice"
)
Selling:=
CALCULATE(
SUM( Table1[Amount] )
,Table1[Category] = "SellingPrice"
)
Profit:=
DIVIDE(
[Selling] - [Cost]
,[Selling]
)
ConditionalMeasure:=
IF(
HASONEFILTER( Table2[Category] )
,SWITCH(
VALUES( Table2[Category] )
,"CostPrice"
,[Cost]
,"SellingPrice"
,[Selling]
,"Profit"
,[Profit]
)
,[Profit]
)
HASONEFILTER() checks that there is filter context on the named field and that the filter context includes only a single distinct value.
This is just a guard to allow our SWITCH() to refer to VALUES( Table2[Category] ). VALUES() returns a table of all distinct values in the named column or table. So, a 1x1 table can be implicitly converted to a scalar, which we need in SWITCH().
SWITCH() is a case statement.
Our else condition in the IF() is just returning [Profit]. You might want something else, but it's unclear what should happen at the grand total level. You can leave this off, and the measure will be blank in IF()'s else condition.
I was thinking about this a little. I'm not sure why you have your categories on rows. Usually the data set would have columns like: item | CostPrice | SellingPrice | Profit. Then you can just use the columns to define your fields. The model becomes easier and more maintainable.