How to do Pivoting in Power BI using DAX - powerbi

I have the below table.
I want the resulting output like below.Is there a way using the DAX to get this?

You can get this matrix visual with a very simple measure and setting the empname on the rows and the status on the columns like folows:
# Status = COUNTROWS( T )

Related

Create a Power BI measure to sum a column where another column meets a requirement

I'm new to DAX and I'm trying to do something that would be really simple in Excel!
Using data from the same table, I'm trying to add a measure, that calculates my 'TargetCost' column where the 'NameUnit' is '1111'.
if nameunit = 1111 then sum the target cost
In excel the formula would be:
=sumif(nameunit,"1111",targetcost)
How do I write this into a measure in DAX please?
Here you go:
Measure =
CALCULATE(
SUM('Table'[targetcost]),
'Table'[nameunit] = "1111"
)
https://learn.microsoft.com/en-us/dax/calculate-function-dax

Power BI Min date of each category

I am familiar with SQL and I can write a query to return results of a query to Select MIN(Date), MAX(Date), SUM(quality) and GROUP BY. However, I am new to Power BI and DAX and find it difficult to do the same on Power BI. Below is my situation.
These tables on Power BI:
Dim_ManefactureDate
Dim_ReleaseDate
Fact_OrderID
Table Relationships
Adding a table visualization to a new page to show data from three tables above, data is showing as below:
Under Values of Visualizations, when selecting SUM over Netweight, it automatically summarizes expected Netweight. However, for ManufactureDate and ReleaseDate, when selecting Earliest then Power BI table shows unexpected 1/01/1900 values like this:
I expect earliest date of each OrderID as below:
I have also tried to use a DAX function to create a new column but it gets error
ManufactureDate_Earliest =
VAR Sum_Netweight = SUM(Fact_OrderID[NetWeight])
VAR GroupBy_OrderID = GROUPBY(Fact_OrderID,Fact_OrderID[OrderID])
RETURN
CALCULATE(
MIN(RELATED(Dim_ManufactureDate[DateBK]))
)
Thank you very much for your help
Due to getting values from relationship tables, used these measured and solved the issue
ManufactureDate_Earliest =
CALCULATE(
MIN(ManufactureDate[DateBK]),
CROSSFILTER(Fact_Order[ManufactureDate_DateSK], ManufactureDate[DateSK], BOTH)
)
ReleaseDate_Earliest =
CALCULATE(
MIN(ReleaseDate[DateBK]),
CROSSFILTER(Fact_Order[ReleaseDate_DateSK], ReleaseDate[DateSK], BOTH)
)

Power BI Dax Measure moving Sum by categories

im struggling with the following problem. I have categorical variables and and Amount column. What I want to do is, to write a dax measure which calculates the moving/rolling Sum, like you see in the third column "Dax Measure". Did not find any inhouse Dax function for that.
moving sum
EDIT:
Result Table with Dax Measure
Source Table
This will work if the category is always sorted ASC.
Dax measure =
VAR _currentRank = RANKX(ALL('Table'[Category]),CALCULATE(MIN('Table'[Category])),,ASC)
RETURN
CALCULATE(
CALCULATE(SUM('Table'[Amount]),TOPN(_currentRank,VALUES('Table'[Category]),MIN([Category]))),
ALL('Table'[Category])
)
Using RANKX to define the other and aggregating for all the item before it.

need assistance\ideas on building what is hopefully a simple DAX measure

I am trying to figure out the DAX to create a new measure in an SSAS Tabular data model. An example of what I am trying to do is more easily shown than described. My SSAS Tabular dataset produces the following table. Cols A and B are from the stores table, Col C is a measure from the Sales table, Col D is a measure from the Products table, and Col E is C/D. This all works fine. Data has been mocked up in Excel to protect the innocent, but it is working in Power BI.
What I would like to do is add a new measure which calculates the Sales/Product at the state level and have that measure show for each store in that state, as shown below
Presumably I have to iterate over all rows and calculate the total sales/state and total products sold/state and divide those 2 to get the answer, but can't work out the DAX to get there. I have tried numerous combinations of
calculate(
sumx(...),
filter(
all(...),
...
)
)
to no avail.
You should use FILTER with ALL to manipulate a context(remove current context);
MesureSumStateLevel = calculate(SUM('Table'[Amount]),
FILTER(ALL('StoreStateTab'), 'StoreStateTab'[State] =
SELECTEDVALUE('StoreStateTab'[State])))
https://dax.guide/filter/
https://dax.guide/selectedvalue/
https://dax.guide/all/
Thanks for the tip. I originally tried that and dropped it because I couldn't get it working. I revisited this morning and solved it. Here is what I did:
State Ttl =
var trxYr = convert(SELECTEDVALUE(dim_date[Year]), INTEGER) //needed because Year is stored as text in the model
var trxMo = SELECTEDVALUE(dim_Date[Short Month Name])
var trxState = SELECTEDVALUE(fact_Sales[state])
Return
CALCULATE(
SUM(fact_sales[SalesAmt])
,all(fact_sales)
,year(fact_sales[SaleDATE]) = trxYr
,dim_Date[Short Month Name] = trxMo
,dim_Stores[state] = trxState
)

Creating an Index Column for a Descriptive Data Using “DAX” in Power BI

I have a table Like this,
Table1
I want to create a column called as Row Number using DAX and not Query Editor (M).
So the Expected output is,
This can be done in M - Power Query Side.
But, I am looking for a solution using DAX- Calculated Column.
Additional source data
The RANKX function should work fine for this purpose.
Row Number = RANKX ( Table1, Table1[ColA] )
Recommended reading:
https://radacad.com/how-to-use-rankx-in-dax-part-1-of-3-calculated-columns